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Zeileis, Achim, Christian Kleiber, and Simon Jackman. "Regression Models for Count Data in R." Foundation for Open Access Statistics, 2008. http://epub.wu.ac.at/4986/1/Zeileis_etal_2008_JSS_Regression%2DModels%2Dfor%2DCount%2DData%2Din%2DR.pdf.
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The classical Poisson, geometric and negative binomial regression models for count data belong to the family of generalized linear models and are available at the core of the statistics toolbox in the R system for statistical computing. After reviewing the conceptual and computational features of these methods, a new implementation of hurdle and zero-inflated regression models in the functions hurdle() and zeroinfl() from the package pscl is introduced. It re-uses design and functionality of the basic R functions just as the underlying conceptual tools extend the classical models. Both hurdle and zero-inflated model, are able to incorporate over-dispersion and excess zeros-two problems that typically occur in count data sets in economics and the social sciences-better than their classical counterparts. Using cross-section data on the demand for medical care, it is illustrated how the classical as well as the zero-augmented models can be fitted, inspected and tested in practice. (authors' abstract)
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Zeileis, Achim, Christian Kleiber, and Simon Jackman. "Regression Models for Count Data in R." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 2007. http://epub.wu.ac.at/1168/1/document.pdf.
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The classical Poisson, geometric and negative binomial regression models for count data belong to the family of generalized linear models and are available at the core of the statistics toolbox in the R system for statistical computing. After reviewing the conceptual and computational features of these methods, a new implementation of zero-inflated and hurdle regression models in the functions zeroinfl() and hurdle() from the package pscl is introduced. It re-uses design and functionality of the basic R functions just as the underlying conceptual tools extend the classical models. Both model classes are able to incorporate over-dispersion and excess zeros - two problems that typically occur in count data sets in economics and the social and political sciences - better than their classical counterparts. Using cross-section data on the demand for medical care, it is illustrated how the classical as well as the zero-augmented models can be fitted, inspected and tested in practice. (author's abstract)Series: Research Report Series / Department of Statistics and Mathematics
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Reineck, Viktor, and Folke Ulfsparre. "The Impact of Weather on Residential Fires in Sweden: A Regression Analysis." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254304.
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The purpose of this report is to investigate possible relationships between the number of residential fires in Sweden and various weather parameters. The study is conducted based on a hypothesis as stated by the MSB, the Swedish Civil Contingencies Agency, that behavioral factors related to weather can have an influence on the number of residential fires. Generalized linear models within the regression analysis have been used and specifically Poisson and negative binomial regression. The aim was to map the possible connection and determine if it was possible to use the analysis as a tool to improve the emergency services in Sweden. Temperature, short term differences in temperature and precipitation were analyzed with residential fires as the dependent variable, which resulted in a model for each municipality in Sweden. The relationships between the weather parameters and residential fires, seen throughout Sweden, proved to be weak to non-existent with one exception. The average temperature variable was significant in 117 out of 290 municipalities and indicated a relationship where the expected number of residential fires decreases at temperature increases. Due to the weak relationships, the model is not recommended as a prognostic tool on a national level. However, individual models could be used as a supplement to current prognostic tools at a local level and used for preventive purposes. Thus, the study has concluded that weather has some impact on the expected number of residential fires and thus has the potential to be used as a tool when forecasting residential fires. As an addition to the regression analysis, an organizational analysis of the emergency services in Sweden is carried out. The analysis sought the optimal structure based on the emergency services conditions and requirements, which were defined on the basis of organizational concepts and methods. The result was a more structured operation and organization where methods and processes are managed at a centralized level.Syftet med denna rapport är att undersöka eventuella samband mellan antalet bostadsbränder i Sverige och olika väderparametrar. Studien genomförts mot bakgrund av en hypotes ställd av MSB, Myndigheten för Samhällsskydd och Beredskap, om att beteendefaktorer relaterade till vädret kan ha en påverkan på antalet bostadsbränder. Generaliserade linjära modeller inom regressionsanalysen har använts och specifikt Poisson- och negativ binomialregression. Målet var att kartlägga det eventuella sambandet och avgöra huruvida det var möjligt att nyttja analysen som verktyg för att förbättra räddningstjänsten i Sverige. Temperatur, kortsiktig temperaturförändring och nederbörd analyserades med bostadsbränder som den beroende variabeln, vilket resulterade i en modell för varje svensk kommun. Sambanden mellan väderparametrarna och bostadsbränder, sett över hela Sverige, visade sig vara svaga till obefintliga med ett undantag. Variabeln för genomsnittstemperatur var signifikant i 117 av 290 kommuner och visade på ett samband där förväntat antal bostadsbränder minskar vid ökad temperatur. På grund av de svaga sambanden, sett över hela Sverige, rekommenderas inte modellen som prognostiskt verktyg på nationell nivå. Däremot skulle enskilda modeller kunna användas som komplement till nuvarande prognostiska verktyg på lokal nivå, samt användas i förebyggande syfte. Därmed har studien kommit fram till att väder har viss påverkan på det förväntade antalet bostadsbränder och således har potential att användas som verktyg vid prognos av bostadsbränder. Som ett komplement till regressionsanalysen genomförs en organisatorisk analys av räddningstjänsten i Sverige. Analysen sökte den optimala strukturen utifrån räddningstjänstens förutsättningar och krav, som definierades utifrån grundläggande organisatoriska begrepp och metoder. Resultatet blev en mer strukturerad verksamhet där metoder och processer sköts på en centraliserad nivå.
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Shrestha, Shivesh. "Development of structural condition thresholds for TSD measurements." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78039.
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This thesis presents (a) results of a field evaluation of the Traffic Speed Deflectometer (TSD) in the United States (b) deflection thresholds to classify the pavement structural condition obtained from the TSD for a small subset of the Pennsylvania secondary road network. The results of the field evaluation included: (1) repeatability of the TSD, (2) ability of the TSD to identify pavement sections with varying structural conditions, and (3) consistency between the structural number (SNeff) calculated from the TSD and SNeff calculated by the Pennsylvania Department of Transportation (PennDOT). The results showed consistent error standard deviation in the TSD measurements and that the TSD was able to identify pavement sections that varied in structural condition. Comparison of the SNeff calculated with TSD measurements, using an empirically developed equation by Rohde, with the SNeff calculated by PennDOT’s Pavement Management System based on construction history showed similar trends, although the TSD-calculated SNeff was higher.
In order to develop deflection thresholds, a model that related the pavement surface condition to pavement surface age and structural condition was developed. Structural condition thresholds were then selected so that the pavement surface condition predicted from the model for a 10-year-old pavement surface fell within one of the three condition categories (Good, Fair, and Poor), to identify pavements in good, fair and poor condition. With Overall Pavement Index(OPI) characterizing the surface condition and Deflection Slope Index(DSI) characterizing the structural condition, the DSI threshold that separates structurally good from structurally fair pavements was determined as follows: (1) the OPI threshold that separates pavements with good surface condition from those with fair surface condition was obtained from the Pennsylvania Pavement Management System (PMS) and (2) the DSI thresholds were calculated using the determined OPI value and the model equation.Master of Science
This thesis presents (a) some of the results of a field evaluation of the Traffic Speed Deflectometer (TSD) in the United States (b) deflection thresholds to classify the pavement structural condition obtained from the TSD for a small subset of the Pennsylvania secondary road network. The results of the field evaluation included: (1) repeatability of the TSD: which is the variation in repeated TSD measurements on the same section of the road, (2) ability of the TSD to identify pavement sections with varying structural conditions, and (3) consistency between the structural number (SNeff) calculated from the TSD and SNeff calculated by the Pennsylvania Department of Transportation (PennDOT). The pavement structural number is an abstract number expressing the structural strength of the pavement. The results showed that the TSD measurements were repeatable and that the TSD was able to identify pavement sections that varied in structural condition. Comparison of the SNeff calculated with TSD measurements, using an empirically developed equation by Rohde, with the SNeff calculated by PennDOT Pavement Management System based on construction history showed similar trends, although the TSD-calculated SNeff was higher. In order to develop deflection thresholds to categorize pavements in different condition: good, fair and poor, a model that related the pavement surface condition to pavement surface age and structural condition was developed. Structural condition thresholds were then selected so that the pavement surface condition predicted from the model for a 10-year-old pavement surface fell within one of the three condition categories (Good, Fair, and Poor), to identify pavements in good, fair and poor condition. With Overall Pavement Index(OPI) characterizing the surface condition and Deflection Slope Index(DSI) characterizing the structural condition, the DSI threshold that separates structurally good from structurally fair pavements was determined as follows: (1) the OPI threshold that separates pavements with good surface condition from those with fair surface condition was obtained from the Pennsylvania Pavement Management System (PMS) and (2) the DSI thresholds were calculated using the determined OPI value and the model equation.
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Pemmanaboina, Rajashekar. "Assessing Crash Occurrence On Urban Freeways Using Static And Dynamic Factors By Applying A System Of Interrelated Equations." Master's thesis, University of Central Florida, 2005. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2617.
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Traffic crashes have been identified as one of the main causes of death in the US, making road safety a high priority issue that needs urgent attention. Recognizing the fact that more and effective research has to be done in this area, this thesis aims mainly at developing different statistical models related to the road safety. The thesis includes three main sections: 1) overall crash frequency analysis using negative binomial models, 2) seemingly unrelated negative binomial (SUNB) models for different categories of crashes divided based on type of crash, or condition in which they occur, 3) safety models to determine the probability of crash occurrence, including a rainfall index that has been estimated using a logistic regression model. The study corridor is a 36.25 mile stretch of Interstate 4 in Central Florida. For the first two sections, crash cases from 1999 through 2002 were considered. Conventionally most of the crash frequency analysis model all crashes, instead of dividing them based on type of crash, peaking conditions, availability of light, severity, or pavement condition, etc. Also researchers traditionally used AADT to represent traffic volumes in their models. These two cases are examples of macroscopic crash frequency modeling. To investigate the microscopic models, and to identify the significant factors related to crash occurrence, a preliminary study (first analysis) explored the use of microscopic traffic volumes related to crash occurrence by comparing AADT/VMT with five to twenty minute volumes immediately preceding the crash. It was found that the volumes just before the time of crash occurrence proved to be a better predictor of crash frequency than AADT. The results also showed that road curvature, median type, number of lanes, pavement surface type and presence of on/off-ramps are among the significant factors that contribute to crash occurrence. In the second analysis various possible crash categories were prepared to exactly identify the factors related to them, using various roadway, geometric, and microscopic traffic variables. Five different categories are prepared based on a common platform, e.g. type of crash. They are: 1) Multiple and Single vehicle crashes, 2) Peak and Off-peak crashes, 3) Dry and Wet pavement crashes, 4) Daytime and Dark hour crashes, and 5) Property Damage Only (PDO) and Injury crashes. Each of the above mentioned models in each category are estimated separately. To account for the correlation between the disturbance terms arising from omitted variables between any two models in a category, seemingly unrelated negative binomial (SUNB) regression was used, and then the models in each category were estimated simultaneously. SUNB estimation proved to be advantageous for two categories: Category 1, and Category 4. Road curvature and presence of On-ramps/Off-ramps were found to be the important factors, which can be related to every crash category. AADT was also found to be significant in all the models except for the single vehicle crash model. Median type and pavement surface type were among the other important factors causing crashes. It can be stated that the group of factors found in the model considering all crashes is a superset of the factors that were found in individual crash categories. The third analysis dealt with the development of a logistic regression model to obtain the weather condition at a given time and location on I-4 in Central Florida so that this information can be used in traffic safety analyses, because of the lack of weather monitoring stations in the study area. To prove the worthiness of the weather information obtained form the analysis, the same weather information was used in a safety model developed by Abdel-Aty et al., 2004. It was also proved that the inclusion of weather information actually improved the safety model with better prediction accuracy.M.S.C.E.
Department of Civil and Environmental Engineering
Engineering and Computer Science
Civil Engineering
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Prasad, Jonathan P. "Zero-Inflated Censored Regression Models: An Application with Episode of Care Data." BYU ScholarsArchive, 2009. https://scholarsarchive.byu.edu/etd/2226.
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The objective of this project is to fit a sequence of increasingly complex zero-inflated censored regression models to a known data set. It is quite common to find censored count data in statistical analyses of health-related data. Modeling such data while ignoring the censoring, zero-inflation, and overdispersion often results in biased parameter estimates. This project develops various regression models that can be used to predict a count response variable that is affected by various predictor variables. The regression parameters are estimated with Bayesian analysis using a Markov chain Monte Carlo (MCMC) algorithm. The tests for model adequacy are discussed and the models are applied to an observed data set.
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Lindberg, Erik. "A study of the effect of inbreeding in Skellefteå during the 19th century : Using Cox Proportional hazard model to analyze lifespans and Poisson/Negative Binomial regression to analyze fertility." Thesis, Umeå universitet, Statistik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-122687.
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Inbreeding is defined as when two individuals who are related mate and produce offspring. The level of inbreeding for an individual can be determined by calculating an inbreeding coefficient. Inbreeding can enhance both positive and negative traits. The risk for recessive diseases also increase. Data from old church records from the region of Skellefteå covering individuals from the late 17th century to the early 20th century has been made available. From this data parent-child relations can be observed and levels of inbreeding calculated. By analyzing the available data using Cox Proportional Hazard regression model it was shown that the level inbreeding affected the lifespan of an individual negatively if the parents are second cousins or more closely related. Using Poisson- and Negative Binomial regression, no evicence of an effect of inbreeding of fertility could be found.
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Vavilikolanu, Srutha. "Crash Prediction Models on Truck-Related Crashes on Two-lane Rural Highways with Vertical Curves." University of Akron / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=akron1221758522.
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Darby, Phillip. "The assessment of driver and manager training in the context of work-related road safety interventions." Thesis, Loughborough University, 2016. https://dspace.lboro.ac.uk/2134/20900.
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Vehicles being driven for work purposes represent a large proportion of road collision and deaths in the workplace. These observations mean that people driving for work can impose a large burden on organisations and on society. In addition, previous studies identified a fleet driver effect for which there was greater collision risk for those who drive for work compared to the general driving population, even after controlling for exposure. This accentuates the need for both organisational and government policy makers to take steps to reduce the impact of these collisions. No single intervention has been found to solve issues around work-related road safety therefore a range of initiatives have been directed towards the risks associated with drivers, vehicles, journeys and organisations. Many of the interventions, however, lack robust evidence to support their use. The aim of this thesis is to assess organisational interventions to improve work-related road safety by using econometric models on real-world data. The data represents driving claims made between 2005 and 2012 by employees of a large UK company, with a fleet of approximately 35,000 vehicles. The drivers were employed in a variety of roles such as working in technical positions at customer sites or making sales visits. The company has applied a range of strategies to road safety resulting in annual claim reductions of 7.7% compared to only a 4.5% reduction in collisions nationally. The company s data are used to undertake three studies which focused on driver training, manager training and claim segmentation. Statistical models were employed to investigate the effect of two different driver training courses on the frequency of claims while controlling for other factors. The results indicated that driver training courses significantly reduced both the total number of claims and the claim types targeted by the training. The impacts of the interventions were also adjusted for the effects of non-random driver selection and other safety improvements initiated by the company or other agencies. An important finding of this work was that randomly inflated pre-training events accounted for between a third and a quarter of the observed reduction in claims following training. The second study evaluated the impact of management training on claims using multilevel models which allowed for correlation between observations. The study could not confirm that this training was an effective safety intervention. This null result provides an incentive to re-evaluate the implementation of the scheme. The final study identified homogeneous claim segments using statistical models and the impact of training was evaluated on these segments. Such claims were estimated to be reduced by between 32% to 55% following existing driver training courses. This thesis has helped close important gaps and contributed to knowledge in terms of both intervention methodology and the understanding of the effectiveness of work-related road safety interventions. The results, which are already being applied in the case study organisation, demonstrated that training employees in either safe and fuel efficient driving, or low speed manoeuvring, reduced vehicle insurance claims. Further work is necessary to verify the safety value of manager training including gathering detailed information on interactions between managers and drivers.
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Coyle, Jesse Aaron. "Optimization of nuclear, radiological, biological, and chemical terrorism incidence models through the use of simulated annealing Monte Carlo and iterative methods." Thesis, Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43599.
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A random search optimization method based off an analogous process for the slow cooling of metals is explored and used to find the optimum solution for a number of regression models that analyze nuclear, radiological, biological,and chemical terrorism targets. A non-parametric simulation based off of historical data is also explored. Simulated series of 30 years and a 30 year extrapolation of historical data are provided. The inclusion of independent variables used in the regression analysis is based off existing work in the reviewed literature. CBRN terrorism data is collected from both the
Monterey Institute's Weapons of Mass Destruction Terrorism Database as well as from the START Global Terrorism Database. Building similar models to those found in the literature and running them against CBRN terrorism incidence data determines if conventional terrorism indicator variables are also significant predictors of CBRN terrorism targets. The negative binomial model was determined to be the best regression model available for the data analysis. Two general types of models are developed, including an economic development model and a political risk model. From the economic development model we find that national GDP, GDP per capita, trade openness, and
democracy to significant indicators of CBRN terrorism targets. Additionally from the political risk model we find corrupt, stable, and democratic regimes more likely to
experience a CBRN event. We do not find language/religious fractionalization to be a significant predictive variable. Similarly we do not find ethnic tensions, involvement in external conflict, or a military government to have significant predictive value.
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Urbieta, Pablo Cezar. "Gráficos CUSUM e EWMA para monitorar dados de contagem com distribuição binominal negativa." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/3/3136/tde-30092016-143355/.
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Gráficos de controle têm sido amplamente utilizados na manufatura para melhoria de processos. Diversas abordagens tem sido propostas para melhorar o desempenho dos gráficos existentes na literatura. Além disso, o uso de gráficos de controle tem se estendido para outras áreas, tais como, economia, finanças, medicina, etc. O objetivo deste trabalho é comparar o gráfico CUSUM com o gráfico EWMA para monitoramento do número diário de internações hospitalares. Para tanto, utilizou-se uma série histórica de internações devido a doenças respiratórias para a população acima de 65 anos. Um modelo linear foi ajustado considerando que o número de internações segue uma distribuição Binomial Negativa. São simulados diversos cenários de mudança no número médio de internações e utilizando diferentes estatísticas baseadas em transformações, é feita uma comparação entre estes gráficos. Verifica-se que o gráfico EWMA com limite de controle assintótico possui desempenho muito similar ao gráfico CUSUM. Já o EWMA implementado com limite de controle exato apresenta melhor desempenho em relação ao gráfico CUSUM quando se atribui pesos menores aos dados atuais.Control charts have been widely used for process improvement in manufacturing. In literature several approaches have been proposed to improve the current charts performance. In addition, the use of control charts has been extended to other areas such as economics, finance, medicine, and others. The objective of this study is to compare CUSUM control chart with EWMA control chart for monitoring daily number of hospital admissions. Using a historical hospitalizations series due to respiratory diseases for people over 65 years old, a Negative Binomial regression model is fitted. Several scenarios are simulated using different shifts in the mean and using different statistics based on transformations, in order to compare these charts. It is shown that EWMA control chart with asymptotic control limit has similar performance as CUSUM control chart. However, using smaller values for new observations the EWMA control chart with exact control limit has better performance than CUSUM control chart.
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Pihl, Svante, and Leonardo Olivetti. "An Empirical Comparison of Static Count Panel Data Models: the Case of Vehicle Fires in Stockholm County." Thesis, Uppsala universitet, Statistiska institutionen, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-412014.
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In this paper we study the occurrences of outdoor vehicle fires recorded by the Swedish Civil Contingencies Agency (MSB) for the period 1998-2019, and build static panel data models to predict future occurrences of fire in Stockholm County. Through comparing the performance of different models, we look at the effect of different distributional assumptions for the dependent variable on predictive performance. Our study concludes that treating the dependent variable as continuous does not hamper performance, with the exception of models meant to predict more uncommon occurrences of fire. Furthermore, we find that assuming that the dependent variable follows a Negative Binomial Distribution, rather than a Poisson Distribution, does not lead to substantial gains in performance, even in cases of overdispersion. Finally, we notice a slight increase in the number of vehicle fires shown in the data, and reflect on whether this could be related to the increased population size.
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Dias, Ishani Madurangi. "Work zone crash analysis and modeling to identify factors associated with crash severity and frequency." Diss., Kansas State University, 2015. http://hdl.handle.net/2097/20517.
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Doctor of PhilosophyCivil Engineering
Sunanda Dissanayake
Safe and efficient flow of traffic through work zones must be established by improving work zone conditions. Therefore, identifying the factors associated with the severity and the frequency of work zone crashes is important. According to current statistics from the Federal Highway Administration, 2,372 fatalities were associated with motor vehicle traffic crashes in work zones in the United States during the four years from 2010 to 2013. From 2002 to 2014, an average of 1,612 work zone crashes occurred in Kansas each year, making it a serious concern in Kansas. Objectives of this study were to analyze work zone crash characteristics, identify the factors associated with crash severity and frequency, and to identify recommendations to improve work zone safety. Work zone crashes in Kansas from 2010 to 2013 were used to develop crash severity models. Ordered probit regression was used to model the crash severities for daytime, nighttime, multi-vehicle and single-vehicle work zone crashes and for work zones crashes in general. Based on severity models, drivers from 26 to 65 years of age were associated with high crash severities during daytime work zone crashes and driver age was not found significant in nighttime work zone crashes. Use of safety equipment was related to reduced crash severities regardless of the time of the crash. Negative binomial regression was used to model the work zone crash frequency using work zones functioned in Kansas in 2013 and 2014. According to results, increased average daily traffic (AADT) was related to higher number of work zone crashes and work zones in operation at nighttime were related to reduced number of work zone crashes. Findings of this study were used to provide general countermeasure ideas for improving safety of work zones.
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Lameira, Verônica de Castro. "Dois ensaios sobre mobilidade de trabalhadores no Brasil." Universidade Federal de Juiz de Fora, 2012. https://repositorio.ufjf.br/jspui/handle/ufjf/1684.
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CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
A análise da mobilidade de trabalhadores exerce papel fundamental na tomada de decisões em políticas públicas. O primeiro ensaio aborda a questão da mobilidade de curta e longa distância, e ainda os fatores regionais da atração de trabalhadores entre as microrregiões do Brasil, utilizando modelo binomial negativo. Houve a constatação da preferência dos trabalhadores por destinos com maior atratividade relativa, admissão de trabalhadores frente aos desligados, densidade, proporção de graduados, menor criminalidade e congestionamento. Para o modelo de longa distância os fluxos são orientados para destinos com menor densidade populacional, menor grau de industrialização, menor criminalidade e maior atração relativa. O congestionamento se mostrou irrelevante na mobilidade de longa distância. A distância figura como fator inibidor para a mobilidade, independente dos cortes de distância. O segundo ensaio adota o modelo logit multinível espacial com o objetivo de identificar os condicionantes individuais e regionais da mobilidade de trabalhadores qualificados nas microrregiões brasileiras. Foi possível verificar que a experiência do trabalhador figura como fator inibidor da mobilidade, a expectativa salarial reflete menor propensão à mudança para trabalhadores em geral, e maior probabilidade para qualificados. Algumas variáveis de contexto também se mostram importantes para explicar a mobilidade, como PIB per capita, proporção de trabalhadores com ensino superior completo, taxa de homicídio, veículos por habitantes, grau de industrialização e rede de migrantes.
The analysis of labor mobility plays a fundamental role in decision-making in public policy. The first essay addresses the issue of mobility by long and short distance, and the regional factors of attraction for workers among Brazilian microregions, by means of negative binomial model. There was the realization of the preferred destinations for workers with higher relative attractiveness, employment of workers off against, density, proportion of graduates, less crime and congestion. To model long-distance flows are oriented destinations with lower population density, lower degree of industrialization, less crime and greater relative attractiveness. Congestion proved irrelevant in the long-distance mobility. The distance appears as an inhibiting factor for mobility, regardless of the cuts away. The second essay adopts a spatial multilevel logit model in order to identify the determinants of individual and regional mobility of skilled workers in the Brazilian microregions. The results indicate that the worker seniority figures as inhibitory factor of mobility, and expected wage decrease the propensity of mobility for workers in general, though it increases the propensity of the more skilled ones. The context variables also show important to explain mobility, such as GDP per capita, proportion of workers with higher education, rate of homicide by vehicle inhabitants, degree of industrialization and net migrants.
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Khoeini, Sara. "Modeling framework for socioeconomic analysis of managed lanes." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/53408.
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Managed lanes are a form of congestion pricing that use occupancy and toll payment requirements to utilize capacity more efficiently. How socio-spatial characteristics impact users’ travel behavior toward managed lanes is the main research question of this study. This research is a case study of the conversion of a High Occupancy Vehicle (HOV) lane to a High Occupancy Toll (HOT) lane, implemented in Atlanta I-85 on 2011. To minimize the cost and maximize the size of the collected data, an innovative and cost-effective modeling framework for socioeconomic analysis of managed lanes has been developed. Instead of surveys, this research is based on the observation of one and a half million license plates, matched to household locations, collected over a two-year study period. Purchased marketing data, which include detailed household socioeconomic characteristics, supplemented the household corridor usage information derived from license plate observations. Generalized linear models have been used to link users’ travel behavior to socioeconomic attributes. Furthermore, GIS raster analysis methods have been utilized to visualize and quantify the impact of the HOV-to-HOT conversion on the corridor commutershed. At the local level, this study conducted a comprehensive socio-spatial analysis of the Atlanta I-85 HOV to HOT conversion. At the general scale, this study enhances managed lanes’ travel demand models with respect to users’ characteristics and introduces a comprehensive modeling framework for the socioeconomic analysis of managed lanes. The methods developed through this research will inform future Traffic and Revenue Studies and help to better predict the socio-spatial characteristics of the target market.
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Zhou, Wei. "Bayesian Model Selections for Log-binomial Regression." University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1544101297752931.
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Soumare, Ibrahim. "Comparing Performance of ANOVA to Poisson and Negative Binomial Regression When Applied to Count Data." Thesis, North Dakota State University, 2020. https://hdl.handle.net/10365/31887.
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Analysis of Variance (ANOVA) is the easiest and most widely used model nowadays in statistics. ANOVA however requires a set of assumptions for the model to be a valid choice and for the inferences to be accurate. Among many, ANOVA assumes the data in question is normally distributed and homogenous. However, data from most disciplines does not meet the assumption of normality and/or equal variance. Regrettably, researchers do not always check whether the assumptions are met, and if these assumptions are violated, inferences might well be wrong.
We conducted a simulation study to compare the performance of standard ANOVA to Poisson and Negative Binomial models when applied to counts data. We considered different combination of sample sizes and underlying distributions. In this simulation study, we first assed Type I error for each model involved. We then compared power as well as the quality of the estimated parameters across the models.
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Aghlmandi, Soheila. "Outliers detection in INAR(1) model with negative binomial innovations." Master's thesis, Universidade de Aveiro, 2012. http://hdl.handle.net/10773/9875.
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Mestrado em Matemática e AplicaçõesOs processos de contagem, apesar de serem largamente usados na pr atica, continuam a ser alvo de investiga c~ao. Neste trabalho considera-se o processo de contagem autorregressivo de 1a ordem - INAR(1). O objetivo principal consiste em tratar o problema da dete c~ao de outliers aditivos em processos INAR(1), considerando uma distribui c~ao binomial negativa para o processo de inova c~oes. Aplica-se a abordagem bayesiana, atrav es da amostragem de Gibbs, para estimar a probabilidade de que uma observa c~ao seja afetada por um outlier. A metodologia proposta e ilustrada atrav es de v arios exemplos simulados e conjuntos de dados reais.
Discrete-valued, or so called Integer-valued, time series is widely used in practice; but still it can be considered as a new subject for research nowadays. In this context, the variables of the process take place on nite or countable in nite sets. In this work, we study rst-order INteger-valued AutoRegressive, INAR(1), processes. The main goal, however, is to develop the statistical expressions for detecting outliers for the model, by considering the distributions of innovations as negative binomial. The Binomial thinning operator is used in process. This work considers a Bayesian approach to the problem of modeling a negative binomial integer-valued autoregressive time series contaminated with additive outliers. Furthermore, we focus on computational part of detecting the outliers of INAR(1) process where we use R software. We show how Gibbs sampling can be used to detect outlying observations in INAR(1) processes.
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Bäcklund, JOakim, and Johdet Nils. "A Bayesian approach to predict the number of soccer goals : Modeling with Bayesian Negative Binomial regression." Thesis, Linköpings universitet, Statistik och maskininlärning, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-149028.
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This thesis focuses on a well-known topic in sports betting, predicting the number of goals in soccer games.The data set used comes from the top English soccer league: Premier League, and consists of games played in the seasons 2015/16 to 2017/18.This thesis approaches the prediction with the auxiliary support of the odds from the betting exchange Betfair. The purpose is to find a model that can create an accurate goal distribution. %The other purpose is to investigate whether Negative binomial distribution regressionThe methods used are Bayesian Negative Binomial regression and Bayesian Poisson regression. The results conclude that the Poisson regression is the better model because of the presence of underdispersion.We argue that the methods can be used to compare different sportsbooks accuracies, and may help creating better models.
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Iragavarapu, Vichika. "Examining factors affecting the safety performance and design of exclusive truck facilities." Texas A&M University, 2007. http://hdl.handle.net/1969.1/85809.
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Many state agencies consider exclusive truck facilities to be an alternative to
handle the safety and operational issues due to the increasing truck volumes. No such
facilities exist, and there are no standard tools or procedures for measuring safety
performance of an exclusive truck facility. This thesis aims at identifying factors that
affect truck crashes, whose results could be used for better designing exclusive truck
facilities. To accomplish the objectives of this thesis, five years' roadway and crash data
for Texas was collected to develop a comprehensive crash database. Negative binomial
regression models were used to establish a relationship between truck crashes and various
environmental, geometric and traffic variables. Separate models were developed for
truck-related (involving at least one truck and another vehicle), truck-only (two trucks or
more) and single-truck crashes. The results suggested that the percentage of trucks in
Average Annual Daily Traffic (AADT), classification of the roadway (Rural/Urban),
posted speed limit, surface condition, alignment and shoulder width are associated with
truck crashes. It was observed that truck-related and truck-only crashes decreased as the
percentage of trucks increased on freeway facilities. Based on conclusions derived from
the literature review and statistical analyses, straight segments with wider shoulders and
uniform grades are recommended for exclusive truck facilities. It is also recommended to
provide ramps, horizontal and vertical curvature and signing based on truck size, driver
eye height, braking ability and maneuverability. These models were developed using
mixed-flow traffic data to understand the association of various factors with truck
crashes. These models should not be used directly to estimate or predict truck crashes.
Further analysis with more detailed data under different flow conditions might help in
quantifying the safety performance of exclusive truck facilities.
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Ellison, Natalie Noel. "The Effect of Smoking on Tuberculosis Incidence in Burdened Countries." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/2977.
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It is estimated that one third of the world's population is infected with tuberculosis. Though once thought a "dead" disease, tuberculosis is very much alive. The rise of drug resistant strains of tuberculosis, and TB-HIV coinfection have made tuberculosis an even greater worldwide threat. While HIV, poverty, and public health infrastructure are historically assumed to affect the burden of tuberculosis, recent research has been done to implicate smoking in this list. This analysis involves combining data from multiple sources in order determine if smoking is a statistically significant factor in predicting the number of incident tuberculosis cases in a country. Quasi-Poisson generalized linear models and negative binomial regression will be used to analyze the effect of smoking, as well as the other factors, on tuberculosis incidence. This work will enhance tuberculosis control efforts by helping to identify new hypotheses that can be tested in future studies. One of the main hypotheses is whether or not smoking increases the number of tuberculosis cases above and beyond the effects of other factors that are known to influence tuberculosis incidence. These known factors include TB-HIV coinfection, poverty and public health infrastructure represented by treatment outcomes.
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Workman, Amanda Claire. "Can Mentoring Help Reduce the Risk of Recidivism? An Analysis of the Serious and Violent Offender Reentry Initiative (SVORI) Data." BYU ScholarsArchive, 2018. https://scholarsarchive.byu.edu/etd/6827.
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This research project investigates the effectiveness of mentors on rates of self-reported criminal offending for released offenders. I use data from the Serious and Violent Offender Reentry Initiative (SVORI) study (2004-2007), which sought to evaluate factors relating to high-risk offenders outcomes post release in an effort to reduce the societal problem of mass incarceration. Previous research has examined the use of mentors to improve the delinquent and criminogenic behavior of youth, but little is known about the effectiveness of mentors used to aid imprisoned adult males. I utilize negative binomial analysis to compare the number of self-reported criminal activities among released offenders with mentors versus those without mentors, and assess if the values varied between different reported levels of need for mentoring. Results indicate that mentoring did not reduce the rate of post-release offending at a statistically significant level. Reasons for the lack of significant results and policy implications are discussed.
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Bhattarai, Shreejana. "Understanding the relationship between land use/land cover and malaria in Nepal." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/96214.
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Malaria is one of the leading causes of mortality and morbidity globally. Land use/land cover (LULC) change have been found to affect the transmission and distribution of malaria in other regions, but no study has attempted to examine such relationships in Nepal. Therefore, this study was conducted in Nepal to assess LULC change between 2000 and 2010, to study the spatial and temporal trend of malaria incidence rate (MIR) between 1999 and 2015, and to understand the relationship between LULC and malaria. The land cover types used for this study are forest, water bodies, agriculture, grassland, shrubland, barren areas, built-up areas and paddy areas. Change detection techniques were used to study LULC change. The temporal trend of MIR in 58 districts, and the relationship between MIR and LULC were evaluated using Poisson and negative binomial regression. Forest, water bodies, snow cover, and built-up area increased in Nepal by 28.5%, 2.96%, 55.12% and 21.19% respectively while the rest of the LULC variables decreased. MIR decreased significantly in 21 districts; however, four districts namely Pyuthan, Kaski, Rupandehi and Siraha had a significantly increasing trend of MIR. During 2001, 2002, and 2003, MIR was positively related to water bodies and paddy areas. Similarly, MIR of 2010 was negatively related to grassland. However, there was no relationship between LULC and MIR in 2000, 2011, 2012 and 2013. It may be because MIR is decreasing significantly in the country and thus the influence of LULC change is also decreasing.MS
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Bhaktha, Nivedita. "Properties of Hurdle Negative Binomial Models for Zero-Inflated and Overdispersed Count data." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1543573678017356.
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Kowdla, Smitha. "MODELING CRASH FREQUENCIES AT SIGNALIZED INTERSECTIONS IN CENTRAL FLOR." Master's thesis, University of Central Florida, 2004. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3836.
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A high percentage of highway crashes in the United States occur at intersections. These crashes result in property damage, lost productivity, injury, and even death. Identifying intersections associated with high crash rate is very important to minimize future crashes. The purpose of this study is to develop efficient means to evaluate intersections, which may require safety improvements. The area covered by the analysis in this thesis includes Orange and Seminole Counties and the City of Orlando. The aforementioned counties and city thus represent Central Florida. Each County/City provided data that consisted of signalized intersection drawings that were either in the form of electronic or hard copies, the county's extensive crash database and a list of intersections that underwent modifications during the study period. A total of 786 intersections were used in the analysis and the crash database was made up of 4271 crashes. From the signalized intersection drawings obtained from the county's traffic engineering department, a geometry database was created to classify all intersections by the number of through lanes, number of left turning lanes, Average Annual Daily Traffic and Posted Speed limits on the Major road of the intersection. In this research, crashes and their type, e.g., rear-end, left-turn and angle as well as total crashes were investigated. Numerous models were developed first using the Poisson regression and then using the Negative Binomial approach as the data showed overdispersion. The modeling process aimed to relate geometric and traffic factors to the frequency of crashes at intersections. Expected value analysis tables were also developed to determine if an intersection had an abnormally high number of crashes. These tables can be used in assisting Traffic Engineers in identifying serious safety problems at intersections. The general models illustrated that rear-end crashes were associated with high natural logarithm of AADT on the major road and the number of lanes (major intersections, e.g. 6x4/6x6), whereas AADT on the major road did not affect left-turn crashes. Intersections with the configuration 4x2/6x2 (2 through lanes at the minor roadway) or T intersections as another category experienced an increase in left-turn crashes. Angle crashes were most frequent at one-way intersections especially in the case of 4x4 intersections. Individual models that included interaction terms with one variable at a time concluded that AADT on the major road positively influenced rear-end crashes more compared to angle and left-turn crashes. As the speed increases on the minor road, the left turn crashes are affected more when compared to angle and rear-end crashes, therefore it can be concluded that left-turn crashes are most influenced by the speed limit on the minor road compared to angle crashes and then followed by rear-end crashes. As the total number of left turn lanes increased at the intersection, thereby increasing the size of the intersection, the number of rear-end crashes increased. An overall model that contained natural logarithm of AADT on major road, total number of left turn lanes at the intersection, number of through lanes on the minor road and configuration of the intersection, as independent variables, along with interaction terms, further concluded and supported the individual models that the number of crashes (rear-end, left-turn and angle) increased as the AADT on the major road increased and the number of crashes decreased as the total number of left turn lanes at the intersection increased. Also, crashes increased as the number of through lanes on the minor road increased. The variables' interaction effects with dummies representing rear-end and left-turn crashes in the final model showed that as the AADT on the major road increased, the number of rear-end crashes increased compared to left-turn and angle crashes and also that as the total number of left turn lanes at the intersection increased, the number of left-turn crashes decreased when compared to rear-end and angle crashes. Also the number of rear-end crashes increased at major four leg intersections e.g. 6x4, 6x6 etc. This thesis demonstrated the superiority of Negative Binomial regression in modeling the frequency of crashes at signalized intersections.M.S.
Department of Civil and Environmental Engineering
Engineering and Computer Science
Civil Engineering
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Radimer, Scott. "Masculine Norms, Ethnic Identity, Social Dominance Orientation, And Alcohol Consumption Among Undergraduate Men." Thesis, Boston College, 2016. http://hdl.handle.net/2345/bc-ir:105070.
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Thesis advisor: Heather Rowan-KenyonAccording to the National Center for Health Statistics (2007), 18-24 year olds are most likely to report heavy drinking in the past year compared to other adults. Heavy alcohol use is problematic not only in itself, but also because it is associated with a host of other negative outcomes. Research has identified traditional-age college men (age 18-24), who are White, and members of a Greek organization or athletic team as the most likely to consume alcohol in excess (Ham & Hope, 2003; Hingson & White, 2012). White men, members of Greek organizations, and college athletes are also the populations least likely to change their behavior as a result of current alcohol interventions employed by colleges and universities (Fachini, Aliane, Martinez, & Furtado, 2012; LaBrie, Pedersen, Lamb, & Quinlan, 2007; Lundahl, Kunz, Brownell, Tollefson, & Burke, 2010; Mattern & Neighbors, 2004). The primary shortcoming of previous research into this problem, is that it has failed to take an intersectional approach to the phenomenon of college men’s alcohol use. To address this gap, this study surveyed 1,457 college men across five college in the Northeastern United States, using the Conformity to Masculine Norms Inventory (CMNI; Mahalik et al., 2003) the Revised Multigroup Ethnic Identity Measure (MEIM-R; Phinney & Ong, 2007) and the Social Dominance Orientation scale (SDO; Pratto, Sidanius, Stallworth, & Malle, 1994). Alcohol consumption was predicted using zero-inflated negative binomial regressions and zero-inflated Poisson regressions, and alcohol problems were predicted using logistic regressions. The study found that the college men’s drinking was primarily predicted by the masculine norms of risk taking, having power over women, emotional control, and desiring multiple sexual partners. Although the sample size was smaller, for non-White respondents in the study, men’s drinking was also predicted by a focus on heterosexual presentation, and the SDO factor of group based dominance. Alcohol problems were largely predicted by the same masculine norms
Thesis (PhD) — Boston College, 2016
Submitted to: Boston College. Lynch School of Education
Discipline: Educational Leadership and Higher Education
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Wright, Joshua P. "Geospatial and Negative Binomial Regression Analysis of Culex nigripalpus, Culex erraticus, Coquillettidia perturbans, and Aedes vexans Counts and Precipitation and Land use Land cover Covariates in Polk County, Florida." Scholar Commons, 2017. http://scholarcommons.usf.edu/etd/6983.
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Although mosquito monitoring systems in the form of dry-ice bated CDC light traps and sentinel chickens are used by mosquito control personnel in Polk County, Florida, the placement of these are random and do not necessarily reflect prevalent areas of vector mosquito populations. This can result in significant health, economic, and social impacts during disease outbreaks. Of these vector mosquitoes Culex nigripalpus, Culex erraticus, Coquillettidia perturbans, and Aedes vexans are present in Polk County and known to transmit multiple diseases, posing a public health concern. This study seeks to evaluate the effect of Land use Land cover (LULC) unique features and precipitation on spatial and temporal distribution of Cx. nigripalpus, Cx. erraticus, Cq. perturbans, and Ae. vexans in Polk County, Florida, during 2013 and 2014, using negative binomial regression on count data from eight environmentally unique light traps retrieved from Polk County Mosquito Control. The negative binomial regression revealed a statistical association among mosquito species for precipitation and LULC features during the two-year study period, with precipitation proving to be the most significant factor in mosquito count numbers. The findings from this study can aid in more precise targeting of mosquito species, saving time and resources on already stressed public health services.
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Flask, Thomas V. "An Application of Multi-Level Bayesian Negative Binomial Models with Mixed Effects on Motorcycle Crashes in Ohio." University of Akron / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=akron1333046055.
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Dapper, Steffani Nikoli. "ESTUDO DA ASSOCIAÇÃO DOS EFEITOS DA POLUIÇÃO DO AR NA SAÚDE DA POPULAÇÃO DE CANOAS/RS." Universidade Federal de Santa Maria, 2016. http://repositorio.ufsm.br/handle/1/8412.
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Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorAir pollution may be due to various economic activities, as well as natural phenomena. Regardless of the generating factor, it influences the environment and quality of life of human beings. In addition to damage the fauna and flora, air pollution can affect people's health. In Brazil, the researchers are concentrated in the state of São Paulo, with few studies in other regions of the country. This study was realized in the city of Canoas/RS and aimed to analyze the association of pollutants (PM10, O3, CO, SO2) with the number of hospitalizations, in 2014, for respiratory diseases in under 14 and over 60 years. Negative Binomial regression was used due to the presence in over dispersed in the data. The relative risks were estimated (RR) for lags (Lag) up to seven days, and the relative percentage risk (RR%) to the increase of 10 mg/m³ of PM10 and increase of difference interquartile of other pollutants. It was observed that occurred in county of Canoas, 3080 hospitalizations by respiratory diseases, in greater numbers in the elderly, which is the main cause of death in the city. With the results of this study, it was possible to verify the association of PM10 (Lag 0, Lag 1 and Lag 3), O3 (Lag 0) and SO2 (Lag 5) with hospitalizations by respiratory diseases in children and adolescents, and CO (Lag 0, Lag 4, Lag 6 and Lag 7) and O3 (Lag 3), with the number of hospitalizations for respiratory diseases in the elderly. These results confirm strong evidence that air pollution is an important risk factor for the onset and worsening of respiratory problems in county of Canoas, stressing the need for effective action to reduce emissions.
A poluição atmosférica pode ser decorrente de diversas atividades econômicas, como também de fenômenos naturais. Independentemente do fator gerador, ela exerce influência no meio ambiente e na qualidade de vida dos seres humanos. Além de prejudicar a fauna e a flora, a poluição atmosférica é capaz de afetar a saúde das pessoas. No Brasil, as pesquisas analisando os efeitos da poluição do ar na saúde se concentram no estado de São Paulo, sendo poucos os estudos desenvolvidos em outras regiões do país. Esta pesquisa foi realizada no município de Canoas/RS e teve o objetivo de analisar a associação de poluentes (MP10, O3, CO, SO2) com o número de internações, em 2014, por doenças respiratórias em menores de 14 anos e maiores de 60 anos. Foi utilizada a regressão Binomial Negativa devido à presença de sobredispersão nos dados. Foram estimados os riscos relativos (RR) para defasagens (Lag) de até sete dias, bem como o risco relativo percentual (RR%) para o incremento de 10 μg/m³ de PM10 e do incremento da diferença interquartílica dos demais poluentes. Foi observado que ocorreram, no município de Canoas, 3080 internações por doenças respiratórias, em maior número nos idosos, sendo esta a principal causa de óbito na cidade, no período analisado. Com os resultados deste estudo, foi possível verificar a associação do PM10 (Lag 0, Lag 1 e Lag 3), do O3 (Lag 0) e do SO2 (Lag 5) com internações por doenças respiratórias em crianças e adolescentes, e do CO (Lag 0, Lag 4, Lag 6 e Lag 7) e do O3 (Lag 3), com o número de internações por doenças respiratórias em idosos. Tais resultados confirmam fortes indícios de que a poluição do ar é fator de risco importante para o surgimento e agravo de problemas respiratórios no município de Canoas, alertando para a necessidade de ações efetivas para a redução da emissão de poluentes.
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Brundin, Robert, and Alexander Abrahamsen. "Vad påverkar tiden som en mamma ammar? : -en empirisk studie." Thesis, Örebro University, Department of Business, Economics, Statistics and Informatics, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-759.
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Syftet med uppsatsen är att försöka förklara vad det är som påverkar tiden som en mamma ammar. För att undersöka vad det är som påverkar tiden som en mamma ammar, har en Zero inflated negative binomial-modell (ZINB-modell) tagits fram. Resultaten visar att det som avgör hur länge en mamma kommer att amma är: Graviditetens längd, mammans ålder, mammans rökvanor under graviditetens sista månader, mammans rökvanor samt mammans nationella ursprung.
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Winkler, Anderson M. "Widening the applicability of permutation inference." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:ce166876-0aa3-449e-8496-f28bf189960c.
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This thesis is divided into three main parts. In the first, we discuss that, although permutation tests can provide exact control of false positives under the reasonable assumption of exchangeability, there are common examples in which global exchangeability does not hold, such as in experiments with repeated measurements or tests in which subjects are related to each other. To allow permutation inference in such cases, we propose an extension of the well known concept of exchangeability blocks, allowing these to be nested in a hierarchical, multi-level definition. This definition allows permutations that retain the original joint distribution unaltered, thus preserving exchangeability. The null hypothesis is tested using only a subset of all otherwise possible permutations. We do not need to explicitly model the degree of dependence between observations; rather the use of such permutation scheme leaves any dependence intact. The strategy is compatible with heteroscedasticity and can be used with permutations, sign flippings, or both combined. In the second part, we exploit properties of test statistics to obtain accelerations irrespective of generic software or hardware improvements. We compare six different approaches using synthetic and real data, assessing the methods in terms of their error rates, power, agreement with a reference result, and the risk of taking a different decision regarding the rejection of the null hypotheses (known as the resampling risk). In the third part, we investigate and compare the different methods for assessment of cortical volume and area from magnetic resonance images using surface-based methods. Using data from young adults born with very low birth weight and coetaneous controls, we show that instead of volume, the permutation-based non-parametric combination (NPC) of thickness and area is a more sensitive option for studying joint effects on these two quantities, giving equal weight to variation in both, and allowing a better characterisation of biological processes that can affect brain morphology.
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Zavaleta, Katherine Elizabeth Coaguila. "Modelo destrutivo com variável terminal em experimentos quimiopreventivos de tumores em animais." Universidade Federal de São Carlos, 2012. https://repositorio.ufscar.br/handle/ufscar/4561.
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Previous issue date: 2012-04-12Financiadora de Estudos e Projetos
The chemical induction of carcinogens in chemopreventive animal experiments is becoming increasingly frequent in biological research. The purpose of these biological experiments is to evaluate the effect of a particular treatment on the rate of tumors incidence in animals. In this work, the number of promoted tumors per animal will be parametrically modeled following the suggestions given by Kokoska (1987) and Freedman et al. (1993). The study of these chemopreventive experiments will be presented in the context of the destructive model proposed by Rodrigues et al. (2010) with terminal variable that allows or censures the experiment at time of the animal death. Since the data analyzed in this field are subject to excess of zeros (Freedman et al. (1993)), we propose for the number of promoted tumors a negative binomial distribution (NB), a zero-inflated Poisson distribution (ZIP), and a zero-inflated Negative Binomial distribution (ZINB). The selection of these models will be made through the likelihood ratio test and the AIC, BIC criteria. The estimation of its parameters will be obtained by using the method of maximum likelihood, and further simulation studies will also be realized. As a future proposition to finalize this project, it is suggested the Bayesian methodology as an alternative to the method of maximum likelihood via the EM algorithm.
A indução química de substâncias cancerígenas em experimentos quimiopreventivos em animais é cada vez mais frequente em pesquisas biológicas. O objetivo destes experimentos biológicos é avaliar o efeito de um determinado tratamento na taxa de incidência de tumores em animais. Neste trabalho o número de tumores promovidos por animal será modelado parametricamente seguindo as sugestões dadas por Kokoska (1987) e por Freedman et al. (1993). O estudo desses experimentos quimiopreventivos será apresentado no contexto do modelo destrutivo proposto por Rodrigues et al. (2010) com variável terminal que condiciona ou censura o experimento no instante de morte do animal. Os dados analisados possuem uma grande quantidade de zeros, portanto será proposto para o número de tumores promovidos as seguintes distribuições: binomial negativa, a distribuição de Poisson com zeros inflacionados e a distribuição binomial negativa com zeros inflacionados. A seleção destes modelos será feita através do teste da razão de verossimilhança e os critérios AIC, BIC. As estimativas dos respectivos parâmetros serão obtidas utilizando o método de máxima verossimilhança e serão feitos estudos de simulação. Para continuar este projeto, a proposta futura é utilizar a metodologia Bayesiana como alternativa ao método de máxima verossimilhança via algoritmo EM.
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Oliveira, Denise Xavier AraÃjo de. "Judicial activity as an alternative to fight crime: an investigation for municipalities in cearÃ." Universidade Federal do CearÃ, 2013. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=10044.
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Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgicoUsing a recent database on productivity of judges CearÃ, this study follows the proposal of Becker (1968) and proposes a model to investigate the determinants of crime in an empirical exercise for the municipalities of the state of CearÃ. The proposed models confront variables of economic development, agility and efficiency in judicial cases of illicit activity. The approach dealt with criminal activity according to the classification adopted in the Brazilian Penal Code, which is based on the legal injured: the person or property. Robust estimates confirm the beneficial effect of agility and efficiency of the judicial system in reducing criminal behavior, although evidencing a positive relationship between municipal development and torts. Together, this evidence suggests that public managers, besides of making strenuous efforts and resources on the intensification of surveillance and apprehension of criminals, as well as the improvement of social conditions, especially education, yet consider developing public policies that allow optimize investigation and punishment crimes.
Utilizando uma recente base de dados acerca da produtividade dos magistrados cearenses, este estudo segue a proposta de Becker (1968) e propÃe um modelo para investigar os determinantes da criminalidade em um exercÃcio empÃrico para os municÃpios do estado do CearÃ. Os modelos propostos confrontam variÃveis de desenvolvimento econÃmico, agilidade e eficiÃncia judiciÃria com casos de atividade ilÃcita. A abordagem tratou a atividade criminosa segundo a classificaÃÃo adotada no CÃdigo Penal Brasileiro, que se fundamenta no bem jurÃdico lesado: a pessoa ou o patrimÃnio. Estimativas robustas comprovam o efeito benÃfico da eficiÃncia e agilidade do sistema judiciÃrio na reduÃÃo do comportamento criminoso, muito embora evidenciem uma relaÃÃo positiva entre desenvolvimento municipal e atos ilÃcitos. Em conjunto, estas evidÃncias sugerem aos gestores pÃblicos que, alÃm de envidarem recursos e esforÃos na intensificaÃÃo da fiscalizaÃÃo e apreensÃo dos criminosos, bem como na melhoria das condiÃÃes sociais, sobretudo a educaÃÃo, considerem ainda desenvolver polÃticas pÃblicas que permitam otimizar a apuraÃÃo e a puniÃÃo dos crimes.
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Philippsen, Adriana Strieder. "Abordagem clássica e bayesiana para os modelos de séries temporais da família GARMA com aplicações para dados de contagem." Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-06062011-164536/.
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Nesta dissertação estudou-se o modelo GARMA para modelar séries temporais de dados de contagem com as distribuições condicionais de Poisson, binomial e binomial negativa. A principal finalidade foi analisar no contexto clássico e bayesiano, o desempenho e a qualidade do ajuste dos modelos de interesse, bem como o desempenho dos percentis de cobertura dos intervalos de confiança dos parâmetros para os modelos adotados. Para atingir tal finalidade considerou-se a análise dos estimadores pontuais bayesianos e foram analisados intervalos de credibilidade. Neste estudo é proposta uma distribuição a priori conjugada para os parâmetros dos modelos e busca-se a distribuição a posteriori, a qual associada a certas funções de perda permite encontrar estimativas bayesianas para os parâmetros. Na abordagem clássica foram calculados estimadores de máxima verossimilhança, usandose o método de score de Fisher e verificou-se por meio de simulação a consistência dos mesmos. Com os estudos desenvolvidos pode-se observar que, tanto a inferência clássica quanto a inferência bayesiana para os parâmetros dos modelos em questão, apresentou boas propriedades analisadas por meio das propriedades dos estimadores pontuais. A última etapa do trabalho consiste na análise de um conjunto de dados reais, sendo uma série real correspondente ao número de internações por causa da dengue em Campina Grande. Estes resultados mostram que tanto o estudo clássico, quanto o bayesiano, são capazes de descrever bem o comportamento da sérieIn this work, it was studied the GARMA model to model time series count data with Poisson, binomial and negative binomial discrete conditional distributions. The main goal is to analyze, in the bayesian and classic context, the performance and the quality of fit of the corresponding models, as well as the coverage percentages performance to these models. To achieve this purpose we considered the analysis of Bayesian estimators and credible intervals were analyzed. To the Bayesian study it was proposed a priori distribution joined to the models parameters and sought a posteriori distribution, which one associate with to certain loss functions allows finding out Bayesian estimates to the parameters. In the classical approach, it was calculated the maximum likelihood estimators using the method of Fisher scoring, whose interest was to verify, by simulation, the consistence. With the studies developed we can notice that, both classical and inference Bayesian inference for the parameters of those models, presented good properties analysed through the properties of the punctual estimators. The last stage of the work consisted of the analysis of one real data set, being a real serie corresponding to the admission number because of dengue in the city of Campina Grande. These results show that both the classic and the Bayesian studies are able to describe well the behavior of the serie
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Brazzini, Giovanna. "Compliance with EU Law: Why Do Some Member States Infringe EU Law More Than Others?" ScholarWorks@UNO, 2005. http://scholarworks.uno.edu/td/216.
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Why do some member states infringe EU law more than others? Based on the quantitative and qualitative analysis reported here, is not because of administrative capacity limitations, but because of political context, policy changes and deliberate opposition by member governments in order to maintain their independence. States in turn, are motivated by domestic politics to seek to avoid implementing EU law. Additionally, I find that richer countries violate the law more often than poorer countries. Further, member states infringe more than others because of a high number of institutional and coalitional veto players. These results suggest that member states are in the EU because the EU serves their national interest over collective ones. Finally, these results suggest new hypothesis. Member states that have a high level of public discontent with the EU are unlikely to tolerate the political costs of implementing EU legislation.
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SALISBURY, SHEILIA. "The Multivariate Generalized Linear Mixed Model for a Joint Modeling Approach for Analysis of Tumor Multiplicity Data: Development and Comparison of Methods." University of Cincinnati / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1202404654.
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Menton, William. "Continuity of Personality Pathology Constructs in an Inpatient Sample: A Comparison of Linear and Count Regression Analyses Using the PID-5 and MMPI-2-RF." Kent State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=kent1460215992.
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Punase, Shubha. "Utilizing Multiple Data Sources In The Preparation Of A Vision Zero Plan For The City Of Alexandria: Investigating The Relationship Between Transportation Infrastructure, Socio- Economic Characteristics, And Crash Outcomes In The City." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/78329.
Full textAbstract:
“Vision Zero,” first adopted by Sweden in 1997, is a road safety policy that aims to achieve a transportation system having zero fatalities or serious injuries for all modes of transportation. It takes a proactive approach to road safety system by identifying risk and taking steps to prevent injuries. Historically, traffic related crashes have disproportionately impacted vulnerable communities and system users including people of color, low income individuals, seniors, children, and pedestrians, bicyclists, and
transit users (who typically walk to and from public transport). These inequities are addressed in the Vision Zero framework by prioritizing interventions in areas that need safety improvements the most.
In 2016, the Alexandria City Council voted unanimously to develop a “Vision Zero” policy and program as a part of its updated transportation master plan. It required an initial equity analysis to assess the impact of traffic crashes on the traditionally underserved communities / groups (groups from at least one of these categories: low-income; minority; elderly; children; limited English proficiency; persons with disabilities; and/or pedestrians/ bicyclists/ transit users). This study combines three different methods to investigate the equity issues regarding traffic safety: 1) descriptive analysis of the spatial pattern of crashes and their relationship with the demographic profiles of neighborhoods at census block group level (for 2010-2014 period); 2) descriptive analysis of the crash trends in Alexandria; and 3) exploratory regression analyses for two different units of analysis (an aggregate regression analysis of crashes at census block group, and a disaggregate regression analysis of the individual level crash reports of traffic crashes). The analysis found that the elderly, school aged children, rail/subway users, and pedestrians had a higher risk of fatalities and severe injuries in traffic crashes. Higher job densities, alcohol impairment, and speeding were significantly related to higher KSI, whereas, smaller block sizes (higher number of street segments per sq. mile area of census block group), higher housing density, and use of safety equipment were related to lower KSI.Master of Urban and Regional Planning
“Vision Zero,” first adopted by Sweden in 1997, is a road safety policy that aims to achieve a transportation system having zero fatalities or serious injuries for all modes of transportation. It takes a proactive approach to road safety system by identifying risk and taking steps to prevent injuries. Historically, traffic related crashes have disproportionately impacted vulnerable communities and system users including people of color, low income individuals, seniors, children, and pedestrians, bicyclists, and transit users (who typically walk to and from public transport). These inequities are addressed in the Vision Zero framework by prioritizing interventions in areas that need safety improvements the most. In 2016, the Alexandria City Council voted unanimously to develop a “Vision Zero” policy and program as a part of its updated transportation master plan. It required an initial equity analysis to assess the impact of traffic crashes on the traditionally underserved communities / groups (groups from at least one of these categories: low-income; minority; elderly; children; limited English proficiency; persons with disabilities; and/or pedestrians/ bicyclists/ transit users). This study combines three different methods to investigate the equity issues regarding traffic safety: 1) descriptive analysis of the spatial pattern of crashes and their relationship with the demographic profiles of neighborhoods at census block group level (for 2010-2014 period); 2) descriptive analysis of the crash trends in Alexandria; and 3) exploratory regression analyses for two different units of analysis (an aggregate regression analysis of crashes at census block group, and a disaggregate regression analysis of the individual level crash reports of traffic crashes). The analysis found that the elderly, school aged children, rail/subway users, and pedestrians had a higher risk of fatalities and severe injuries in traffic crashes. Higher job densities, alcohol impairment, and speeding were significantly related to higher KSI, whereas, smaller block sizes (higher number of street segments per sq. mile area of census block group), higher housing density, and use of safety equipment were related to lower KSI.
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D'Errico, Christian. "Covid-19 e Inquinamento Atmosferico: Raccolta e Analisi dei Dati con Metodi e Tecnologie di Data Science." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21612/.
Full textAbstract:
L’emergenza sanitaria dovuta alla pandemia di Covid-19 è un evento che ha sconvolto completamente le nostre vite.
Le conseguenze di tutto ciò sono state terribili, sia da un punto di vista sanitario che economico.
L’improvvisa comparsa della malattia nel mondo e la velocità disarmante della sua diffusione hanno spinto i ricercatori ad effettuare analisi e ricercare informazioni cruciali per rallentare la devastazione di questo nemico silenzioso.
Uno dei punti primari della questione su cui gli scienziati di tutto il globo sono stati chiamati a far luce è l’individuazione delle cause e dei fattori concomitanti alla comparsa del nuovo virus, con uno sguardo particolare alle componenti ambientali coinvolte, che potrebbero avere avuto e continuato poi a mantenere un ruolo importante sulla rapidità e la gravità con la quale la
malattia ha colpito gli individui. Questo è l'obiettivo dichiarato di tale elaborato di tesi.
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Helm, Linda S. "Prevention of Non-Biological Male Perpetrated Child Maltreatment: Does a Prevention and Public Awareness Campaign Work?" The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1387564568.
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Johansson, Linus, and Linus Nilsson. "The Impact of a Carbon Dioxide Price on Green Innovation : An Econometric Study Based on Patent Counts." Thesis, Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-79651.
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The aim of this study is to examine the effects of a market-based greenhouse gases price on green innovation by testing the Hicksian theory of induced innovation. To test whether causality exists, panel data compiled of 30 countries over 13 years (2005-2017) have been used. The study is restricted to the European Union emission trading scheme, where the price of EUA has been used as a market-based price for greenhouse gases. To capture the effect on innovation, an approximation for innovation in the form of patent counts have been employed using the patent category Y02 constructed by the EPO. The result suggests that green innovation is affected by the price of the EUA, total CO2 emissions and tax revenue from energy. This study employed a knowledge stock variable that was not found to be significant, contrary to previous literature on induced innovation. The incidence rate ratio associated with the permits price indicates that a one euro increase in price would result in a 1.135 % increase in the patenting of green technology. The result suggests that a higher price in permits would stimulate innovation of green technology within the European Union.
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Gonzalez-Velez, Enrique. "Safety Evaluation of Roadway Lighting Illuminance Levels and its Relationship with Nighttime Crash Injury Severity for West Central Florida Region." Scholar Commons, 2011. http://scholarcommons.usf.edu/etd/3122.
Full textAbstract:
The main role of roadway lighting is to produce quick, accurate and comfortable visibility during nighttime conditions. It is commonly known that good lighting levels enable motorists, pedestrians and bicyclists to obtain necessary visual information in an effective and efficient manner. Many previous studies also proved that roadway lighting minimizes the likelihood of crashes by providing better visibility for roadway users.
Appropriate and adequate roadway lighting illuminance levels for each roadway classification and pedestrian areas are essential to provide safe and comfortable usage. These levels are usually provided by national, or local standards and guidelines. The Florida Department of Transportation (FDOT) Plan Preparation Manual recommends a roadway lighting illuminance level average standard of 1.0 horizontal foot candle (fc) for all the roadway segments used in this research. The FDOT Plan Preparation Manual also states that this value should be considered standard, but should be increased if necessary to maintain an acceptable uniformity illuminance ratio.
This study aimed to find the relationship between nighttime crash injury severity and roadway lighting illuminance. To accomplish this, the research team analyzed crash data and roadway lighting illuminance measured in roadway segments within the West Central Florida Region. An Ordered Probit Model was developed to understand the relationship between roadway lighting illuminance levels and crash injury severity. Additionally, a Negative Binomial Model was used to determine which roadway lighting illuminance levels can be more beneficial in reducing the counts of crashes resulting in injuries.
A comprehensive literature review was conducted using longitudinal studies with and without roadway lighting. Results showed that on the same roadways there was a significant decrease in the number of nighttime crashes with the presence of roadway lighting. In this research, roadway lighting illuminance was measured every 40 feet using an Advanced Lighting Measurement System (ALMS) on a total of 245 centerline miles of roadway segments within the West Central Florida Region. The data were mapped and then analyzed using the existing mile post.
During the process of crash data analysis, it was observed that rear-end collisions were the most common first harmful event observed in all crashes, regardless of the lighting conditions. Meanwhile, the average injury severity for all crashes, was found to be possible injury regardless of the lighting conditions (day, dark, dusk, and dawn).
Finally, this research presented an Ordered Probit Model, developed to understand the existing relationship between roadway lighting illuminance levels and injury severity within the West Central Florida Region. It was observed that having a roadway lighting average moving illuminance range between 0.4 to 0.6 foot candles (fc) was more likely to have a positive effect in reducing the probability of injury severity during a nighttime crash. A Negative Binomial Model was conducted to determine if the roadway lighting average moving illuminance level, found on the Ordered Probit Model was beneficial in reducing crash injury severity during nighttime, would also be beneficial in reducing the counts of crashes resulting in injuries. It was observed that a roadway lighting average moving illuminance, range between 0.4 to 0.6 fc, was more likely to reduce the count of crashes resulting in injuries during nighttime conditions, thus increasing roadway safety. It was also observed that other factors such as pavement condition, site location (intersection or no intersection), number of lanes, and traffic volume can affect the severity and counts of nighttime crashes.
The results of this study suggest that simply adding more roadway lighting does not make the roadway safer. The fact is that a reduction in the amount of roadway lighting illuminance can produce savings in energy consumption and help the environment by reducing light pollution. Moreover, these results show that designing roadway lighting systems go beyond the initial design process, it also requires continuous maintenance. Furthermore, regulations for new developments and the introduction of additional lighting sources near roadway facilities (that are not created with the intent of being used for roadway users) need to be created.
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Pirozhkova, Daria. "Statistical models for an MTPL portfolio." Master's thesis, Vysoká škola ekonomická v Praze, 2017. http://www.nusl.cz/ntk/nusl-359373.
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In this thesis, we consider several statistical techniques applicable to claim frequency models of an MTPL portfolio with a focus on overdispersion. The practical part of the work is focused on the application and comparison of the models on real data represented by an MTPL portfolio. The comparison is presented by the results of goodness-of-fit measures. Furthermore, the predictive power of selected models is tested for the given dataset, using the simulation method. Hence, this thesis provides a combination of the analysis of goodness-of-fit results and the predictive power of the models.
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Guo, Meng. "Benchmark, Explain, and Model Urban Commuting." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1354597241.
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Pookhao, Naruekamol. "Statistical Methods for Functional Metagenomic Analysis Based on Next-Generation Sequencing Data." Diss., The University of Arizona, 2014. http://hdl.handle.net/10150/320986.
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Metagenomics is the study of a collective microbial genetic content recovered directly from natural (e.g., soil, ocean, and freshwater) or host-associated (e.g., human gut, skin, and oral) environmental communities that contain microorganisms, i.e., microbiomes. The rapid technological developments in next generation sequencing (NGS) technologies, enabling to sequence tens or hundreds of millions of short DNA fragments (or reads) in a single run, facilitates the studies of multiple microorganisms lived in environmental communities. Metagenomics, a relatively new but fast growing field, allows us to understand the diversity of microbes, their functions, cooperation, and evolution in a particular ecosystem. Also, it assists us to identify significantly different metabolic potentials in different environments. Particularly, metagenomic analysis on the basis of functional features (e.g., pathways, subsystems, functional roles) enables to contribute the genomic contents of microbes to human health and leads us to understand how the microbes affect human health by analyzing a metagenomic data corresponding to two or multiple populations with different clinical phenotypes (e.g., diseased and healthy, or different treatments). Currently, metagenomic analysis has substantial impact not only on genetic and environmental areas, but also on clinical applications. In our study, we focus on the development of computational and statistical methods for functional metagnomic analysis of sequencing data that is obtained from various environmental microbial samples/communities.
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Faden, Abdulrahman Khalid. "Development of Safety Performance Functions For Two-Lane Rural Highways in the State of Ohio." University of Dayton / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1591976280554876.
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Low, Wan Jing. "Variants of compound models and their application to citation analysis." Thesis, University of Wolverhampton, 2017. http://hdl.handle.net/2436/620467.
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This thesis develops two variant statistical models for count data based upon compound models for contexts when the counts may be viewed as derived from two generations, which may or may not be independent. Unlike standard compound models, the variants model the sum of both generations. We consider cases where both generations are negative binomial or one is Poisson and the other is negative binomial. The first variant, denoted SVA, follows a zero restriction, where a zero in the first generation will automatically be followed by a zero in the second generation. The second variant, denoted SVB, is a convolution model that does not possess this zero restriction. The main properties of the SVA and SVB models are outlined and compared with standard compound models. The results show that the SVA distributions are similar to standard compound distributions for some fixed parameters. Comparisons of SVA, Poisson hurdle, negative binomial hurdle and their zero-inflated counterpart using simulated SVA data indicate that different models can give similar results, as the generating models are not always selected as the best fitting. This thesis focuses on the use of the variant models to model citation counts. We show that the SVA models are more suitable for modelling citation data than other previously used models such as the negative binomial model. Moreover, the application of SVA and SVB models may be used to describe the citation process. This thesis also explores model selection techniques based on log-likelihood methods, Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The suitability of the models is also assessed using two diagrammatic methods, randomised quantile residual plots and Christmas tree plots. The Christmas tree plots clearly illustrate whether the observed data are within fluctuation bounds under the fitted model, but the randomised quantile residual plots utilise the cumulative distribution, and hence are insensitive to individual data values. Both plots show the presence of citation counts that are larger than expected under the fitted model in the data sets.
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Rusch, Thomas, Paul Hofmarcher, Reinhold Hatzinger, and Kurt Hornik. "Modeling Mortality Rates In The WikiLeaks Afghanistan War Logs." WU Vienna University of Economics and Business, 2011. http://epub.wu.ac.at/3210/1/Report112.pdf.
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The WikiLeaks Afghanistan war logs contain more than 76 000 reports about fatalities and their circumstances in the US led Afghanistan war, covering the period from January 2004 to December 2009. In this paper we use those reports to build statistical models to help us understand the mortality rates associated with specific circumstances. We choose an approach that combines Latent Dirichlet Allocation (LDA) with negative binomial based recursive partitioning. LDA is used to process the natural language information contained in each report summary. We estimate latent topics and assign each report to one of them. These topics - in addition to other variables in the data set - subsequently serve as explanatory variables for modeling the number of fatalities of the civilian population, ISAF Forces, Anti-Coalition Forces and the Afghan National Police or military as well as the combined number of fatalities. Modeling is carried out with manifest mixtures of negative binomial distributions estimated with model-based recursive partitioning. For each group of fatalities, we identify segments with different mortality rates that correspond to a small number of topics and other explanatory variables as well as their interactions. Furthermore, we carve out the similarities between segments and connect them to stories that have been covered in the media. This provides an unprecedented description of the war in Afghanistan covered by the war logs. Additionally, our approach can serve as an example as to how modern statistical methods may lead to extra insight if applied to problems of data journalism. (author's abstract)Series: Research Report Series / Department of Statistics and Mathematics
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Saha, Dibakar. "Improved Criteria for Estimating Calibration Factors for Highway Safety Manual (HSM) Applications." FIU Digital Commons, 2014. http://digitalcommons.fiu.edu/etd/1701.
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The Highway Safety Manual (HSM) estimates roadway safety performance based on predictive models that were calibrated using national data. Calibration factors are then used to adjust these predictive models to local conditions for local applications. The HSM recommends that local calibration factors be estimated using 30 to 50 randomly selected sites that experienced at least a total of 100 crashes per year. It also recommends that the factors be updated every two to three years, preferably on an annual basis. However, these recommendations are primarily based on expert opinions rather than data-driven research findings. Furthermore, most agencies do not have data for many of the input variables recommended in the HSM. This dissertation is aimed at determining the best way to meet three major data needs affecting the estimation of calibration factors: (1) the required minimum sample sizes for different roadway facilities, (2) the required frequency for calibration factor updates, and (3) the influential variables affecting calibration factors.
In this dissertation, statewide segment and intersection data were first collected for most of the HSM recommended calibration variables using a Google Maps application. In addition, eight years (2005-2012) of traffic and crash data were retrieved from existing databases from the Florida Department of Transportation. With these data, the effect of sample size criterion on calibration factor estimates was first studied using a sensitivity analysis. The results showed that the minimum sample sizes not only vary across different roadway facilities, but they are also significantly higher than those recommended in the HSM. In addition, results from paired sample t-tests showed that calibration factors in Florida need to be updated annually.
To identify influential variables affecting the calibration factors for roadway segments, the variables were prioritized by combining the results from three different methods: negative binomial regression, random forests, and boosted regression trees. Only a few variables were found to explain most of the variation in the crash data. Traffic volume was consistently found to be the most influential. In addition, roadside object density, major and minor commercial driveway densities, and minor residential driveway density were also identified as influential variables.
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Krisztin, Tamás, and Manfred M. Fischer. "The gravity model for international trade: Specification and estimation issues in the prevalence of zero flows." WU Vienna University of Economics and Business, 2014. http://epub.wu.ac.at/4453/3/TheGravityModelForInternationalTrade2.pdf.
Full textAbstract:
The gravity model for international trade is one of the most
successful empirical models in trade literature. There is a long tradition to log-linearise the multiplicative model and to estimate the parameters of interest by least squares. But this practice is inappropriate for several reasons. First of all, bilateral trade flows are frequently zero and disregarding countries that do not trade with each other produces biased results. Second, log-linearisation in the presence of heteroscedasticity leads to inconsistent estimates in general.
In recent years, the Poisson gravity model along with pseudo maximum likelihood estimation methods have become popular as a way of dealing with such econometric issues as arise when dealing with origin-destination
flows. But the standard Poisson model specification
is vulnerable to problems of overdispersion and excess zero
flows. To overcome these problems, this paper presents zero-inflated extensions of the Poisson and negative binomial specifications as viable alternatives to both the log-linear and the standard Poisson specifications of
the gravity model. The performance of the alternative model specifications is assessed on a real world example, where more than half of country-level trade flows are zero. (authors' abstract)Series: Working Papers in Regional Science