Relevant bibliographies by topics / Binary logit

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Binary logit'

Author: Grafiati
Published: 4 June 2021
Last updated: 14 February 2022

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Journal articles on the topic "Binary logit"

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LIPOVETSKY, STAN. "CONDITIONAL AND MULTINOMIAL LOGITS AS BINARY LOGIT REGRESSIONS." Advances in Adaptive Data Analysis 03, no. 03 (July 2011): 309–24. http://dx.doi.org/10.1142/s1793536911000738.

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For a categorical variable with several outcomes, its dependence on the predictors is usually considered in the conditional or multinomial logit models. This work considers elasticity features of the binary and categorical logits and introduces the coefficients individual by observations. The paper shows that by a special rearrangement of data the more complicated conditional and multinomial models can be reduced to binary logistic regression. It suggests the usage of any software widely available for logit modeling to facilitate constructing for complex conditional and multinomial regressions. In addition, for binary logit, it is possible to obtain meaningful coefficients of regression by transforming data to the linear link function, which opens a possibility to obtain meaningful parameters of the complicated models with categorical dependent variables.
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Shekhar, Suraj Kushe, Rehin K. R. Rehin K.R, and Dr P. T. Raveendran Dr. P.T Raveendran. "Demographic Variables & Nutritional Risk: The Predictive Power Using Binary Logit Model." Indian Journal of Applied Research 3, no. 11 (October 1, 2011): 278–80. http://dx.doi.org/10.15373/2249555x/nov2013/91.

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Purhadi, Purhadi, and M. Fathurahman. "A Logit Model for Bivariate Binary Responses." Symmetry 13, no. 2 (February 16, 2021): 326. http://dx.doi.org/10.3390/sym13020326.

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This article provides a bivariate binary logit model and statistical inference procedures for parameter estimation and hypothesis testing. The bivariate binary logit (BBL) model is an extension of the binary logit model that has two correlated binary responses. The BBL model responses were formed using a 2 × 2 contingency table, which follows a multinomial distribution. The maximum likelihood and Berndt–Hall–Hall–Hausman (BHHH) methods were used to obtain the BBL model. Hypothesis testing of the BBL model contains the simultaneous test and the partial test. The test statistics of the simultaneous test and the partial test were determined using the maximum likelihood ratio test method. The likelihood ratio statistics of the simultaneous test and the partial test were approximately asymptotically chi-square distributed with 3p degrees of freedom. The BBL model was applied to a real dataset, and the BBL model with the single covariate was better than the BBL model with multiple covariates.
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Moon, C. G. "Simulataneous specicication test in a binary logit." Communications in Statistics - Theory and Methods 17, no. 10 (January 1988): 3361–87. http://dx.doi.org/10.1080/03610928808829809.

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Sarkar, S. K., Habshah Midi, and Sohel Rana. "Adequacy of Multinomial Logit Model with Nominal Responses over Binary Logit Model." Trends in Applied Sciences Research 6, no. 8 (August 1, 2011): 900–909. http://dx.doi.org/10.3923/tasr.2011.900.909.

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Horowitz, Joel L., and N. E. Savin. "Binary Response Models: Logits, Probits and Semiparametrics." Journal of Economic Perspectives 15, no. 4 (November 1, 2001): 43–56. http://dx.doi.org/10.1257/jep.15.4.43.

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A binary-response model is a mean-regression model in which the dependent variable takes only the values zero and one. This paper describes and illustrates the estimation of logit and probit binary-response models. The linear probability model is also discussed. Reasons for not using this model in applied research are explained and illustrated with data. Semiparametric and nonparametric models are also described. In contrast to logit and probit models, semi- and nonparametric models avoid the restrictive and unrealistic assumption that the analyst knows the functional form of the relation between the dependent variable and the explanatory variables.
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Rungie, Cam, and Gilles Laurent. "Repeated Binary Logit: Analysing Variation in Behavioural Loyalty." Australasian Marketing Journal (AMJ) 13, no. 2 (January 2005): 27–36. http://dx.doi.org/10.1016/s1441-3582(05)70075-6.

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Magnac, Thierry. "Panel Binary Variables and Sufficiency: Generalizing Conditional Logit." Econometrica 72, no. 6 (November 2004): 1859–76. http://dx.doi.org/10.1111/j.1468-0262.2004.00556.x.

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Gunby, Molly, and Ivan Damnjanovic. "Identifying Project Value Interests: A Binary Logit Model." International Journal of Architecture, Engineering and Construction 1, no. 3 (September 2012): 121–33. http://dx.doi.org/10.7492/ijaec.2012.014.

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Nugraha, Ryan Septiady. "Commuter Train Mode Choice Modelling Using Binary Logit Model." WIDYAKALA JOURNAL 6, no. 1 (February 22, 2019): 1. http://dx.doi.org/10.36262/widyakala.v6i1.137.

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Car production in Malaysia increasing dramatically. This situation created serious impact such as pollution and congestion. The Malaysian government should find a proper solution to prevent the vehicles growth by controlling them and improve public transportation services. The only way to get people to switch to public transportation is by improving the public transport system becomes more efficient. To find out the solution, an understanding of traveler behavior by applying to mode choice model using binary logit approach is necessary. Stated preferences method was adopted in order to construct hypothetical choice in current and future situations. A total of 250 respondents were selected as the sample based on the research study. This research employed a discrete choice analysis to examine the relationship between the independent variables (travel time, fares, comfort and safety). With variation of trip purpose (school, work, leisure activity, and shopping), model has been developed and tested to check the validity. The result shows that the potential of new train services to compete with the current commuter (KTM) and private car user are quite competitive. This is no doubt due to the characteristics of the respondent to choose a good level of services especially a better comfortability and safety with an affordable price (fares). It can be concluded that scenario 2 has great potential to be implemented since forecasting demand reached above 90%.
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Dissertations / Theses on the topic "Binary logit"

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Mannila, Kranthi Kiran. "ANALYSIS OF VARIOUS CAR-TRUCK CRASH TYPES BASED ON GES AND FARS CRASH DATABASES USING MUTLINOMIAL AND BINARY LOGIT MODEL." Master's thesis, University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2583.

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Each year about 400,000 trucks are involved in motor vehicle crashes. Crashes involving a car and truck have always been a major concern due to the heavy fatality rates. These types of crashes result in about 60 percent of all fatal truck crashes and two-thirds of all police-reportable truck crashes. Car-truck crashes need to be analyzed further to study the trends for a car-truck crash and develop some countermeasures to lower these crashes. Various types of car-truck crashes are analyzed in this study and the effects of various roadway/environment factors and variables related to driver characteristics in these car-truck crashes are investigated. To examine the crash characteristics and to investigate the significant factors related to a car-truck crash, this study analyzed five years of data (2000-2004) of the General estimates system of National Sampling System (GES) and the Fatality Analysis Reporting system database (FARS). All two vehicle crashes including either a car or truck (truck-truck cases excluded because of their low percentage composition) were obtained from these databases. Based on the five year data (GES/FARS) the percentage of car-truck angle collisions constituted the highest percent of frequency of all types of car-truck collisions. Furthermore, based on the 2004 GES data there is a clear trend that the frequency of angle collision increases with the increase in driver injury severity. When analyzing the GES data it was observed that the percentage of angle collisions was the highest followed by the rear end and sideswipe (same direction) collisions respectively. When the fatalities were considered (FARS database used), the percentage of angle collisions was the highest followed by head-on and rear-end collisions. The nominal multinomial logit model and logistic regression models were utilized for this analysis. Divided section, alcohol involvement, adverse weather conditions, dark lighting condition and old age of drivers had a significant effect on the car-truck crashes and were likely to increase the likelihood of a car-truck crash. Whereas dark but light conditions, young aged drivers showed a less likelihood of involving in a car-truck crash. This research is significant in providing an insight into various car-truck crash types and provides with results, which have impacted the car-truck crashes. A better understanding of the factors impacting these crashes will help in providing better countermeasures, which would result in reducing the car-truck crashes.
M.S.
Department of Civil and Environmental Engineering
Engineering and Computer Science
Civil Engineering
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Nti, Frank Kyekyeku. "Climate change vulnerability and coping mechanisms among farming communities in Northern Ghana." Thesis, Kansas State University, 2012. http://hdl.handle.net/2097/15116.

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Master of Science
Department of Agricultural Economics
Andrew Barkley
This study examines the effect of extreme climatic conditions (drought, flood, and bushfires) on the livelihood of households in the Bawku West district of Ghana. The research identified the mechanisms with which households cope in such situations, and analyzed factors influencing the adoption of coping strategies for flood, coping strategies for drought, and coping strategies for bushfires. Data for the study were collected in selected villages across the district in the aftermath of the 2007/2008 extreme climatic events (a prolonged drought period followed by an erratic rainfall). A binary logit regression (BLR) model was then specified to estimate factors that influence the adoption of a given coping mechanisms. Results from the BLR model indicate that literacy level, membership with an FBO, household income, and location of households had positive and significant impacts on adaptation to drought. Similarly, source of seeds for planting, membership with an FBO, household income, and farm size had positive significant influence on adaptation to flood. Adaption to bushfire was positively influenced by radio ownership, seed source and income. The main effect of these climatic extreme events on households included destruction of crops, livestock and buildings; food and water shortage; poor yield or harvest and limited fields for livestock grazing. Therefore, government policies should be geared towards creating revenue generating channels and in strengthening institutions that provide access to farm credit, readily available improve seeds and extension. Additionally, policies that expedite information dissemination through radio and other public media will enhance households’ adaptive capacity.
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Kotikalapudi, Siddhartha. "Characteristics and contributory causes related to large truck crashes (phase-II) - all crashes." Thesis, Kansas State University, 2012. http://hdl.handle.net/2097/14027.

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Master of Science
Department of Civil Engineering
Sunanda Dissanayake
In order to improve safety of the overall surface transportation system, each of the critical areas needs to be addressed separately with more focused attention. Statistics clearly show that large-truck crashes contribute significantly to an increased percentage of high-severity crashes. It is therefore important for the highway safety community to identify characteristics and contributory causes related to large-truck crashes. During the first phase of this study, fatal crash data from the Fatality Analysis Reporting System (FARS) database were studied to achieve that objective. In this second phase, truck-crashes of all severity levels were analyzed with the intention of understanding characteristics and contributory causes, and identifying factors contributing to increased severity of truck-crashes, which could not be achieved by analyzing fatal crashes alone. Various statistical methodologies such as cross-classification analysis and severity models were developed using Kansas crash data. Various driver-, road-, environment- and vehicle- related characteristics were identified and contributory causes were analyzed. From the cross-classification analysis, severity of truck-crashes was found to be related with variables such as road surface (type, character and condition), accident class, collision type, driver- and environment-related contributory causes, traffic-control type, truck-maneuver, crash location, speed limit, light and weather conditions, time of day, functional class, lane class, and Average Annual Daily Traffic (AADT). Other variables such as age of truck driver, day of the week, gender of truck-driver, pedestrian- and truck-related contributory causes were found to have no relationship with crash severity of large trucks. Furthermore, driver-related contributory causes were found to be more common than any other type of contributory cause for the occurrence of truck-crashes. Failing to give time and attention, being too fast for existing conditions, and failing to yield right of way were the most dominant truck-driver-related contributory causes, among many others. Through the severity modeling, factors such as truck-driver-related contributory cause, accident class, manner of collision, truck-driver under the influence of alcohol, truck maneuver, traffic control device, surface condition, truck-driver being too fast for existing conditions, truck-driver being trapped, damage to the truck, light conditions, etc. were found to be significantly related with increased severity of truck-crashes. Truck-driver being trapped had the highest odds of contributing to a more severe crash with a value of 82.81 followed by the collision resulting in damage to the truck, which had 3.05 times higher odds of increasing the severity of truck-crashes. Truck-driver under the influence of alcohol had 2.66 times higher odds of contributing to a more severe crash. Besides traditional practices like providing adequate traffic signs, ensuring proper lane markings, provision of rumble strips and elevated medians, use of technology to develop and implement intelligent countermeasures were recommended. These include Automated Truck Rollover Warning System to mitigate truck-crashes involving rollovers, Lane Drift Warning Systems (LDWS) to prevent run-off-road collisions, Speed Limiters (SLs) to control the speed of the truck, connecting vehicle technologies like Vehicle-to-Vehicle (V2V) integration system to prevent head-on collisions etc., among many others. Proper development and implementation of these countermeasures in a cost effective manner will help mitigate the number and severity of truck-crashes, thereby improving the overall safety of the transportation system.
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Saúde, Arthur Moreira. "Metodologia de previsão de recessões: um estudo econométrico com aplicações de modelos de resposta binária." reponame:Repositório Institucional do FGV, 2017. http://hdl.handle.net/10438/18221.

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This paper aims to create an econometric model capable of anticipating recessions in the United States economy, one year in advance, using not only monetary market variables that are already used by economists, but also capital market variables. Using a data span from 1959 to 2016, it was observed that the yield spread continues to be an explanatory variable with excellent predictive power over recessions. Evidence has also emerged of new variables that have very high statistical significance, and which offer valuable contributions to the regressions. Out-of-sample tests have been conducted which suggest that past recessions would have been predicted with substantially higher accuracy if the proposed Probit model had been used instead of the most widespread model in the economic literature. This accuracy is evident not only in the predictive quality, but also in the reduction of the number of false positives and false negatives in the regression, and in the robustness of the out-of-sample tests.
Este trabalho visa desenvolver um modelo econométrico capaz de antecipar, com um ano de antecedência, recessões na economia dos Estados Unidos, utilizando não só variáveis dos mercados monetários, que já são indicadores antecedentes bastante utilizados por economistas, mas também dos mercados de capitais. Utilizando-se dados de 1959 a 2016, pode-se observar que o spread de juros de longo e curto prazo continua sendo uma variável explicativa com excelente poder preditivo sobre recessões. Também surgiram evidências de novas variáveis que possuem altíssimas significâncias estatísticas, e que oferecem valiosas contribuições para as regressões. Foram conduzidos testes fora da amostra que sugerem que as recessões passadas teriam sido previstas com acurácia substancialmente superior, caso o modelo Probit proposto tivesse sido utilizado no lugar do modelo mais difundido na literatura econômica. Essa acurácia é evidente não só na qualidade preditiva, mas também na redução do número de falsos positivos e falsos negativos da regressão, e na robustez dos testes fora da amostra.
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Rönchen, Philipp. "Constraints of Binary Simple Homogeneous Structures." Thesis, Uppsala universitet, Algebra och geometri, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-361217.

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Flick, Jason. "Evaluating the Impact of OOCEA's Dynamic Message Signs (DMS) on Travelers' Experience Using a Pre and Post-Deployment Survey." Master's thesis, University of Central Florida, 2008. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3030.

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The purpose of this thesis was to evaluate the impact of dynamic message signs (DMS) on the Orlando-Orange County Expressway Authority (OOCEA) toll road network using a Pre and Post-Deployment DMS Survey (henceforth referred to as "pre and post-deployment survey") analysis. DMS are electronic traffic signs used on roadways to give travelers information about travel times, traffic congestion, accidents, disabled vehicles, AMBER alerts, and special events. The particular DMS referred to in this study are large rectangular signs installed over the travel lanes and these are not the portable trailer mount signs. The OOCEA have been working over the past two years to add several fixed DMS on their toll road network. At the time of the pre-deployment survey, only one DMS was installed on the OOCEA toll road network. At the time of the post-deployment survey, a total of 30 DMS were up and running on the OOCEA toll road network. Since most of the travelers on the OOCEA toll roads are from Orange, Osceola, and Seminole counties, this study was limited to these counties. This thesis documents the results and comparisons between the pre and post-deployment survey analysis. The instrument used to analyze the travelers' perception of DMS was a survey that utilized computer aided telephone interviews. The pre-deployment survey was conducted during early November of 2006, and the post-deployment survey was conducted during the month of May, 2008. Questions pertaining to the acknowledgement of DMS on the OOCEA toll roads, satisfaction with travel information provided on the network, formatting of the messages, satisfaction with different types of messages, diversion questions (Revealed and Stated preferences), and classification/socioeconomic questions (such as age, education, most traveled toll road, county of residence, and length of residency) were asked to the respondents. The results of both the pre and post-deployment surveys are discussed in this thesis, but it should be noted that the more telling results are those of the post-deployment survey. The results of the post-deployment survey show the complete picture of the impact of DMS on travelers' experience on the OOCEA toll road network. The pre-deployment results are included to show an increase or decrease in certain aspects of travel experience with relation to DMS. The results of the pre-deployment analysis showed that 54.4% of the OOCEA travelers recalled seeing DMS on the network, while a total of 63.93% of the OOCEA travelers recalled seeing DMS during the post-deployment analysis. This showed an increase of almost 10% between the two surveys demonstrating the people are becoming more aware of DMS on the OOCEA toll road network. The respondents commonly agreed that the DMS were helpful for providing information about hazardous conditions, and that the DMS are easy to read. Also, upon further research it was found that between the pre and post-deployment surveys the travelers' satisfaction with special event information provided on DMS and travel time accuracy on DMS increased significantly. With respect to formatting of the DMS, the following methods were preferred by the majority of respondents in both the pre and post-deployment surveys: • Steady Message as a default DMS message format • Flashing Message for abnormal traffic information (94% of respondents would like to be notified of abnormal traffic information) • State road number to show which roadway (for Colonial – SR 50, Semoran – SR 436 and Alafaya – SR 434) • "I-Drive" is a good abbreviation for International Drive • If the distance to the international airport is shown on a DMS it thought to be the distance to the airport exit The results from the binary logit model for "satisfaction with travel information provided on OOCEA toll road network" displayed the significant variables that explained the likelihood of the traveler being satisfied. This satisfaction model was based on respondents who showed a prior knowledge of DMS on OOCEA toll roads. With the use of a pooled model (satisfaction model with a total of 1775 responses – 816 from pre-deployment and 959 from post-deployment), it was shown that there was no statistical change between the pre and post-deployment satisfaction based on variables thought to be theoretically relevant. The results from the comparison between the pre and post-deployment satisfaction models showed that many of the coefficients of the variables showed a significant change. Although some of the variables were statistically insignificant in one of the two survey model results: Either the pre or post-deployment model, it was still shown that every variable was significant in at least one of the two models. The coefficient for the variable corresponding to DMS accuracy showed a significantly lower value in the post-deployment model. The coefficient for the variable "DMS was helpful for providing special event information" showed a significantly higher value in the post-deployment model. The final post-deployment diversion model was based on a total of 732 responses who answered that they had experienced congestion in the past 6 months. Based on this final post-deployment diversion model, travelers who had stated that their most frequently traveled toll road was either SR 408 or SR 417 were more likely to divert. Also, travelers who stated that they would divert in the case of abnormal travel times displayed on DMS or stated that a DMS influenced their response to congestion showed a higher likelihood of diversion. These two variables were added between the pre and post-deployment surveys. It is also beneficial to note that travelers who stated they would divert in a fictitious congestion situation of at least 30 minutes of delay were more likely to divert. This shows that they do not contradict themselves in their responses to Revealed Preference and Stated Preference diversion situations. Based on a comparison between pre and post-deployment models containing similar variables, commuters were more likely to stay on the toll road everything else being equal to the base case. Also, it was shown that in the post-deployment model the respondents traveling on SR 408 and SR 417 were more likely to divert, but in the pre-deployment model only the respondents traveling on SR 408 were more likely to divert. This is an expected result since during the pre-deployment survey only one DMS was located on SR 408, and during the post-deployment survey there were DMS located on all toll roads. Also, an interesting result to be noted is that in the post-deployment survey, commuters who paid tolls with E-pass were more likely to stay on the toll road than commuters who paid tolls with cash. The implications for implementation of these results are discussed in this thesis. DMS should be formatted as a flashing message for abnormal traffic situations and the state road number should be used to identify a roadway. DMS messages should pertain to information on roadway hazards when necessary because it was found that travelers find it important to be informed on events that are related to their personal safety. The travel time accuracy on DMS was shown to be significant for traveler information satisfaction because if the travelers observe inaccurate travel times on DMS, they may not trust the validity of future messages. Finally, it is important to meet the travelers' preferences and concerns for DMS.
M.S.C.E.
Department of Civil and Environmental Engineering
Engineering and Computer Science
Civil Engineering MS
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Pérez, Manríquez Alejandra. "Quivers for semigroup algebras of binary relations of small rank." Thesis, Uppsala universitet, Algebra och geometri, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-411481.

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Buonocore, Chiara. "Development of a model to choose the path of cyclists using GPS data collected via smartphone." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/17199/.

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Nowadays it is impossible being indifferent to the improvement of the urbanization and the mobility and sustainable road infrastructures.It has to be taken into account the bike as a mode of transport for many reasons such as:reduction of pollution and the emissions,safety on the road,less space and healthy.Mostly in big cities,perhaps it is the fastest mode of transport because it's not subject to traffic and its bottlenecks that block the flow.The Netherlands is the most interested country to travel by bike.It's the place where there are more bikes than cars.In recent years the availability of GPS data has seen a marked improvement in terms of accuracy,continuity and quality of data,thanks to the spread of smartphones and applications for auto-location and navigation.The main advantage is to obtain information on the travel routes actually followed by a large sample of cyclists on the entire network, from their origin to their destination.When GPS tracks can be attributed to detailed transport networks, it is possible to evaluate the factors that users consider in the process of choosing a specific route.It's important to study the choice of the route that cyclists make for many reasons.The objective of this thesis is to examine the aspects that the cyclists taking into account when they choose a route instead of another one.We want to focus on the time travelled,considering the average speed per each link and its correspondent length,and the average waiting times at the intersections:how the time influences cyclists choice. This research will investigate which aspects of the bicycle infrastructures have greater or lesser repercussions on the path made by the cyclists and to model their route choices.It will explore the link between the routes chosen by the cyclists and some attributes of the transport network of the Netherlands.The chosen routes will be compare with the fastest and the shortest calculated thanks to the network analyst in ArcMap for each OD pair.
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Mendonça, Danilo Marques de. "Perfil das famílias tomadoras de crédito no Brasil: caracterização a partir de um modelo desenvolvido com microdados da POF 2008/09." Pontifícia Universidade Católica de São Paulo, 2014. https://tede2.pucsp.br/handle/handle/9236.

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After the period of monetary stabilization started with the Real Plan in 1994 , the credit market has shown annual growth rates of 20 %. About 40 % of this growth came from the credit market for individuals . This paper analyzed the profile of the families who have credit expenses, and what changes in their characteristics can cause any effect in their propensity to take credit . For this purpose we applied binary logit choice model based on microdata from the Household Budget Survey (POF 2008 / 09 ) of the IBGE, in an attempt to measure the probability of the family take a loan. For this, we used categorical variables relating to the constitution of families, such as education level, sex, race and age of household head, and other information on the composition of household expenditures found in POF. The data suggest that the two most important factors to increase the likelihood of family borrowing is the age of the household head and income per capita. However other factors also contribute significantly, such as the existence of financial investment spending , expend with reform the household or even health spending, children's age, sex, race and education of household head
Após o período de estabilização monetária iniciado com o Plano Real em 1994, o mercado de crédito brasileiro vem apresentando taxas de crescimento anuais nominais acima de 20%. Cerca de 40% deste crescimento advêm do mercado de crédito direcionado às pessoas físicas. Neste trabalho é analisado o perfil das famílias que possuem despesas com crédito, e quais mudanças em suas características podem causar alterações em sua propensão a tomar crédito. Para tal objetivo foi aplicado o modelo de escolha binária logit à base dos microdados da Pesquisa de Orçamento Familiar (POF 2008/09) do IBGE, na tentativa de mensurar a probabilidade da família ser tomadora de crédito. Para tanto, são usadas variáveis categóricas referentes à constituição das famílias, como: grau de escolaridade, sexo, raça e idade do chefe da família, além de outras informações sobre a composição das despesas familiares encontradas na POF. Os dados sugerem que os fatores mais relevantes a aumentar a probabilidade da família tomar empréstimos são a idade do chefe da família e a renda per capita. No entanto outros fatores também contribuem significativamente, tais como a existência de gastos com aplicação financeira, gastos com reforma do domicílio ou mesmo com saúde emergencial, idade dos filhos, sexo, raça e educação do chefe da família
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Cazor, Laurent. "How to make the most of open data? A travel demand and supply model for regional bicycle paths." Thesis, KTH, Transport och systemanalys, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-296219.

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Detta examensarbete syftar till att svara på ett av Trafikverket fastställt problem: en gemensam regional cykelplanerings process skulle göra dem billigare och mer jämförbara. De erbjuder för närvarande planerarna en modell som utvecklades av Kågeson 2007. Denna modell har formen av en rapport som ger råd om när man ska bygga en cykelväg mellan städer eller platser i en region. Ändå används den bara i endast 6 av de 21 svenska länen. Trafikverket kräver ett nytt planeringsstödverktyg, mer interaktivt och komplett än Kågeson-modellen. Några nya önskade funktioner är separationen av efterfrågan per syfte, införandet av e-cyklar, olika resesyfte och en prioritering av investeringarna.  Examensarbetet är att designa och implementera det här verktyget, även kallat Planning Support System (PSS), som syftar till att jämföra utbud och efterfrågan på cykelväg till prioritering av infrastrukturförbättringar. En huvudbegränsning för modellen är att den måste vara billig datavis, men så komplett och exakt som möjligt. Det baseras på flera öppna dataleverantörer, till exempel OpenStreetMap, den svenska nationella vägdatabasen (NVDB) eller reseundersökningar från Sverige och Nederländerna. Resultatet är en modell, uppdelad efter turändamål och typ av cykel.  Del för efterfrågeuppskattning anpassar en klassisk fyrsteg transportmodell till cykelplanering och begränsad data. För olika resändamål genereras och distribueras resor tack vare en ursprungs begränsad gravitationsmodell. Valet av cykelläge är anpassat till det faktiska resebeteendet genom logistisk regression med en binär logit-modell. Resorna tilldelas sedan nätverket med tilldelnings metoden "allt-eller-ingenting" genom Dijkstras algoritm. För att utvärdera cykelförsörjningen använde vi ett mått som heter Level of Traffic Stress (LTS), som uppskattar den potentiella användningen av en nätverkslänk för olika delar av befolkningen som en funktion av vägnätvariablerna. Prioriteringsrankningen är då förhållandet mellan mått på efterfrågan och utbud.  Detta nya verktyg implementeras med opensource Geographic Information System (GIS) som heter QGIS och med Python 3 och testas i Södermanlands län
This Master Thesis main objective is to answer a problem set by the Swedish Transport Administration: a common regional bicycle planning process would them cheaper and more comparable. They currently offer the planners a model developed by Kågeson in 2007. This model takes the form of a report which advises on when to build a bicycle path between cities or places of a region. Still, it is only used in only 6 of the 21 Swedish counties. Trafikverket requires a new planning support tool, more interactive and complete than the Kågeson model. Some new desired features are the separation of demand per purpose, the inclusion of e-bikes, different trip purposes, and a prioritization of the investments.  The Degree Project work is to design and implement this tool, also called Planning Support System (PSS), which compares supply and demand for bicycle path to prioritizing infrastructure improvements. A main constraint for the model is that it needs to be cheap data-wise, but as complete and precise as possible. It bases on several open data providers, such as OpenStreetMap, the Swedish National Road Database (NVDB), or Travel Surveys from Sweden and the Netherlands. The result is a model, disaggregated by trip purpose and type of bicycle.  The demand estimation part adapts a classic four-step transportation model to bicycle planning and limited data. For different trip purposes, trips are generated and distributed thanks to an origin-constrained gravity model. Bicycle mode choice is fit to actual travel behaviour through logistic regression with a binary logit model. The trips are then assigned to the network using the "all-or-nothing" assignment method through the Dijkstra algorithm. To evaluate bicycle supply, we used a metric called Level of Traffic Stress (LTS), which estimates the potential use of a network link by different parts of the population as a function of the road network variables. The prioritization ranking is then the ratio between demand and supply metrics.  This new tool is implemented with the opensource Geographic Information System (GIS) called QGIS and with Python 3, and it is tested on Södermanland County.
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Books on the topic "Binary logit"

1

Law, Vincent Hin-Wei. Quasi-static energy recovery binary decision diagram logic (QSBDDL). Ottawa: National Library of Canada, 2003.

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Drechsler, Rolf. Binary decision diagrams: Theory and implementation. Boston: Kluwer Academic Publishers, 1998.

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Majerski, Stanisław. Economical and optimal carry-lookahead (CLA) units for high-speed binary adders. Warsaw: Institute of Computer Science, Polish Academy of Sciences, 1988.

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Jamīl, T̤āriq. Complex Binary Number System: Algorithms and Circuits. India: Springer India, 2013.

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(Micheline), Cosinschi-Meunier M., ed. Essai de logique ternaire sémiotique et philosophique. Bern: Peter Lang, 2009.

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Zimmermann, Reto. Binary adder architectures for cell-based VLSI and their synthesis. Konstanz: Hartung-Gorre, 1998.

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Akihiro, Nozaki. Anno's hat tricks. New York: Philomel Books, 1985.

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Akihiro, Nozaki. Anno's hat tricks. New York: Philomel Books, 1985.

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Folawewo, Abiodun O., and Olusegun A. Orija. Informal–formal workers' transition in Nigeria: A livelihood analysis. UNU-WIDER, 2020. http://dx.doi.org/10.35188/unu-wider/2020/903-7.

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This study evaluates the effects of the informal sector on Nigerian workers’ livelihoods and analyses workers’ transitions within the informal sector and between informal and formal employment. A binary logit model is applied to General Household Survey panel data for the periods 2010/11, 2012/13, and 2015/16. We find that informal employment has the greatest impact on workers’ livelihoods in terms of earnings. Results also indicate the existence of a high level of dynamic transition of workers within different types of informal employment. Our results further indicate that both self-employed and wage employed informal workers are likely to transit to formal employment, the likelihood being higher for the upper-tier informal wage employed. While informally employed workers have a very high chance of transiting to formal employment, formal workers have a much lower chance of transiting to informal employment. The policy implication of our results is the need to create better working conditions for informal workers.
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Glebov, Alexey. Logic of Digital Circuits. Nova Science Publishers, Incorporated, 2016.

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Book chapters on the topic "Binary logit"

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Frühwirth-Schnatter, Sylvia, and Rudolf Frühwirth. "Data Augmentation and MCMC for Binary and Multinomial Logit Models." In Statistical Modelling and Regression Structures, 111–32. Heidelberg: Physica-Verlag HD, 2009. http://dx.doi.org/10.1007/978-3-7908-2413-1_7.

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Ganbaatar, Tsend-Ayush. "Using Demographic Variables to Determine Target Segments in Binary Logit Models." In Advances in Applied Economic Research, 193–224. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-48454-9_15.

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Xu, Wen, JiaJun Li, and Bin Shen. "Influencing Factor Analysis of Logistics Service Satisfaction in China: A Binary Logit Model Approach." In Smart Transportation Systems 2020, 79–88. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5270-0_7.

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Mitchell, R. J. "Logic and Binary Data." In Microprocessor Systems, 30–37. London: Macmillan Education UK, 1995. http://dx.doi.org/10.1007/978-1-349-13812-8_4.

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Stonham, T. J. "Operations on Binary Data." In Digital Logic Techniques, 15–28. Boston, MA: Springer US, 1987. http://dx.doi.org/10.1007/978-1-4615-6856-8_2.

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Bryant, Randal E., and Christoph Meinel. "Ordered Binary Decision Diagrams." In Logic Synthesis and Verification, 285–307. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0817-5_11.

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Dubois, Catherine. "Formally Verified Transformation of Non-binary Constraints into Binary Constraints." In Functional and Constraint Logic Programming, 117–28. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75333-7_7.

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Demoen, Bart, and André Mariën. "Implementation of Prolog as binary definite programs." In Logic Programming, 165–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/3-540-55460-2_12.

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Idrissou, Yaya, Alassan Seidou Assani, Mohamed Nasser Baco, and Ibrahim Alkoiret Traoré. "Determinants of Cattle Farmers’ Perception of Climate Change in the Dry and Subhumid Tropical Zones of Benin (West Africa)." In African Handbook of Climate Change Adaptation, 197–212. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-45106-6_16.

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AbstractUnderstanding the factors influencing the perception of climate change can help improve policies for strengthening the adaptive capacity of pastoralists with regard to climate change. Despite this importance, few studies have focused on this issue, especially among cattle farmers. In order to attempt filling this gap, this study analyzed the determinants of the perception of climate change by cattle farmers distributed in the dry and sub-humid tropical zones of Benin as well as the current adaptation strategies developed by these farmers. For this purpose, surveys were carried out through group discussions and an individual questionnaire administered to 360 cattle farmers in the two climatic zones. The data collected related to the sociodemographic characteristics of cattle farmers and their perception of climate change and adaptation strategies. A binary logit model has identified the factors that influence cattle farmers’ perceptions of climate change. The results of the study showed that cattle farmers perceive a drop in rain (at least 77%), an increase in temperature (at least 80%), and violent winds (at least 60%). Breeding experience, level of education of the farmer, household size, membership of a breeders’ organization, and cattle herd size determine these perceptions. Four major groups of adaptation strategies have been developed by farmers to cope with climate change. These are production adjustment strategies, activity diversification strategies, livestock management strategies, and selection strategies. The political implication of this study is that government and development partners should integrate these factors into projects and programs related to climate change.
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Morris, Noel M. "Binary systems and computer logic." In Mastering Electronic and Electrical Calculations, 357–76. London: Macmillan Education UK, 1996. http://dx.doi.org/10.1007/978-1-349-13705-3_18.

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Conference papers on the topic "Binary logit"

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Li, Chunyan, and Jun Chen. "An Improvement of the Binary Logit Model for Trip Generation Forecasting." In 2009 International Conference on Measuring Technology and Mechatronics Automation. IEEE, 2009. http://dx.doi.org/10.1109/icmtma.2009.251.

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Zhu, Hongguo, Yiyi Zhang, and Zhuanglin Ma. "Commuter Travel Behavior of Trip Chaining Based on Binary Logit Model." In 17th COTA International Conference of Transportation Professionals. Reston, VA: American Society of Civil Engineers, 2018. http://dx.doi.org/10.1061/9780784480915.416.

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Keren, Gil, Sivan Sabato, and Björn Schuller. "A Walkthrough for the Principle of Logit Separation." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/861.

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We consider neural network training, in applications in which there are many possible classes, but at test-time, the task is a binary classification task of determining whether the given example belongs to a specific class. We define the Single Logit Classification (SLC) task: training the network so that at test-time, it would be possible to accurately identify whether the example belongs to a given class in a computationally efficient manner, based only on the output logit for this class. We propose a natural principle, the Principle of Logit Separation, as a guideline for choosing and designing loss functions that are suitable for SLC. We show that the Principle of Logit Separation is a crucial ingredient for success in the SLC task, and that SLC results in considerable speedups when the number of classes is large.
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Jiang, Kang, Nannan Zhang, and Zhongxiang Feng. "A Binary Logit Model for Commute Mode Choice: A Case Study of Hefei." In 14th COTA International Conference of Transportation Professionals. Reston, VA: American Society of Civil Engineers, 2014. http://dx.doi.org/10.1061/9780784413623.290.

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Zhou, Feng, Jiajun Huang, and Ruihua Xu. "Study on Influencing Factors of Public Transport Attractiveness Based on the Binary Logit Model." In 14th COTA International Conference of Transportation Professionals. Reston, VA: American Society of Civil Engineers, 2014. http://dx.doi.org/10.1061/9780784413623.137.

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Yang, Jian, Yongbing Jiao, and Chunxia Zhang. "A Binary Logit Estimation of Controllable Factors Affecting Adoption of RFID by Agro-food Firms." In 2011 IEEE 8th International Conference on e-Business Engineering (ICEBE). IEEE, 2011. http://dx.doi.org/10.1109/icebe.2011.13.

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Basbas, S., V. Tetou, and I. Politis. "Ordinal and binary logistic logit models for examination of behavioral, infrastructure and perception factors influencing biking." In URBAN TRANSPORT 2013. Southampton, UK: WIT Press, 2013. http://dx.doi.org/10.2495/ut130461.

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Liu, Yuanlin, and Ye Li. "Characteristic Variables and Behavior Analysis of Simple and Complex Non-Work Trip Chains Base on Binary Logit Model." In 17th COTA International Conference of Transportation Professionals. Reston, VA: American Society of Civil Engineers, 2018. http://dx.doi.org/10.1061/9780784480915.398.

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Burnap, Alex, Yi Ren, Honglak Lee, Richard Gonzalez, and Panos Y. Papalambros. "Improving Preference Prediction Accuracy With Feature Learning." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-35440.

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Motivated by continued interest within the design community to model design preferences, this paper investigates the question of predicting preferences with particular application to consumer purchase behavior: How can we obtain high prediction accuracy in a consumer preference model using market purchase data? To this end, we employ sparse coding and sparse restricted Boltzmann machines, recent methods from machine learning, to transform the original market data into a sparse and high-dimensional representation. We show that these ‘feature learning’ techniques, which are independent from the preference model itself (e.g., logit model), can complement existing efforts towards high-accuracy preference prediction. Using actual passenger car market data, we achieve significant improvement in prediction accuracy on a binary preference task by properly transforming the original consumer variables and passenger car variables to a sparse and high-dimensional representation.
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Suliyanto, Marisa Rifada, and Eko Tjahjono. "Estimation of nonparametric binary logistic regression model with local likelihood logit estimation method (case study of diabetes mellitus patients at Surabaya Hajj General Hospital)." In SYMPOSIUM ON BIOMATHEMATICS 2019 (SYMOMATH 2019). AIP Publishing, 2020. http://dx.doi.org/10.1063/5.0025807.

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