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Prendergast, Tim. "Interrupted Time Series Analysis Techniques in Pharmacovigilance." Thèse, Université d'Ottawa / University of Ottawa, 2013. http://hdl.handle.net/10393/30291.
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This thesis considers an approach to evaluate the effectiveness of risk communications for prescription drugs by performing interrupted time series analysis of prescription drug volumes prior to and after the risk communication date.
The paper presents methods for detecting change in the presence of autocorrelation and techniques to reduce bias in estimation. Statistical results and data plots are presented for 63 data series. Size and power of the statistical techniques are considered, and a correspondence analysis between these statistical techniques and a small group of physicians is performed.
The methods considered in this thesis correspond weakly with physician sentiment, and exhibit inflated type I errors in the presence of significant autocorrelation.
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Gerlach, Laura A. "Increasing Organ Donations in Maryland: An Interrupted Time Series Analysis." ScholarWorks, 2018. https://scholarworks.waldenu.edu/dissertations/5707.
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The state of Maryland has been unsuccessful in achieving its goal of registering all of its population as organ donors. The purpose of this correlational study was to understand if allowing registered donors to remain anonymous would increase donor registration rates.
The theoretical foundation of this study was the theory of planned behavior. Data were collected from the Motor Vehicle Administration of Maryland and the Division of Motor Vehicle of Virginia. The data were analyzed using regression displacement, interrupted time series analysis, auto correlation analysis, and Arima Box Jenkins methodology. According to the study findings, offering the option to remain anonymous and registering to be an organ donor with no heart icon on the driver's license did not have the immediate effect of encouraging more people to register as an organ donor. Parameter estimates from an Arima autoregression analysis did suggest that the impact of the removal of the heart icon may have a delayed impact, although data availability limited attempts at further investigation.
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Hummelgren, Axel. "Vilket pris avgör vad du handlar? : En kvantitativ jämförande studie av krympflations påverkan på försäljning." Thesis, Uppsala universitet, Nationalekonomiska institutionen, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-419854.
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Konsumtionsbeteende är idag en viktig undersökningspunkt för att med säkerhet kunna genomföra implementeringar av nya policys inom konsumentpolitiken. Både klassiska nationalekonomiska teorier och beteendeekonomiska teorier används för att beskriva och förutsäga dessa beteenden, men det saknas undersökningar på deras faktiska kopplingar till olika typer av prissättning. Denna uppsats har gjort ett försök till att undersöka vilken påverkan en förändring i pris genom en förändring i paketstorlek har på efterfrågan. Den har även försökt ge en analys till om de förändringar som noteras är kopplade till beteendeekonomi eller klassisk nationalekonomisk teori. Med hjälp av en vanlig tidstrendsanalys tillsammans med en interrupted-time-series-analysis har försäljningstrenderna för försäljning i KG för två substituerande produkter skapats och jämförts. Dessa fastställer att förändringens påverkan framförallt stämmer överens med teorier gällande beteendeekonomi men att sambandet mellan en förändring i försäljningsnivå och en förändring i paketstorlek inte är säkerställt. Analyserna gjorda i denna studie blir därför inte fastställda och möjligtvis otillräckliga för att besvara den fråga som ställts. Jag som författare vill därför uppmana till att flera utvecklande studier inom ämnet bör utföras för att säkerställa möjliga resultat.Consumer behaviour is today an important aspect of making quality decisions regarding policies on the consumer market. Both classical economical models and behavioural economical models are used to describe and predict these kinds of behaviours. Although todays studies on their connections to different methods of pricing are lacking. This paper tries to investigate what kind of impact a change in price by changing the size of the good has on demand. It also tries to produce an analysis on if this impact is connected with bevioural or classical economic theories. Based on a classical time-trend analysis together with an interrupted-time-series-analysis different trends for sales in KG regarding two substitutional products have been created. These determine that the effects on demand are most likely connected to behavioural economics but that the effects aren’t statistically significant. The analysis done in this paper therefore cannot be statistically determined and indicates that further studies on the subject need to be done to answer these questions with more certainty.
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Bonander, Carl. "Searching for causal effects of road traffic safety interventions : applications of the interrupted time series design." Licentiate thesis, Karlstads universitet, Institutionen för miljö- och livsvetenskaper, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-35781.
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Traffic-related injuries represent a global public health problem, and contribute largely to mortality and years lived with disability worldwide. Over the course of the last decades, improvements to road traffic safety and injury surveillance systems have resulted in a shift in focus from the prevention of motor vehicle accidents to the control of injury events involving vulnerable road users (VRUs), such as cyclists and moped riders. There have been calls for improvements to the evaluation of safety interventions due to methodological problems associated with the most commonly used study designs. The purpose of this licentiate thesis was to assess the strengths and limitations of the interrupted time series (ITS) design, which has gained some attention for its ability to provide valid effect estimates. Two national road safety interventions involving VRUs were selected as cases: the Swedish bicycle helmet law for children under the age 15, and the tightening of licensing rules for Class 1 mopeds. The empirical results suggest that both interventions were effective in improving the safety of VRUs. Unless other concurrent events affect the treatment population at the exact time of intervention, the effect estimates should be internally valid. One of the main limitations of the study design is the inability to identify why the interventions were successful, especially if they are complex and multifaceted. A lack of reliable exposure data can also pose a further threat to studies of interventions involving VRUs if the intervention can affect the exposure itself. It may also be difficult to generalize the exact effect estimates to other regions and populations. Future studies should consider the use of the ITS design to enhance the internal validity of before-after measurements.Traffic-related injuries represent a global public health problem, and contribute largely to mortality and years lived with disability. Over the course of the last decades, improvements to road traffic safety and injury surveillance systems have resulted in a shift in focus from motor vehicle accidents to injury events involving vulnerable road users (VRUs), such as cyclists and moped riders. There have been calls for improvements to the evaluation of safety interventions due to methodological problems associated with the most commonly used study designs. The purpose of this licentiate thesis was to assess the strengths and limitations of the interrupted time series (ITS) design, which has gained some attention for its ability to provide valid effect estimates while accounting for secular trends. Two national interventions involving VRUs were selected as cases: the Swedish bicycle helmet law for children under the age 15, and the tightening of licensing rules for Class 1 mopeds. The empirical results suggest that both interventions were effective. These results are discussed in the light of some methodological considerations regarding internal and external validity, data quality and the ability to fully understand key causal mechanisms behind complex interventions.
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Akbari, Ayub. "Change in Referral Patterns to Nephrologists after Estimated Glomerular Filtration Rate (eGFR) Reporting: An interrupted time series analysis." Thesis, University of Ottawa (Canada), 2011. http://hdl.handle.net/10393/28785.
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Objectives: To update a Cochrane review of interventions to improve outpatient referral and to assess changes in referrals to nephrologists after initiating automatic estimated glomerular filtration rate (eGFR) reporting.
Methods: Systematic review using standardized Cochrane methods. Before and after study with interrupted time series analysis using data from retrospective chart review on referrals from family medicine to nephrology.
Results: Review added one new study and removed one for total of 17 studies. Referrals improved with education and structured referral sheets. Of 2766 eligible referrals for one-year pre-eGFR reporting to one-year post, 96.6% were reviewed. There was a 68.2% increase in referrals for chronic kidney disease (P < 0.01) and a 64.1% increase in total appropriate referrals (P =0.01) with no significant change in proportion of appropriate referrals (-2.5%, P=0.56).
Conclusion: Systematic review findings did not change from the previous review. eGFR reporting increased both appropriate and inappropriate referrals.
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Condron, Aaron. "An impact evaluation of u.s. arms export controls on the u.s. defense industrial base an interrupted time-series analysis." Honors in the Major Thesis, University of Central Florida, 2011. http://digital.library.ucf.edu/cdm/ref/collection/ETH/id/363.
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The United States Defense Industrial Base (USDIB) is an essential industry to both the economic prosperity of the US and its strategic control over many advanced military systems and technologies. The USDIB, which encompasses the industries of aerospace and defense, is a volatile industry - prone to many internal and external factors that cause demand to ebb and flow widely year over year. Among the factors that influence the volume of systems the USDIB delivers to its international customers are the arms export controls of the US. These controls impose a divergence from the historical US foreign policy of furthering an open exchange of ideas and liberalized trade. These controls, imposed by the Departments of Commerce, Defense, and State rigidly control all international presence of the Industry. The overlapping controls create an inability to conform to rapidly changing realpolitiks, leaving these controls in an archaic state. This, in turn, imposes a great deal of anxiety and expense upon managers within and outside of the USDIB. Using autoregressive integrated moving average time-series analyses, this paper confirms that the implementation of or amendment to broad arms export controls correlates to significant and near immediate declines in USDIB export volumes. In the context of the US's share of world arms exports, these controls impose up to a 20% decline in export volume.B.S.B.A.
Bachelors
Business Administration
Finance
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Donnelly, Neil James Public Health & Community Medicine Faculty of Medicine UNSW. "The use of interrupted time series analysis to evaluate the impact of Pharmaceutical Benefits Scheme policies on drug utilisation in Australia." Awarded by:University of New South Wales. Public Health and Community Medicine, 2005. http://handle.unsw.edu.au/1959.4/22509.
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PROBLEM INVESTIGATED: Methodological issues and policy implications arising from the application of interrupted time series (ITS) analyses to assess the impact of Pharmaceutical Benefit Scheme (PBS) subsidisation policies on drug utilisation in Australia. PROCEDURES FOLLOWED: A critical review of methodological issues relating to the application and analysis of ITS designs was undertaken. This included an examination of drug utilisation data sources in Australia. The PBS policies examined were: (i) the introduction of copayments in 1990; (ii) the introduction of re-supply limits in 1994 and (iii) the introduction of a form of reference pricing in 1998. Monthly aggregate drug utilisation data was obtained from the Australian Department of Health and Ageing. Segmented regression analyses incorporating autocorrelated errors were implemented and statistical diagnostics applied to ensure correct ITS model specification. Alternative seasonal modelling approaches were compared. RESULTS OBTAINED: The copayment ITS evaluation found that while these copayments produced a reduction in the utilisation of essential and discretionary medications, this effect was stronger for discretionary drugs. An unintended policy effect was a large anticipatory increase in drug utilisation during the month prior to the copayments. Repatriation PBS data was also utilised due to the limited number of pre-intervention data points in the Community series. The re-supply limit ITS evaluation found that the 20-day rule markedly reduced the size of the seasonal increase during the month of December. However, logistic regression analyses showed that the size of this reduction attenuated over time, highlighting the need to consider alternative analysis strategies when applying a ITS approach. The reference pricing ITS evaluation found that this policy had achieved its drug utilisation objectives for H2RAs and ACE Inhibitors. However with regard to CCBs, no increase in the utilisation of benchmark priced drug was apparent, which probably reflected clinical concerns at the time about the safety of these drugs. MAJOR CONCLUSIONS: Well implemented ITS analyses provide a valuable tool for evaluating the impact of PBS subsidisation policy change on drug utilisation in Australia. As with any methodology, however, different design and data integrity issues will affect the quality of information provided.
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Kylén, Linda. "Utvärdering av mötesfria vägar : Analys av olyckor på mötesfria vägar i Karlstadsregionen." Thesis, Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-33081.
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Sedan år 1998 har det i Nollvisionens fotspår startats ett utvecklingsprogram i Sverige som syftar till att omvandla gamla 13 meters landsvägar och motortrafikleder till mötesfria. Implementeringen var tänkt att påtagligt reducera antalet mötes- och omkörningsolyckor samt singelolyckor med svåra konsekvenser i form av svårt skadade och dödade utan att försämra trafiksäkerheten i övrigt. Syftet med denna studie är att göra en effektmätning av de mötesfria vägarnas införande i Karlstadsregionen samt att göra en sammanställning av de olycksrisker mötesfria vägar omfattas av. Frågeställningarna som används i studien är: - Har det blivit säkrare på vägarna sedan implementeringen av mötesfria vägar i Karlstadsregionen? - Hur sker olyckor på mötesfria vägar inom Karlstadsregionen? För att beskriva hur olyckor sker på mötesfria vägar inom Karlstadsregionen har en deskriptiv analys tillämpats som grundats på de beskrivningar av händelseförlopp som dokumenterats i STRADA och CORE, mellan åren 2010-2013. För att avgöra huruvida vägarna blivit säkrare sedan implementering tillämpades en segmenterad linjär regressionsanalys där antalet personskadeolyckor studerats, tre år innan och tre år efter ombyggnad för respektive vägavsnitt. Singel- och upphinnandeolyckor var de dominerande olyckstyperna på mötesfria vägar i Karlstadsregionen mellan åren 2010-2013 då de sammanlagt stod för 72,3% av samtliga olyckor som medfört skada. Vid kategoriseringen av huvudorsak till olycka framgick det att 42% av alla olyckor kan spåras till brister i samspel mellan trafikanter och väderförhållanden bedömdes i 24,1% av fallen vara huvudorsak till olycka. Den statistiska analysen var inte signifikant, men gav indikation på att vägarna blivit säkrare sedan implementering då trenden för samtliga skadade minskat.In the footsteps of Vision Zero, a development program in Sweden was initiated in 1998. The program aimed to increase road safety on existing 13-meter roads and express roads by implementing median barriers. The purpose of this study is to measure the impact of the transformed roadways in the Karlstad region and to examine the different types of accident risks the roadways are covered by. The research questions used are: - Has the implementation of median barriers in the Karlstad region contributed to safer roads? - How do accidents occur on roads with median barriers? To describe how accidents occur on roads with median barriers in Karlstad region a descriptive analysis was made by the description of event that is documented in STRADA and CORE, between the years 2010-2013. To determine whether the roads became safer after implementation a segmented linear regression analysis was applied. Accidents resulting in injury were examined, three years before and three years after reconstruction for each road section. Single-vehicle accidents and rear-end collisions were the dominating accident types on roadways with median barriers in the Karlstad region between the years 2010-2013. They together accounted for 72,3% of all accidents that resulted in injury. When the main cause of accident was examined, it emerged that 42% of all accidents could be traced to deficiencies in the interaction between road users. Weather conditions were estimated to be the main cause of accident in 24,1% of all the studied cases. The statistical analysis was not significant, but indicated that the roads became safer after the implementation since the observed trend for all types of injured decreased.
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Ma, Xinyi. "The effect of the random breath testing policy in Australia." Thesis, The University of Sydney, 2013. http://hdl.handle.net/2123/10281.
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Road crashes are a major cause of death and serious injuries in many countries and extract a high cost on society. Drink driving is one of the most important reasons for road crashes. Many countries have enacted drink-driving policy and legislation. In Australia, Random Breath Testing (RBT) program is the main legislation against drink driving. This research examines the effect of RBT program by investigating whether RBT program is effective in reducing road accident rates; and whether there is a relationship between increased RBT enforcement level and decreased road accident rates. The road accident data from New South Wales (NSW), Queensland (QLD), Western Australia (WA) and Tasmania (TAS) in Australia during the time period 1978-1992 are analysed in three models. Model 1 investigates the effect of RBT program using interrupted time series (ITS) analysis, finding that the RBT program is effective in reducing road accident rates in all four States. Model 2 estimates the effect of RBT enforcement level on road accident rates. The results of Model 2 indicate that increasing RBT enforcement level reduces fatal accident rate (TFAR) in all States, reduces single-vehicle night-time accident rate (SVNAR) in all States except QLD, and reduces serious accident rate (TSAR) in WA and TAS. In addition, the implemented RBT enforcement levels are found effective in NSW, below effective level in WA, and above effective level in QLD and TAS. Model 3 reexamines the effect of RBT enforcement level on road accident rates without imposing any functional form of the RBT enforcement level using the semiparametric regression model. The estimation results in Model 3 are generally consistent with the findings in Model 2, in the sense that increasing RBT enforcement level is effective in reducing road accident rates only when RBT enforcement level lies within a specific range for each State. Conclusions, policy implications and limitations are discussed at the end of the thesis.
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Afonso, Eliane Terezinha. "Impacto da vacinação com a PCV10 na morbidade hospitalar por pneumonia no Brasil: análise de série temporal interrompida." Universidade Federal de Goiás, 2015. http://repositorio.bc.ufg.br/tede/handle/tede/5507.
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BACKGROUND: Pneumonia causes substantial morbidity and mortality in all age groups around the world. The 10-valent pneumococcal conjugate vaccine (PCV10) was introduced into the routine infant immunization in Brazil, free of charge, in March 2010. The aim of this study was to evaluate the impact PCV10 vaccination on rates of all cause pneumonia hospitalizations one year and three years after its introduction in Brazil. METHODS: We conducted two interrupted time series analysis studies. The first evaluated only the direct effect of PCV10 vaccination, in five Brazilian cities (Belo Horizonte, Curitiba, Porto Alegre, São Paulo and Recife), and was conducted one year after starting the vaccination. The second study evaluated the direct and indirect impact (individuals not vaccinated) of PCV10 vaccination in Brazil, and was conducted three years after vaccination. We used data from the Brazilian Hospitalization System from 2005-2013. The main outcome was monthly rates of all-cause pneumonia hospitalizations identified by ICD-10 codes J12-J18. We used hospitalization rates for congenital malformations and non-respiratory causes as a comparison groups. The time-series analysis was based on a generalized linear model. Pneumonia rates observed in the pre-vaccination period were used to estimate the hospitalization rates in the post-vaccination period of each study, adjusting for seasonality and secular trends. To estimate the direct (2-23 months of age) and indirect (≥5 years of age) impact of PCV10 vaccination, we calculated the percentage change in hospitalization rates, as the observed divided by the predicted rates of hospitalization in the post-intervention period minus one, with respective 95% CI and p values. The number of all-cause pneumonia hospitalizations averted by vaccination was calculated taking into account the difference between the predicted and observed number in the PCV10 post vaccination period. RESULTS: One year after introduction of PCV10 in Brazil, significant declines in hospitalizations for pneumonia in children aged 2-23 months were noted in Belo Horizonte (28.7%), Curitiba (23.3%), and Recife (27.4%). After three years of the introduction of PCV10, 461,519 pneumonia hospitalizations were averted in Brazil, and a significant decrease in rates of pneumonia hospitalization was observed in unvaccinated individuals aged 5-39 years, ranging from 14.1-17.4% (p<0.05). In contrast, an increased trend in pneumonia hospitalizations (p=0·004) was observed for elderly (≥ 65 years). CONCLUSION: Vaccination with PCV10 in Brazil was associated with reduction of pneumonia hospitalizations in vaccinated individuals. Herd effect was observed in individuals aged 5-39 years after three years of vaccination. Potential reasons for the increased trend in pneumonia hospitalization rates in the elderly should be investigated.
INTRODUÇÃO: As pneumonias contribuem com alta carga de morbimortalidades em todo mundo. No Brasil, a vacina pneumocócica conjugada 10 valente (PCV10) foi introduzida na rotina de imunização da infância em março de 2010. Este estudo teve como objetivo avaliar o impacto da vacinação nas taxas de hospitalizações por pneumonia no Brasil no curto e médio prazo do início da vacinação. METODOLOGIA: Dois estudos de séries temporais interrompidas foram conduzidos. O primeiro avaliou o efeito direto da vacinação em cinco capitais brasileiras (Belo Horizonte, Curitiba, Porto Alegre, São Paulo e Recife) e foi conduzido após um ano de introdução da PCV10 no país. O segundo estudo avaliou o impacto direto e indireto (população não vacinada) da vacinação em todo país e foi conduzido três anos após sua introdução. Os dados de hospitalizações foram obtidos do Sistema de Informações Hospitalares (SIH-SUS) de 2005 a 2013. O desfecho principal foi a taxa mensal de hospitalização por pneumonia definida pelos códigos J12-J18 da CID10. As taxas de hospitalizações por malformações congênitas e causas não respiratórias foram utilizadas como grupos de comparações. A análise de série temporal utilizou um modelo de regressão linear generalizado. As taxas de hospitalizações por pneumonia observadas no período pré-PCV10, ajustadas por tendência secular e sazonalidade, foram utilizadas para estimar as taxas no período pós-PCV10. O impacto da vacinação para cada faixa etária foi calculado como o percentual de mudança nas taxas de hospitalizações, dividindo-se as taxas observadas pelas taxas preditas do período pós PCV10, menos um. Os respectivos IC95% e os valores de p foram apresentados. O número de hospitalizações por pneumonia evitadas após três anos de vacinação foi estimado pela diferença entre os números de hospitalizações por pneumonia preditos e observados no período pós-vacinação. RESULTADOS: Após um ano de introdução da PCV10 no Brasil, observou-se significativo declínio nas taxas de hospitalizações por pneumonia em crianças de 2 a 23 meses em três das cinco capitais estudadas: Belo Horizonte (28,7%), Curitiba (23,3%), e Recife (27,4%). Após três anos da introdução da PCV10, 461.519 hospitalizações por pneumonia foram evitadas no Brasil e um significativo declínio nas taxas de pneumonia foi observado em indivíduos não vacinados de 5 a 39 anos variando de 14,1% a 17,4% (p<0,05). No entanto, observou-se um aumento significativo (9,9%, p=0,004) nas taxas de hospitalizações por pneumonia para idosos ≥65 anos. CONCLUSÕES: A vacinação com a PCV10 foi associada à significativa redução das hospitalizações por pneumonia na infância. Adicionalmente, o estudo evidenciou importante redução das hospitalizações por pneumonia em grupos etários não vacinados, sinalizando efeito indireto conferida pela vacina. A tendência de aumento das hospitalizações por pneumonias em idosos necessita de investigações para elucidação dos fatores envolvidos nesse fenômeno.
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López, Bernal J. "The use of interrupted time series for the evaluation of public health interventions." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2018. http://researchonline.lshtm.ac.uk/4648680/.
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Robust evaluation of public health interventions is required to ensure that interventions that lead to the greatest health benefit are adopted. However, traditional experimental evaluative designs are rarely possible for public health evaluation. Furthermore, alternative “quasi-experimental” designs are underused, are seldom covered in detail in epidemiology courses and are excluded from many guidelines and reviews. As a result population level health interventions have suffered from an “evaluative bias” whereby interventions not amenable to randomised control trials are often either poorly evaluated or not evaluated at all. Interrupted time series (ITS) analysis is one of the most powerful quasi-experimental designs for evaluating the effectiveness of population level health interventions. It is increasingly being used to evaluate the effectiveness of interventions ranging from clinical guidelines to national public health legislation. The basic design involves comparing the outcome of interest before and after an intervention, whilst accounting for any underlying trend. Nevertheless, ITS studies, like other quasiexperiments have more inherent threats to their internal validity than experimental designs, many of which have not been adequately addressed in the existing literature. Further guidance is needed on these threats and how they are best addressed in the design, application and appraisal of ITS studies. The overarching aims of this thesis are to improve the way that interrupted time series studies of public health interventions are designed in order to reduce the risk of bias and to make robust ITS designs more accessible to evaluators of public health interventions. This will be achieved through a range of methodological and applied studies using ITS designs.
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Pope, Kenneth James. "Time series analysis." Thesis, University of Cambridge, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.318445.
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Yin, Jiang Ling. "Financial time series analysis." Thesis, University of Macau, 2011. http://umaclib3.umac.mo/record=b2492929.
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Lam, Vai Iam. "Time domain approach in time series analysis." Thesis, University of Macau, 2000. http://umaclib3.umac.mo/record=b1446633.
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Malan, Karien. "Stationary multivariate time series analysis." Pretoria : [s.n.], 2008. http://upetd.up.ac.za/thesis/available/etd-06132008-173800.
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Alagon, J. "Discriminant analysis for time series." Thesis, University of Oxford, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.375222.
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Warnes, Alexis. "Diagnostics in time series analysis." Thesis, Durham University, 1994. http://etheses.dur.ac.uk/5159/.
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The portmanteau diagnostic test for goodness of model fit is studied. It is found that the true variances of the estimated residual autocorrelation function are potentially deflated considerably below their asymptotic level, and exhibit high correlations with each other. This suggests a new portmanteau test, ignoring the first p + q residual autocorrelation terms and hence approximating the asymptotic chi-squared distribution more closely. Simulations show that this alternative portmanteau test produces greater accuracy in its estimated significance levels, especially in small samples. Theory and discussions follow, pertaining to both the Dynamic Linear Model and the Bayesian method of forecasting. The concept of long-term equivalence is defined. The difficulties with the discounting approach in the DLM are then illustrated through an example, before deriving equations for the step-ahead forecast distribution which could, instead, be used to estimate the evolution variance matrix W(_t). Non-uniqueness of W in the constant time series DLM is the principal drawback with this idea; however, it is proven that in any class of long-term equivalent models only p degrees of freedom can be fixed in W, leading to a potentially diagonal form for this matrix. The bias in the k(^th) step-ahead forecast error produced by any TSDLM variance (mis)specification is calculated. This yields the variances and covariances of the forecast error distribution; given sample estimates of these, it proves possible to solve equations arising from these calculations both for V and p elements of W. Simulations, and a "head-to-head" comparison, for the frequently-applied steady model illustrate the accuracy of the predictive calculations, both in the convergence properties of the sample (co)variances, and the estimates Ṽ and Ŵ. The method is then applied to a 2-dimensional constant TSDLM. Further simulations illustrate the success of the approach in producing accurate on-line estimates for the true variance specifications within this widely-used model.
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Chan, Hon Tsang. "Discriminant analysis of time series." Thesis, University of Newcastle Upon Tyne, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.315614.
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Huang, Naijing. "Essays in time series analysis." Thesis, Boston College, 2015. http://hdl.handle.net/2345/bc-ir:104627.
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Thesis advisor: Zhijie XiaoI have three chapters in my dissertation. The first chapter is about the estimation and inference for DSGE model; the second chapter is about testing financial contagion among stock markets, and in the last chapter, I propose a new econometrics method to forecast inflation interval. This first chapter studies proper inference and asymptotically accurate structural break tests for parameters in Dynamic Stochastic General Equilibrium (DSGE) models in a maximum likelihood framework. Two empirically relevant issues may invalidate the conventional inference procedures and structural break tests for parameters in DSGE models: (i) weak identification and (ii) moderate parameter instability. DSGE literatures focus on dealing with weak identification issue, but ignore the impact of moderate parameter instability. This paper contributes to the literature via considering the joint impact of two issues in DSGE framework. The main results are: in a weakly identified DSGE model, (i) moderate instability from weakly identified parameters would not affect the validity of standard inference procedures or structural break tests; (ii) however, if strongly identified parameters are featured with moderate time-variation, the asymptotic distributions of test statistics would deviate from standard ones and would no longer be nuisance parameter free, which renders standard inference procedures and structural break tests invalid and provides practitioners misleading inference results; (iii) as long as I concentrate out strongly identified parameters, the instability impact of them would disappear as the sample size goes to infinity, which recovers the power of conventional inference procedure and structural break tests for weakly identified parameters. To illustrate my results, I simulate and estimate a modified version of the Hansen (1985) Real Business Cycle model and find that my theoretical results provide reasonable guidance for finite sample inference of the parameters in the model. I show that confidence intervals that incorporate weak identification and moderate parameter instability reduce the biases of confidence intervals that ignore those effects. While I focus on DSGE models in this paper, all of my theoretical results could be applied to any linear dynamic models or nonlinear GMM models. The second chapter, regarding the asymmetric and leptokurtic behavior of financial data, we propose a new contagion test in the quantile regression framework that is robust to model misspecification. Unlike conventional correlation-based tests, the proposed quantile contagion test allows us to investigate the stock market contagion at various quantiles, not only at the mean. We show that the quantile contagion test can detect a contagion effect that is possibly ignored by correlation-based tests. A wide range of simulation studies show that the proposed test is superior to the correlation-based tests in terms of size and power. We compare our test with correlation-based tests using three real data sets: the 1994 Tequila crisis, the 1997 Asia crisis, and the 2001 Argentina crisis. Empirical results show substantial differences between two types of tests. In the third chapter, I use Quantile Bayesian Approach-- to do the interval forecast for inflation in the semi-parametric framework. This new method introduces Bayesian solution to the quantile framework for two reasons: 1. It enables us to get more efficient quantile estimates when the informative prior is used (He and Yang (2012)); 2. We use Markov Chain Monte Carlo (MCMC) algorithm to generate samples of the posterior distribution for unknown parameters and take the mean or mode as the estimates. This MCMC estimator takes advantage of numerical integration over the standard numerical differentiation based optimization, especially when the likelihood function is complicated and multi-modal. Simulation results find better interval forecasting performance of Quantile Bayesian Approach than commonly used parametric approach
Thesis (PhD) — Boston College, 2015
Submitted to: Boston College. Graduate School of Arts and Sciences
Discipline: Economics
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Fulcher, Benjamin D. "Highly comparative time-series analysis." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:642b65cf-4686-4709-9f9d-135e73cfe12e.
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In this thesis, a highly comparative framework for time-series analysis is developed. The approach draws on large, interdisciplinary collections of over 9000 time-series analysis methods, or operations, and over 30 000 time series, which we have assembled. Statistical learning methods were used to analyze structure in the set of operations applied to the time series, allowing us to relate different types of scientific methods to one another, and to investigate redundancy across them. An analogous process applied to the data allowed different types of time series to be linked based on their properties, and in particular to connect time series generated by theoretical models with those measured from relevant real-world systems. In the remainder of the thesis, methods for addressing specific problems in time-series analysis are presented that use our diverse collection of operations to represent time series in terms of their measured properties. The broad utility of this highly comparative approach is demonstrated using various case studies, including the discrimination of pathological heart beat series, classification of Parkinsonian phonemes, estimation of the scaling exponent of self-affine time series, prediction of cord pH from fetal heart rates recorded during labor, and the assignment of emotional content to speech recordings. Our methods are also applied to labeled datasets of short time-series patterns studied in temporal data mining, where our feature-based approach exhibits benefits over conventional time-domain classifiers. Lastly, a feature-based dimensionality reduction framework is developed that links dependencies measured between operations to the number of free parameters in a time-series model that could be used to generate a time-series dataset.
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Hwang, Peggy May T. "Factor analysis of time series /." The Ohio State University, 1997. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487944660933305.
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Rego, Padraig. "Bikesharing as an intervention: Does it increase cycling? : A controlled interrupted time series study from Helsinki, Finland." Thesis, Uppsala universitet, Internationell mödra- och barnhälsovård (IMCH), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-396564.
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Background Bikesharing is a versatile intervention, that enables cheap and convenient cycling for urban populations, and according to recent literature, has a positive impact on health, safety and the economy. Many of these impacts are based on the assumption of a modal shift induced by bikesharing, i.e. implementing a Bicycle Sharing System (BSS) will increase population cycling. However, the evidence is inconclusive. The aim of this study was to evaluate if the intervention of implementing a BSS increases cycling. The study was conducted using bicycle count data from Helsinki between 2014 to 2018. Methods A controlled interrupted time series design was used in combination with segmented regression as the method. An intervention series and a control series were analysed separately. The slopes (trend) and intercepts (level) of pre-intervention (2014&2015) segments were compared with post-intervention segments (2016-2018). The same analysis was performed in both intervention series and control series. ResultsThe results from the intervention series showed an increase of 105% in the level of the outcome after the implementation of the intervention. Simultaneously, the control series showed that the underlying trend of cycling remained largely unchanged during the whole study period (level increased by 3%). Stratified analysis supported these results in both intervention and control series. Conclusion The analysis of the intervention series revealed, that the level of the outcome increased sharply after the intervention, implying that the intervention had an immediate effect. However, the lack of statistical significance in the analysis of the slopes made it impossible to determine if the effect was sustained.
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Gore, Christopher Mark. "A time series classifier." Diss., Rolla, Mo. : Missouri University of Science and Technology, 2008. http://scholarsmine.mst.edu/thesis/pdf/Gore_09007dcc804e6461.pdf.
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Thesis (M.S.)--Missouri University of Science and Technology, 2008.Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed April 29, 2008) Includes bibliographical references (p. 53-55).
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Rivera, Pablo Marshall. "Analysis of a cross-section of time series using structural time series models." Thesis, London School of Economics and Political Science (University of London), 1990. http://etheses.lse.ac.uk/13/.
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This study deals with multivariate structural time series models, and in particular, with the analysis and modelling of cross-sections of time series. In this context, no cause and effect relationships are assumed between the time series, although they are subject to the same overall environment. The main motivations in the analysis of cross-sections of time series are (i) the gains in efficiency in the estimation of the irregular, trend and seasonal components; and (ii) the analysis of models with common effects. The study contains essentially two parts. The first one considers models with a general specification for the correlation of the irregular, trend and seasonal components across the time series. Four structural time series models are presented, and the estimation of the components of the time series, as well as the estimation of the parameters which define this components, is discussed. The second part of the study deals with dynamic error components models where the irregular, trend and seasonal components are generated by common, as well as individual, effects. The extension to models for multivariate observations of cross-sections is also considered. Several applications of the methods studied are presented. Particularly relevant is an econometric study of the demand for energy in the U. K.
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Reiss, Joshua D. "The analysis of chaotic time series." Diss., Full text available online (restricted access), 2001. http://images.lib.monash.edu.au/ts/theses/reiss.pdf.
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Healey, J. J. "Qualitative analysis of experimental time series." Thesis, University of Oxford, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302891.
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謝永然 and Wing-yin Tse. "Time series analysis in inventory management." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1993. http://hub.hku.hk/bib/B31977510.
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Yiu, Fu-keung, and 饒富強. "Time series analysis of financial index." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1996. http://hub.hku.hk/bib/B31267804.
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Dunne, Peter Gerard. "Essays in financial time-series analysis." Thesis, Queen's University Belfast, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.337690.
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Brunsdon, T. M. "Time series analysis of compositional data." Thesis, University of Southampton, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.378257.
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Schwill, Stephan. "Entropy analysis of financial time series." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/entropy-analysis-of-financial-time-series(7e0c84fe-5d0b-41bc-96c6-5e41ffa5b8fe).html.
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This thesis applies entropy as a model independent measure to address research questions concerning the dynamics of various financial time series. The thesis consists of three main studies as presented in chapters 3, 4 and 5. Chapters 3 and 4 apply an entropy measure to conduct a bivariate analysis of drawdowns and drawups in foreign exchange rates. Chapter 5 investigates the dynamics of investment strategies of hedge funds using entropy of realised volatility in a conditioning model. In all three studies, methods from information theory are applied in novel ways to financial time series. As Information Theory and its central concept of entropy are not widely used in the economic sciences, a methodology chapter was therefore included in chapter 2 that gives an overview on the theoretical background and statistical features of the entropy measures used in the three main studies. In the first two studies the focus is on mutual information and transfer entropy. Both measures are used to identify dependencies between two exchange rates. The chosen measures generalise, in a well defined manner, correlation and Granger causality. A different entropy measure, the approximate entropy, is used in the third study to analyse the serial structure of S&P realised volatility. The study of drawdowns and drawups has so far been concentrated on their uni- variate characteristics. Encoding the drawdown information of a time series into a time series of discrete values, Chapter 3 uses entropy measures to analyse the correlation and cross correlations of drawdowns and drawups. The method to encode the drawdown information is explained and applied to daily and hourly EUR/USD and GBP/USD exchange rates from 2001 to 2012. For the daily series, we find evidence of dependence among the largest draws (i.e. 5% and 95% quantiles), but it is not as strong as the correlation between the daily returns of the same pair of FX rates. There is also dependence between lead/lagged values of these draws. Similar and stronger findings were found among the hourly data. We further use transfer entropy to examine the spill over and lead-lag information flow between drawup/drawdown of the two exchange rates. Such information flow is indeed detectable in both daily and hourly data. The amount of information transferred is considerably higher for the hourly than the daily data. Both daily and hourly series show clear evidence of information flowing from EUR/USD to GBP/USD and, slightly stronger, in the reverse direction. Robustness tests, using effective transfer entropy, show that the information measured is not due to noise. Chapter 4 uses state space models of volatility to investigate volatility spill overs between exchange rates. Our use of entropy related measures in the investigation of dependencies of two state space series is novel. A set of five daily exchange rates from emerging and developed economies against the dollar over the period 1999 to 2012 is used. We find that among the currency pairs, the co-movement of EUR/USD and CHF/USD volatility states show the strongest observed relationship. With the use of transfer entropy, we find evidence for information flows between the volatility state series of AUD, CAD and BRL.Chapter 5 uses the entropy of S&P realised volatility in detecting changes of volatility regime in order to re-examine the theme of market volatility timing of hedge funds. A one-factor model is used, conditioned on information about the entropy of market volatility, to measure the dynamic of hedge funds equity exposure. On a cross section of around 2500 hedge funds with a focus on the US equity markets we find that, over the period from 2000 to 2014, hedge funds adjust their exposure dynamically in response to changes in volatility regime. This adds to the literature on the volatility timing behaviour of hedge fund manager, but using entropy as a model independent measure of volatility regime. Finally, chapter 6 summarises and concludes with some suggestions for future research.
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Correia, Maria Inês Costa. "Cluster analysis of financial time series." Master's thesis, Instituto Superior de Economia e Gestão, 2020. http://hdl.handle.net/10400.5/21016.
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Mestrado em Mathematical FinanceEsta dissertação aplica o método da Signature como medida de similaridade entre dois objetos de séries temporais usando as propriedades de ordem 2 da Signature e aplicando-as a um método de Clustering Asimétrico. O método é comparado com uma abordagem de Clustering mais tradicional, onde a similaridade é medida usando Dynamic Time Warping, desenvolvido para trabalhar com séries temporais. O intuito é considerar a abordagem tradicional como benchmark e compará-la ao método da Signature através do tempo de computação, desempenho e algumas aplicações. Estes métodos são aplicados num conjunto de dados de séries temporais financeiras de Fundos Mútuos do Luxemburgo. Após a revisão da literatura, apresentamos o método Dynamic Time Warping e o método da Signature. Prossegue-se com a explicação das abordagens de Clustering Tradicional, nomeadamente k-Means, e Clustering Espectral Assimétrico, nomeadamente k-Axes, desenvolvido por Atev (2011). O último capítulo é dedicado à Investigação Prática onde os métodos anteriores são aplicados ao conjunto de dados. Os resultados confirmam que o método da Signature têm efectivamente potencial para Machine Learning e previsão, como sugerido por Levin, Lyons and Ni (2013).
This thesis applies the Signature method as a measurement of similarities between two time-series objects, using the Signature properties of order 2, and its application to Asymmetric Spectral Clustering. The method is compared with a more Traditional Clustering approach where similarities are measured using Dynamic Time Warping, developed to work with time-series data. The intention for this is to consider the traditional approach as a benchmark and compare it to the Signature method through computation times, performance, and applications. These methods are applied to a financial time series data set of Mutual Exchange Funds from Luxembourg. After the literature review, we introduce the Dynamic Time Warping method and the Signature method. We continue with the explanation of Traditional Clustering approaches, namely k-Means, and Asymmetric Clustering techniques, namely the k-Axes algorithm, developed by Atev (2011). The last chapter is dedicated to Practical Research where the previous methods are applied to the data set. Results confirm that the Signature method has indeed potential for machine learning and prediction, as suggested by Levin, Lyons, and Ni (2013).
info:eu-repo/semantics/publishedVersion
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Åkerlund, Agnes. "Time-Series Analysis of Pulp Prices." Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-39726.
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The pulp and paper industry has a significant role in Europe’s economy and society, and its significance is still growing. The pulp market and the customers’ requirements are highly affected by the pulp market prices and the requested kind of pulp, i.e., Elementary Chlorine Free (ECF) or Total Chlorine Free (TCF). There is a need to predict different market aspects, where the market price is one, to gain a better understanding of a business situation. Understanding market dynamics can support organizations to optimize their processes and production. Forecasting future pulp prices has not recently been done, but it would help businesses to make decisions that are more informed about where to sell their product. The studies existing about the pulp industry and forecast of market prices were completed over 20 years ago, and the market has changed since then in terms of, e.g., demand and production volume. There is a research gap within the pulp industry from a market price perspective. The pulp market is similar to, e.g., the energy industry in some aspects, and time-series analysis has been used to forecast electricity prices to support decision making by electricity producers and retailers. Autoregressive Integrated Moving Average (ARIMA) is one time-series analysis method that is used when data are collected with a constant frequency and when the average is not constant. Holt-Winters model is a well-known and simple time-series analysis. In this thesis, time-series analysis is used to predict the weekly market price for pulp the three upcoming months, with the research question “With what accuracy can time-series analysis be used to forecast the European PIX price on pulp on a week-ahead basis?”. The research method in this thesis is a case study where data are collected through the data collection method documents. First, articles are studied to gain understanding within the problem area leading to the use of the artefact time-series analyses and a case study. Then, historical data are collected from the organization FOEX Fastmarkets, where a new market price of pulp has been released every Tuesday since September 1996. The dataset has a total of 1200 data points. After data cleaning, it is merged to 1196 data points that are used for the analysis. To evaluate the results from the time-series analysis models ARIMA and Holt-Winter, Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) are used. The software RStudio is used for programming. The results shows that the ARIMA model provides the most accurate results. The mean value for MAE is 16,59 for ARIMA and 44,61 for Holt-Winters. The mean value for MAPE is 1,99% for ARIMA and 5,37% for Holt-Winters.
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Michel, Jonathan R. "Essays in Nonlinear Time Series Analysis." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1555001297904158.
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Khalfaoui, Rabeh. "Wavelet analysis of financial time series." Thesis, Aix-Marseille, 2012. http://www.theses.fr/2012AIXM1083.
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Cette thèse traite la contribution des méthodes d'ondelettes sur la modélisation des séries temporelles économiques et financières et se compose de deux parties: une partie univariée et une partie multivariée. Dans la première partie (chapitres 2 et 3), nous adoptons le cas univarié. Premièrement, nous examinons la classe des processus longue mémoire non-stationnaires. Une étude de simulation a été effectuée afin de comparer la performance de certaines méthodes d'estimation semi-paramétrique du paramètre d'intégration fractionnaire. Nous examinons aussi la mémoire longue dans la volatilité en utilisant des modèles FIGARCH pour les données de l'énergie. Les résultats montrent que la méthode d'estimation Exact Local Whittle de Shimotsu et Phillips [2005] est la meilleure méthode de détection de longue mémoire et la volatilité du pétrole exhibe une forte évidence de phénomène de mémoire longue. Ensuite, nous analysons le risque de marché des séries de rendements univariées de marchés boursier, qui est mesurée par le risque systématique (bêta) à différents horizons temporels. Les résultats montrent que le Bêta n'est pas stable, en raison de multi-trading stratégies des investisseurs. Les résultats basés sur l'analyse montrent que le risque mesuré par la VaR est plus concentrée aux plus hautes fréquences. La deuxième partie (chapitres 4 et 5) traite l'estimation de la variance et la corrélation conditionnelle des séries temporelles multivariées. Nous considérons deux classes de séries temporelles: les séries temporelles stationnaires (rendements) et les séries temporelles non-stationnaires (séries en niveaux)This thesis deals with the contribution of wavelet methods on modeling economic and financial time series and consists of two parts: the univariate time series and multivariate time series. In the first part (chapters 2 and 3), we adopt univariate case. First, we examine the class of non-stationary long memory processes. A simulation study is carried out in order to compare the performance of some semi-parametric estimation methods for fractional differencing parameter. We also examine the long memory in volatility using FIGARCH models to model energy data. Results show that the Exact local Whittle estimation method of Shimotsu and Phillips [2005] is the better one and the oil volatility exhibit strong evidence of long memory. Next, we analyze the market risk of univariate stock market returns which is measured by systematic risk (beta) at different time horizons. Results show that beta is not stable, due to multi-trading strategies of investors. Results based on VaR analysis show that risk is more concentrated at higher frequency. The second part (chapters 4 and 5) deals with estimation of the conditional variance and correlation of multivariate time series. We consider two classes of time series: the stationary time series (returns) and the non-stationary time series (levels). We develop a novel approach, which combines wavelet multi-resolution analysis and multivariate GARCH models, i.e. the wavelet-based multivariate GARCH approach. However, to evaluate the volatility forecasts we compare the performance of several multivariate models using some criteria, such as loss functions, VaR estimation and hedging strategies
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Yiu, Fu-keung. "Time series analysis of financial index /." Hong Kong : University of Hong Kong, 1996. http://sunzi.lib.hku.hk/hkuto/record.jsp?B18003047.
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Guthrey, Delparde Raleigh. "Time series analysis of ozone data." CSUSB ScholarWorks, 1998. https://scholarworks.lib.csusb.edu/etd-project/1788.
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Ishida, Isao. "Essays on financial time series /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2004. http://wwwlib.umi.com/cr/ucsd/fullcit?p3153696.
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Hossain, Md Jobayer. "Analysis of nonstationary time series with time varying frequencies." Ann Arbor, Mich. : ProQuest, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3220410.
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Thesis (Ph.D. in Statistical Science)--S.M.U.Title from PDF title page (viewed July 6, 2007). Source: Dissertation Abstracts International, Volume: 67-05, Section: B, page: 2641. Advisers: Wayne A. Woodward; Henry L. Gray. Includes bibliographical references.
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Morrill, Jeffrey P., and Jonathan Delatizky. "REAL-TIME RECOGNITION OF TIME-SERIES PATTERNS." International Foundation for Telemetering, 1993. http://hdl.handle.net/10150/608854.
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International Telemetering Conference Proceedings / October 25-28, 1993 / Riviera Hotel and Convention Center, Las Vegas, NevadaThis paper describes a real-time implementation of the pattern recognition technology originally developed by BBN [Delatizky et al] for post-processing of time-sampled telemetry data. This makes it possible to monitor a data stream for a characteristic shape, such as an arrhythmic heartbeat or a step-response whose overshoot is unacceptably large. Once programmed to recognize patterns of interest, it generates a symbolic description of a time-series signal in intuitive, object-oriented terms. The basic technique is to decompose the signal into a hierarchy of simpler components using rules of grammar, analogous to the process of decomposing a sentence into phrases and words. This paper describes the basic technique used for pattern recognition of time-series signals and the problems that must be solved to apply the techniques in real time. We present experimental results for an unoptimized prototype demonstrating that 4000 samples per second can be handled easily on conventional hardware.
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Koller, Stefan. "Applications of Time Series Analysis for Finance." St. Gallen, 2007. http://www.biblio.unisg.ch/org/biblio/edoc.nsf/wwwDisplayIdentifier/05604814001/$FILE/05604814001.pdf.
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Mui, Chi Seong. "Frequency domain approach to time series analysis." Thesis, University of Macau, 2000. http://umaclib3.umac.mo/record=b1446676.
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Purutcuoglu, Vilda. "Unit Root Problems In Time Series Analysis." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/2/12604701/index.pdf.
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In time series models, autoregressive processes are one of the most popular stochastic processes, which are stationary under certain conditions. In this study we consider nonstationary autoregressive models of order one, which have iid random errors. One of the important nonstationary time series models is the unit root process in AR (1), which simply implies that a shock to the system has permanent effect through time. Therefore, testing unit root is a very important problem.
However, under nonstationarity, any estimator of the autoregressive coefficient does not have a known exact distribution and the usual t &ndashstatistic is not accurate even if the sample size is very large. Hence,Wiener process is invoked to obtain the asymptotic distribution of the LSE under normality. The first four moments of under normality have been worked out for large n. In 1998, Tiku and Wong proposed the new test statistics and whose type I error and power values are calculated by using three &ndash
moment chi &ndash
square or four &ndash
moment F approximations. The test statistics are based on the modified maximum likelihood estimators and the least square estimators, respectively. They evaluated the type I errors and the power of these tests for a family of symmetric distributions (scaled Student&rsquo
s t). In this thesis, we have extended this work to skewed distributions, namely, gamma and generalized logistic.
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Glover, James N. "Time series analysis near a fixed point." Thesis, University of Cambridge, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.295353.
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Al-Wasel, Ibrahim A. "Spectral analysis for replicated biomedical time series." Thesis, Lancaster University, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.412585.
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Manrique, Garcia Aurora. "Econometric analysis of limited dependent time series." Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.389797.
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Clarke, Liam. "Nonlinear time series analysis of data streams." Thesis, University of Oxford, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.401147.
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Cheung, Chung-pak, and 張松柏. "Multivariate time series analysis on airport transportation." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1991. http://hub.hku.hk/bib/B31976499.
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Nguyen, Minh Hoai. "Segment-based SVMs for Time Series Analysis." Research Showcase @ CMU, 2012. http://repository.cmu.edu/dissertations/202.
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Enabling computers to understand human and animal behavior has the potential to revolutionize many areas that benefit society such as clinical diagnosis, human-computer interaction, and social robotics. Critical to the understanding of human and animal behavior, and any temporally-varying phenomenon in general, is the capability to segment, classify, and cluster time series data. This thesis proposes segment-based Support Vector Machines (Seg-SVMs), a framework for supervised, weakly-supervised, and unsupervised time series analysis. Seg-SVMs outperform state-of-the-art approaches by combining three powerful ideas: energy-based structure prediction, bag-of-words representation, and maximum-margin learning. Energy-based structure prediction provides a principled mechanism for concurrent top-down recognition and bottom-up temporal localization. Bag-of-words representation provides segment-based features that tolerate misalignment errors and are computationally efficient. Maximum-margin learning, such as SVM and Structure Output SVM, has a convex learning formulation; it produces classifiers that are discriminative and less prone to over-fitting.
In this thesis, we show how Seg-SVMs outperform state-of-the-art approaches for segmenting, classifying, and clustering human and animal behavior in video and accelerometer data of varying complexity. We illustrate these benefits in the problems of facial event detection, sequence labeling of human actions, and temporal clustering of animal behavior. In addition, the Seg-SVMs framework naturally provides solutions to two novel problems: early detection of human actions and weakly-supervised discovery of discriminative events.
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Moeanaddin, Rahim. "Aspects of non-linear time series analysis." Thesis, University of Kent, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.328463.
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