Dissertations / Theses on the topic 'Bayesian statistical decision theory - Graphic methods'
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馮榮錦 and Wing-kam Tony Fung. "Analysis of outliers using graphical and quasi-Bayesian methods." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1987. http://hub.hku.hk/bib/B31230842.
Full textArmstrong, Helen School of Mathematics UNSW. "Bayesian estimation of decomposable Gaussian graphical models." Awarded by:University of New South Wales. School of Mathematics, 2005. http://handle.unsw.edu.au/1959.4/24295.
Full textFung, Wing-kam Tony. "Analysis of outliers using graphical and quasi-Bayesian methods /." [Hong Kong] : University of Hong Kong, 1987. http://sunzi.lib.hku.hk/hkuto/record.jsp?B1236146X.
Full textThaithara, Balan Sreekumar. "Bayesian methods for astrophysical data analysis." Thesis, University of Cambridge, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.607847.
Full textMetcalfe, Leanne N. "Bayesian methods in determining health burdens." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/31809.
Full textCommittee Chair: Vidakovic, Brani; Committee Member: Griffin, Paul; Committee Member: Kemp, Charlie; Committee Member: Sprigle, Stephen; Committee Member: Villivalam, Arun. Part of the SMARTech Electronic Thesis and Dissertation Collection.
Pei, Xin, and 裴欣. "Bayesian approach to road safety analyses." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B46591989.
Full textChiu, Jing-Er. "Applications of bayesian methods to arthritis research /." free to MU campus, to others for purchase, 2001. http://wwwlib.umi.com/cr/mo/fullcit?p3036813.
Full textChan, Ka Hou. "Bayesian methods for solving linear systems." Thesis, University of Macau, 2011. http://umaclib3.umac.mo/record=b2493250.
Full textLau, Wai Kwong. "Bayesian nonparametric methods for some econometric problems /." View abstract or full-text, 2005. http://library.ust.hk/cgi/db/thesis.pl?ISMT%202005%20LAU.
Full textLarocque, Jean-René. "Advanced bayesian methods for array signal processing /." *McMaster only, 2001.
Find full textRiggelsen, Carsten. "Approximation methods for efficient learning of Bayesian networks /." Amsterdam ; Washington, DC : IOS Press, 2008. http://www.loc.gov/catdir/toc/fy0804/2007942192.html.
Full text林達明 and Daming Lin. "Reliability growth models and reliability acceptance sampling plans from a Bayesian viewpoint." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1995. http://hub.hku.hk/bib/B3123429X.
Full textSo, Moon-tong, and 蘇滿堂. "Applications of Bayesian statistical model selection in social scienceresearch." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B39312951.
Full text蕭偉成 and Wai-shing Siu. "On a subjective modelling of VaR: fa Bayesianapproach." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31225159.
Full textChinyamakobvu, Mutsa Carole. "Eliciting and combining expert opinion : an overview and comparison of methods." Thesis, Rhodes University, 2015. http://hdl.handle.net/10962/d1017827.
Full textNg, William Reilly James P. "Advances in wideband array signal processing using numerical Bayesian methods /." *McMaster only, 2003.
Find full textWoo, Bo-kei, and 胡寶琦. "A new hierarchical Bayesian approach to low-field magnetic resonance imaging." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31226917.
Full textThomas, Clifford S. "From 'tree' based Bayesian networks to mutual information classifiers : deriving a singly connected network classifier using an information theory based technique." Thesis, University of Stirling, 2005. http://hdl.handle.net/1893/2623.
Full textYee, Irene Mei Ling. "Local parametric poisson models for fisheries data." Thesis, University of British Columbia, 1988. http://hdl.handle.net/2429/28360.
Full textScience, Faculty of
Statistics, Department of
Graduate
Endres, Dominik M. "Bayesian and information-theoretic tools for neuroscience." Thesis, St Andrews, 2006. http://hdl.handle.net/10023/162.
Full textFang, Fang. "A simulation study for Bayesian hierarchical model selection methods." View electronic thesis (PDF), 2009. http://dl.uncw.edu/etd/2009-2/fangf/fangfang.pdf.
Full textNegash, Efrem Ocubamicael. "Risk and admissibility for a Weibull class of distributions." Thesis, Stellenbosch : Stellenbosch University, 2004. http://hdl.handle.net/10019.1/50086.
Full textENGLISH ABSTRACT: The Bayesian approach to decision-making is considered in this thesis for reliability/survival models pertaining to a Weibull class of distributions. A generalised right censored sampling scheme has been assumed and implemented. The Jeffreys' prior for the inverse mean lifetime and the survival function of the exponential model were derived. The consequent posterior distributions of these two parameters were obtained using this non-informative prior. In addition to the Jeffreys' prior, the natural conjugate prior was considered as a prior for the parameter of the exponential model and the consequent posterior distribution was derived. In many reliability problems, overestimating a certain parameter of interest is more detrimental than underestimating it and hence, the LINEX loss function was used to estimate the parameters and their consequent risk measures. Moreover, the same analogous derivations have been carried out relative to the commonly-used symmetrical squared error loss function. The risk function, the posterior risk and the integrated risk of the estimators were obtained and are regarded in this thesis as the risk measures. The performance of the estimators have been compared relative to these risk measures. For the Jeffreys' prior under the squared error loss function, the comparison resulted in crossing-over risk functions and hence, none of these estimators are completely admissible. However, relative to the LINEX loss function, it was found that a correct Bayesian estimator outperforms an incorrectly chosen alternative. On the other hand for the conjugate prior, crossing-over of the risk functions of the estimators were evident as a result. In comparing the performance of the Bayesian estimators, whenever closed-form expressions of the risk measures do not exist, numerical techniques such as Monte Carlo procedures were used. In similar fashion were the posterior risks and integrated risks used in the performance compansons. The Weibull pdf, with its scale and shape parameter, was also considered as a reliability model. The Jeffreys' prior and the consequent posterior distribution of the scale parameter of the Weibull model have also been derived when the shape parameter is known. In this case, the estimation process of the scale parameter is analogous to the exponential model. For the case when both parameters of the Weibull model are unknown, the Jeffreys' and the reference priors have been derived and the computational difficulty of the posterior analysis has been outlined. The Jeffreys' prior for the survival function of the Weibull model has also been derived, when the shape parameter is known. In all cases, two forms of the scalar estimation error have been t:. used to compare as much risk measures as possible. The performance of the estimators were compared for acceptability in a decision-making framework. This can be seen as a type of procedure that addresses robustness of an estimator relative to a chosen loss function.
AFRIKAANSE OPSOMMING: Die Bayes-benadering tot besluitneming is in hierdie tesis beskou vir betroubaarheids- / oorlewingsmodelle wat behoort tot 'n Weibull klas van verdelings. 'n Veralgemene regs gesensoreerde steekproefnemingsplan is aanvaar en geïmplementeer. Die Jeffreyse prior vir die inverse van die gemiddelde leeftyd en die oorlewingsfunksie is afgelei vir die eksponensiële model. Die gevolglike aposteriori-verdeling van hierdie twee parameters is afgelei, indien hierdie nie-inligtingge-wende apriori gebruik word. Addisioneel tot die Jeffreyse prior, is die natuurlike toegevoegde prior beskou vir die parameter van die eksponensiële model en ooreenstemmende aposteriori-verdeling is afgelei. In baie betroubaarheidsprobleme het die oorberaming van 'n parameter meer ernstige nagevolge as die onderberaming daarvan en omgekeerd en gevolglik is die LINEX verliesfunksie gebruik om die parameters te beraam tesame met ooreenstemmende risiko maatstawwe. Soortgelyke afleidings is gedoen vir hierdie algemene simmetriese kwadratiese verliesfunksie. Die risiko funksie, die aposteriori-risiko en die integreerde risiko van die beramers is verkry en word in hierdie tesis beskou as die risiko maatstawwe. Die gedrag van die beramers is vergelyk relatief tot hierdie risiko maatstawwe. Die vergelyking vir die Jeffreyse prior onder kwadratiese verliesfunksie het op oorkruisbare risiko funksies uitgevloei en gevolglik is geeneen van hierdie beramers volkome toelaatbaar nie. Relatief tot die LINEX verliesfunksie is egter gevind dat die korrekte Bayes-beramer beter vaar as die alternatiewe beramer. Aan die ander kant is gevind dat oorkruisbare risiko funksies van die beramers verkry word vir die toegevoegde apriori-verdeling. Met hierdie gedragsvergelykings van die beramers word numeriese tegnieke toegepas, soos die Monte Carlo prosedures, indien die maatstawwe nie in geslote vorm gevind kan word nie. Op soortgelyke wyse is die aposteriori-risiko en die integreerde risiko's gebruik in die gedragsvergelykings. Die Weibull waarskynlikheidsverdeling, met skaal- en vormingsparameter, is ook beskou as 'n betroubaarheidsmodel. Die Jeffreyse prior en die gevolglike aposteriori-verdeling van die skaalparameter van die Weibull model is afgelei, indien die vormingsparameter bekend is. In hierdie geval is die beramingsproses van die skaalparameter analoog aan die afleidings van die eksponensiële model. Indien beide parameters van die Weibull modelonbekend is, is die Jeffreyse prior en die verwysingsprior afgelei en is daarop gewys wat die berekeningskomplikasies is van 'n aposteriori-analise. Die Jeffreyse prior vir die oorlewingsfunksie van die Weibull model is ook afgelei, indien die vormingsparameter bekend is. In al die gevalle is twee vorms van die skalaar beramingsfoute gebruik in die vergelykings, sodat soveel as moontlik risiko maatstawwe vergelyk kan word. Die gedrag van die beramers is vergelyk vir aanvaarbaarheid binne die besluitnemingsraamwerk. Hierdie kan gesien word as 'n prosedure om die robuustheid van 'n beramer relatief tot 'n gekose verliesfunksie aan te spreek.
Chen, Hongshu. "Sampling-based Bayesian latent variable regression methods with applications in process engineering." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1189650596.
Full textMiyamoto, Kazutoshi Seaman John Weldon. "Bayesian and maximum likelihood methods for some two-segment generalized linear models." Waco, Tex. : Baylor University, 2008. http://hdl.handle.net/2104/5233.
Full textNortje, Willem Daniel. "Comparison of Bayesian learning and conjugate gradient descent training of neural networks." Pretoria : [s.n.], 2001. http://upetd.up.ac.za/thesis/available/etd-11092004-091241.
Full textKapur, Loveena. "Investigation of artificial neural networks, alternating conditional expectation, and Bayesian methods for reservoir characterization /." Digital version accessible at:, 1998. http://wwwlib.umi.com/cr/utexas/main.
Full textLiu, Jie. "Novel Bayesian Methods for Disease Mapping: An Application to Chronic Obstructive Pulmonary Disease." Link to electronic thesis, 2002. http://www.wpi.edu/Pubs/ETD/Available/etd-0501102-110350.
Full textKeywords: latent class model; Poisson regression model; Metropolis-Hastings sampler; order restriction; disease mapping. Includes bibliographical references.
Hecht, Marie B. "A comparison of Bayesian and classical statistical techniques used to identify hazardous traffic intersections." Thesis, The University of Arizona, 1988. http://hdl.handle.net/10150/276795.
Full textChau, Ka-ki, and 周嘉琪. "Informative drop-out models for longitudinal binary data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B2962714X.
Full textSwallow, Ben. "Bayesian multi-species modelling of non-negative continuous ecological data with a discrete mass at zero." Thesis, University of St Andrews, 2015. http://hdl.handle.net/10023/9626.
Full textHeywood, Ben. "Investigations into the use of quantified Bayesian maximum entropy methods to generate improved distribution maps and biomass estimates from fisheries acoustic survey data /." St Andrews, 2008. http://hdl.handle.net/10023/512.
Full textLiang, Yiheng. "Computational Methods for Discovering and Analyzing Causal Relationships in Health Data." Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc804966/.
Full textHoi, Ka In. "Enhancement of efficiency and robustness of Kalman filter based statistical air quality models by using Bayesian approach." Thesis, University of Macau, 2010. http://umaclib3.umac.mo/record=b2488003.
Full textMichell, Justin Walter. "A review of generalized linear models for count data with emphasis on current geospatial procedures." Thesis, Rhodes University, 2016. http://hdl.handle.net/10962/d1019989.
Full textWheeler, David C. "Diagnostic tools and remedial methods for collinearity in linear regression models with spatially varying coefficients." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1155413322.
Full textCave, Vanessa M. "Statistical models for the long-term monitoring of songbird populations : a Bayesian analysis of constant effort sites and ring-recovery data." Thesis, St Andrews, 2010. http://hdl.handle.net/10023/885.
Full textVo, Ba Tuong. "Random finite sets in Multi-object filtering." University of Western Australia. School of Electrical, Electronic and Computer Engineering, 2008. http://theses.library.uwa.edu.au/adt-WU2009.0045.
Full textGilbride, Timothy J. "Models for heterogeneous variable selection." Columbus, Ohio : Ohio State University, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1083591017.
Full textTitle from first page of PDF file. Document formatted into pages; contains xii, 138 p.; also includes graphics. Includes abstract and vita. Advisor: Greg M. Allenby, Dept. of Business Admnistration. Includes bibliographical references (p. 134-138).
Oteniya, Lloyd. "Bayesian belief networks for dementia diagnosis and other applications : a comparison of hand-crafting and construction using a novel data driven technique." Thesis, University of Stirling, 2008. http://hdl.handle.net/1893/497.
Full textBernardini, Diego Fernando de 1986. "Inferencia Bayesiana para valores extremos." [s.n.], 2010. http://repositorio.unicamp.br/jspui/handle/REPOSIP/307585.
Full textDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica
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Resumo: Iniciamos o presente trabalho apresentando uma breve introdução a teoria de valores extremos, estudando especialmente o comportamento da variável aleatória que representa o máximo de uma sequência de variáveis aleatórias independentes e identicamente distribuídas. Vemos que o Teorema dos Tipos Extremos (ou Teorema de Fisher-Tippett) constitui uma ferramenta fundamental no que diz respeito ao estudo do comportamento assintóticos destes máximos, permitindo a modelagem de dados que representem uma sequência de observações de máximos de um determinado fenômeno ou processo aleatório, através de uma classe de distribuições conhecida como família de distribuições de Valor Extremo Generalizada (Generalized Extreme Value - GEV). A distribuição Gumbel, associada ao máximo de distribuições como a Normal ou Gama entre outras, é um caso particular desta família. Torna-se interessante, assim, realizar inferência para os parâmetros desta família. Especificamente, a comparação entre os modelos Gumbel e GEV constitui o foco principal deste trabalho. No Capítulo 1 estudamos, no contexto da inferência clássica, o método de estimação por máxima verossimilhança para estes parâmetros e um procedimento de teste de razão de verossimilhanças adequado para testar a hipótese nula que representa o modelo Gumbel contra a hipótese que representa o modelo completo GEV. Prosseguimos, no Capítulo 2, com uma breve revisão em teoria de inferência Bayesiana obtendo inferências para o parâmetro de interesse em termos de sua distribuição a posteriori. Estudamos também a distribuição preditiva para valores futuros. No que diz respeito à comparação de modelos, estudamos inicialmente, neste contexto bayesiano, o fator de Bayes e o fator de Bayes a posteriori. Em seguida estudamos o Full Bayesian Significance Test (FBST), um teste de significância particularmente adequado para testar hipóteses precisas, como a hipótese que caracteriza o modelo Gumbel. Além disso, estudamos outros dois critérios para comparação de modelos, o BIC (Bayesian Information Criterion) e o DIC (Deviance Information Criterion). Estudamos as medidas de evidência especificamente no contexto da comparação entre os modelos Gumbel e GEV, bem como a distribuição preditiva, além dos intervalos de credibilidade e inferência a posteriori para os níveis de retorno associados a tempos de retorno fixos. O Capítulo 1 e parte do Capítulo 2 fornecem os fundamentos teóricos básicos deste trabalho, e estão fortemente baseados em Coles (2001) e O'Hagan (1994). No Capítulo 3 apresentamos o conhecido algoritmo de Metropolis-Hastings para simulação de distribuições de probabilidade e o algoritmo particular utilizado neste trabalho para a obtenção de amostras simuladas da distribuição a posteriori dos parâmetros de interesse. No capítulo seguinte formulamos a modelagem dos dados observados de máximos, apresentando a função de verossimilhança e estabelecendo a distribuição a priori para os parâmetros. Duas aplicações são apresentadas no Capítulo 5. A primeira delas trata das observações dos máximos trimestrais das taxas de desemprego nos Estados Unidos da América, entre o primeiro trimestre de 1994 e o primeiro trimestre de 2009. Na segunda aplicação estudamos os máximos semestrais dos níveis de maré em Newlyn, no sudoeste da Inglaterra, entre 1990 e 2007. Finalmente, uma breve discussão é apresentada no Capítulo 6.
Abstract: We begin this work presenting a brief introduction to the extreme value theory, specifically studying the behavior of the random variable which represents the maximum of a sequence of independent and identically distributed random variables. We see that the Extremal Types Theorem (or Fisher-Tippett Theorem) is a fundamental tool in the study of the asymptotic behavior of those maxima, allowing the modeling of data which represent a sequence of maxima observations of a given phenomenon or random process, through a class of distributions known as Generalized Extreme Value (GEV) family. We are interested in making inference about the parameters of this family. Specifically, the comparison between the Gumbel and GEV models constitute the main focus of this work. In Chapter 1 we study, in the context of classical inference, the method of maximum likelihood estimation for these parameters and likelihood ratio test procedure suitable for testing the null hypothesis associated to the Gumbel model against the hypothesis that represents the complete GEV model. We proceed, in Chapter 2, with a brief review on Bayesian inference theory. We also studied the predictive distribution for future values. With respect to the comparison of models, we initially study the Bayes factor and the posterior Bayes factor, in the Bayesian context. Next we study the Full Bayesian Significance Test (FBST), a significance test particularly suitable to test precise hypotheses, such as the hypothesis characterizing the Gumbel model. Furthermore, we study two other criteria for comparing models, the BIC (Bayesian Information Criterion) and the DIC (Deviance Information Criterion). We study the evidence measures specifically in the context of the comparison between the Gumbel and GEV models, as well as the predictive distribution, beyond the credible intervals and posterior inference to the return levels associated with fixed return periods. Chapter 1 and part of Chapter 2 provide the basic theoretical foundations of this work, and are strongly based on Coles (2001) and O'Hagan (1994). In Chapter 3 we present the well-known Metropolis-Hastings algorithm for simulation of probability distributions, and the particular algorithm used in this work to obtain simulated samples from the posterior distribution for the parameters of interest. In the next chapter we formulate the modeling of the observed data of maximum, presenting the likelihood function and setting the prior distribution for the parameters. Two applications are presented in Chapter 5. The first one deals with observations of the quarterly maximum for unemployment rates in the United States of America, between the first quarter of 1994 and first quarter of 2009. In the second application we studied the semiannual maximum of sea levels at Newlyn, in southwest of England, between 1990 and 2007. Finally, a brief discussion is presented in Chapter 6.
Mestrado
Estatistica
Mestre em Estatística
Barette, Tammy S. "A Bayesian approach to the estimation of adult skeletal age assessing the facility of multifactorial and three-dimensional methods to improve accuracy of age estimation /." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1180543680.
Full textLi, Qianqiu. "Bayesian inference on dynamics of individual and population hepatotoxicity via state space models." Connect to resource, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1124297874.
Full textTitle from first page of PDF file. Document formatted into pages; contains xiv, 155 p.; also includes graphics (some col.). Includes bibliographical references (p. 147-155). Available online via OhioLINK's ETD Center
Koullias, Stefanos. "Methodology for global optimization of computationally expensive design problems." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/49085.
Full textGouveia, Paulo Sergio da Silva. "Resolução do problema de alinhamento estrutural entre proteínas via técnicas de otimização global." [s.n.], 2011. http://repositorio.unicamp.br/jspui/handle/REPOSIP/305964.
Full textTese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica
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Resumo: A comparação estrutural entre proteínas é um problema fundamental na Biologia Molecular, pois estruturas similares entre proteínas, frequentemente refletem uma funcionalidade ou origem em comum entre as mesmas. No Problema de Alinhamento Estrutural entre Proteínas, buscamos encontrar o melhor alinhamento estrutural entre duas proteínas, ou seja, a melhor sobreposição entre duas estruturas proteicas, uma vez que alinhamentos locais podem levar a conclusões distorcidas sobre as características c funcionalidades das proteínas em estudo. A maioria dos métodos atuais para abordar este problema ou tem um custo computacional muito elevado ou não tem nenhuma garantia de convergência para o melhor alinhamento entre duas proteínas. Neste trabalho, propomos métodos computacionais para o Problema de Alinhamento Estrutural entre Proteínas que tenham boas garantias de encontrar o melhor alinhamento, mas em um tempo computacional razoável, utilizando as mais variadas técnicas de Otimização Global. A análise sobre os desempenhos de cada método tanto em termos quantitativos quanto qualitativos, além de um gráfico de Pareto, são apresentados de forma a facilitar a comparação entre os métodos com respeito à qualidade da solução e ao tempo computacional
Abstract: The structural comparison of proteins is a fundamental problem in Molecular Biology because similar structures often reflect a comrnon origin or funcionality. In the Protein Alignment problem onc seeks the best structural alignment between two proteins, i.e. the best overlap between two protein structures. Merely local alignments can lead to distorted conclusions on the problem features and functions. Most methods addressing this problem have a very high computational cost or are not supported with guarantecs of convergence to the best alignment. In this work we des-cribe computational methods for Protein Structural Alignment with good certificatea of optimality and reasonable computational execution time. We employ several Global Op-timization techniques. The performance is visualized by means of profile graphics and Pareto curves in order to take into account simultaneously emeiency and robustness of the methods
Doutorado
Otimização
Doutor em Matemática Aplicada
Vicini, Lorena. "Modelos de processo de Poisson não-homogêneo na presença de um ou mais pontos de mudança, aplicados a dados de poluição do ar." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/305867.
Full textTese (doutorado) ¿ Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica
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Resumo: A poluição do ar é um problema que tem afetado várias regiões ao redor do mundo. Em grandes centros urbanos, como é esperado, a concentração de poluição do ar é maior. Devido ao efeito do vento, no entanto, este problema não se restringe a esses centros, e consequentemente a poluição do ar se espalha para outras regiões. Os dados de poluição do ar são modelados por processos de Poisson não-homogêneos (NHPP) em três artigos: dois usando métodos Bayesianos com Markov Chain Monte Carlo (MCMC) para dados de contagem, e um usando análise de dados funcionais. O primeiro artigo discute o problema da especificação das distribuições a priori, incluindo a discussão de sensibilidade e convergência das cadeias MCMC. O segundo artigo introduz um modelo incluindo pontos de mudança para NHPP com a função taxa modelada por uma distribuição gama generalizada, usando métodos Bayesianos. Modelos com e sem pontos de mudança foram considerados para fins de comparação. O terceiro artigo utiliza análise de dados funcionais para estimar a função taxa de um NHPP. Esta estimação é feita sob a suposição de que a função taxa é contínua, mas com um número finito de pontos de descontinuidade na sua primeira derivada, localizados exatamente nos pontos de mudança. A função taxa e seus pontos de mudança foram estimadas utilizando suavização splines e uma função de penalização baseada nos candidatos a pontos de mudança. Os métodos desenvolvidos neste trabalho foram testadas através de simulações e aplicados a dados de poluição de ozônio da Cidade do México, descrevendo a qualidade do ar neste centro urbano. Ele conta quantas vezes, em um determinado período, a poluição do ar excede um limiar especificado de qualidade do ar, com base em níveis de concentração de ozônio. Observou-se que quanto mais complexos os modelos, incluindo os pontos de mudança, melhor foi o ajuste
Abstract: Air pollution is a problem that is currently affecting several regions around the world. In major urban centers, as expected, the concentration of air pollution is higher. Due to wind effect, however, this problem does not remain constrained in such centers, and air pollution spreads to other regions. In the thesis the air pollution data is modeled by Non-Homogeneous Poisson Process (NHPP) in three papers: two using Bayesian methods with Markov Chain Monte Carlo (MCMC) for count data, and one using functional data analysis. Paper one discuss the problem of the prior specification, including discussion of the sensitivity and convergence of the MCMC chains. Paper two introduces a model including change point for NHPP with rate function modeled by a generalized gamma distribution, using Bayesian methods. Models with and without change points were considered for comparison purposes. Paper three uses functional data analysis to estimate the rate function of a NHPP. This estimation is done under the assumption that the rate function is continuous, but with a finite number of discontinuity points in its first derivative, exactly at the change-points. The rate function and its change-points were estimated using splines smoothing and a penalty function based on candidate change points. The methods developed in this work were tested using simulations and applied to ozone pollution data from Mexico City, describing the air quality in this urban center. It counts how many times, in a determined period, air pollution exceeds a specified threshold of air quality, based on ozone concentration levels. It was observed that the more complex the models, including change-points, the better the fitting
Doutorado
Estatistica
Doutor em Estatística
Kao, Ling-Jing. "Data augmentation for latent variables in marketing." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1155653751.
Full textAntelo, Junior Ernesto Willams Molina. "Estimação conjunta de atraso de tempo subamostral e eco de referência para sinais de ultrassom." Universidade Tecnológica Federal do Paraná, 2017. http://repositorio.utfpr.edu.br/jspui/handle/1/2616.
Full textEm ensaios não destrutivos por ultrassom, o sinal obtido a partir de um sistema de aquisição de dados real podem estar contaminados por ruído e os ecos podem ter atrasos de tempo subamostrais. Em alguns casos, esses aspectos podem comprometer a informação obtida de um sinal por um sistema de aquisição. Para lidar com essas situações, podem ser utilizadas técnicas de estimativa de atraso temporal (Time Delay Estimation ou TDE) e também técnicas de reconstrução de sinais, para realizar aproximações e obter mais informações sobre o conjunto de dados. As técnicas de TDE podem ser utilizadas com diversas finalidades na defectoscopia, como por exemplo, para a localização precisa de defeitos em peças, no monitoramento da taxa de corrosão em peças, na medição da espessura de um determinado material e etc. Já os métodos de reconstrução de dados possuem uma vasta gama de aplicação, como nos NDT, no imageamento médico, em telecomunicações e etc. Em geral, a maioria das técnicas de estimativa de atraso temporal requerem um modelo de sinal com precisão elevada, caso contrário, a localização dessa estimativa pode ter sua qualidade reduzida. Neste trabalho, é proposto um esquema alternado que estima de forma conjunta, uma referência de eco e atrasos de tempo para vários ecos a partir de medições ruidosas. Além disso, reinterpretando as técnicas utilizadas a partir de uma perspectiva probabilística, estendem-se suas funcionalidades através de uma aplicação conjunta de um estimador de máxima verossimilhança (Maximum Likelihood Estimation ou MLE) e um estimador máximo a posteriori (MAP). Finalmente, através de simulações, resultados são apresentados para demonstrar a superioridade do método proposto em relação aos métodos convencionais.
Abstract (parágrafo único): In non-destructive testing (NDT) with ultrasound, the signal obtained from a real data acquisition system may be contaminated by noise and the echoes may have sub-sample time delays. In some cases, these aspects may compromise the information obtained from a signal by an acquisition system. To deal with these situations, Time Delay Estimation (TDE) techniques and signal reconstruction techniques can be used to perform approximations and also to obtain more information about the data set. TDE techniques can be used for a number of purposes in the defectoscopy, for example, for accurate location of defects in parts, monitoring the corrosion rate in pieces, measuring the thickness of a given material, and so on. Data reconstruction methods have a wide range of applications, such as NDT, medical imaging, telecommunications and so on. In general, most time delay estimation techniques require a high precision signal model, otherwise the location of this estimate may have reduced quality. In this work, an alternative scheme is proposed that jointly estimates an echo model and time delays for several echoes from noisy measurements. In addition, by reinterpreting the utilized techniques from a probabilistic perspective, its functionalities are extended through a joint application of a maximum likelihood estimator (MLE) and a maximum a posteriori (MAP) estimator. Finally, through simulations, results are presented to demonstrate the superiority of the proposed method over conventional methods.
"Optimal Bayesian estimators for image segmentation and surface reconstruction." Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, 1985. http://hdl.handle.net/1721.1/2879.
Full text"May, 1985."
Bibliography: p. 16.
"Advanced Research Projects Agency of the Department of Defense under Office of Naval Research Contract N00014-80-C-0505" "The author was supported by the Army Research Office under contract ARO-DAAG29-84-K-0005."
Cheng, Edward K. "Selected Legal Applications for Bayesian Methods." Thesis, 2018. https://doi.org/10.7916/D8H71Z8N.
Full text"Some Bayesian methods for analyzing mixtures of normal distributions." 2003. http://library.cuhk.edu.hk/record=b6073536.
Full text"April 2003."
Thesis (Ph.D.)--Chinese University of Hong Kong, 2003.
Includes bibliographical references (p. 124-132).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Mode of access: World Wide Web.