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Dissertations / Theses on the topic 'Bayesian analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Abrams, Keith Rowland. "Bayesian survival analysis." Thesis, University of Liverpool, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.316744.

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In cancer research the efficacy of a new treatment is often assessed by means of a clinical trial. In such trials the outcome measure of interest is usually time to death from entry into the study. The time to intermediate events may also be of interest, for example time to the spread of the disease to other organs (metastases). Thus, cancer clinical trials can be seen to generate multi-state data, in which patients may be in anyone of a finite number of states at a particular time. The classical analysis of data from cancer clinical trials uses a survival regression model. This type of model

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2

Yuan, Lin. "Bayesian nonparametric survival analysis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq22253.pdf.

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3

Conti, Gabriella, Sylvia Frühwirth-Schnatter, James J. Heckman, and Rémi Piatek. "Bayesian exploratory factor analysis." Elsevier, 2014. http://dx.doi.org/10.1016/j.jeconom.2014.06.008.

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This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional agg

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4

Fang, Qijun. "Hierarchical Bayesian Benchmark Dose Analysis." Diss., The University of Arizona, 2014. http://hdl.handle.net/10150/316773.

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An important objective in statistical risk assessment is estimation of minimum exposure levels, called Benchmark Doses (BMDs) that induce a pre-specified Benchmark Response (BMR) in a target population. Established inferential approaches for BMD analysis typically involve one-sided, frequentist confidence limits, leading in practice to what are called Benchmark Dose Lower Limits (BMDLs). Appeal to hierarchical Bayesian modeling and credible limits for building BMDLs is far less developed, however. Indeed, for the few existing forms of Bayesian BMDs, informative prior information is seldom inco

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5

Font, Valverde Martí. "Bayesian analysis of textual data." Doctoral thesis, Universitat Politècnica de Catalunya, 2016. http://hdl.handle.net/10803/384329.

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En esta tesis se desarrolla, siempre con el enfoque bayesiano en mente, una metodología estadística para el análisis de datos discretos en su aplicación en problemas estilometría. El análisis estadístico del estilo literario se ha utilizado para caracterizar el estilo de textos y autores, y para ayudar a resolver problemas de atribución de autoría. Estudios anteriores caracterizaron el estilo usando la longitud de las palabras, la longitud de las oraciones, y la proporción de los sustantivos, artículos, adjetivos o adverbios. Los datos que aquí se utilizan van, desde la frecuencia de frecuenci

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6

Husain, Syeda Tasmine. "Bayesian analysis of longitudinal models /." Internet access available to MUN users only, 2003. http://collections.mun.ca/u?/theses,163598.

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7

Brink, Anton Meredith. "Bayesian analysis of contingency tables." Thesis, Imperial College London, 1997. http://hdl.handle.net/10044/1/8948.

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8

LaBute, Gerard Joseph. "Pseudo-Bayesian response surface analysis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape15/PQDD_0001/MQ34971.pdf.

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9

Wright, Alan. "Bayesian pathway analysis in epigenetics." Thesis, University of Plymouth, 2013. http://hdl.handle.net/10026.1/1286.

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A typical gene expression data set consists of measurements of a large number of gene expressions, on a relatively small number of subjects, classified according to two or more outcomes, for example cancer or non-cancer. The identification of associations between gene expressions and outcome is a huge multiple testing problem. Early approaches to this problem involved the application of thousands of univariate tests with corrections for multiplicity. Over the past decade, numerous studies have demonstrated that analyzing gene expression data structured into predefined gene sets can produce ben

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10

O'Donovan, Daniel James. "Bayesian analysis of NMR data." Thesis, University of Cambridge, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.608789.

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11

Ma, Yimin. "Bayesian and empirical Bayesian analysis for the truncation parameter distribution families." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape10/PQDD_0027/NQ51000.pdf.

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12

Ma, Yimin. "Bayesian and empirical Bayesian analysis for the truncation parameter distribution families /." *McMaster only, 1998.

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13

Freeman, Corey Ross. "Bayesian network analysis of nuclear acquisitions." [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-3023.

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14

Bennett, James Elston. "Bayesian analysis of population pharmacokinetic models." Thesis, Imperial College London, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.363017.

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15

Gay, John Michael. "Frailties in the Bayesian survival analysis." Thesis, Imperial College London, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.405009.

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16

Huntriss, Alicia. "A Bayesian analysis of luminescence dating." Thesis, Durham University, 2008. http://etheses.dur.ac.uk/2928/.

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Luminescence dating is a widespread dating method used in the fields of archaeology and Quaternary science. As an experimental method it is subject to various uncertainties in the determination of parameters that are used to evaluate age. The need to express these uncertainties fully, combined with the prior archaeological knowledge commonly available, motivates the development of a Bayesian approach to the assessment of age based on luminescence data. The luminescence dating procedure is dissected into its component parts, and each is considered individually before being combined to find the

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17

Dimitrakopoulou, Vasiliki. "Bayesian variable selection in cluster analysis." Thesis, University of Kent, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.594195.

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Statistical analysis of data sets of high-dimensionality has met great interest over the past years, with great applications on disciplines such as medicine, nellascience, pattern recognition, image analysis and many others. The vast number of available variables though, contrary to the limited sample size, often mask the cluster structure of the data. It is often that some variables do not help in distinguishing the different clusters in the data; patterns over the samp•.l ed observations are, thus, usually confined to a small subset of variables. We are therefore interested in identifying th

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18

Purutçuŏglu, Vilda. "Bayesian methods for gene network analysis." Thesis, Lancaster University, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.497164.

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The two main aims of this thesis is initially to develop a new frequentist gene expression index (FOX) for Affymetrix oligonucleotide DNA arrays and then to present different stages of the analysis of a realistic MAPK/ERK pathway starting from its identification via quasi reaction set, then moving to its exact and approximated stochastic simulations and finally estimating its model parameters, rates, under distinct models.

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19

Frühwirth-Schnatter, Sylvia, Regina Tüchler, and Thomas Otter. "Bayesian analysis of the heterogeneity model." SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, 2002. http://epub.wu.ac.at/678/1/document.pdf.

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In the present paper we consider Bayesian estimation of a finite mixture of models with random effects which is also known as the heterogeneity model. First, we discuss the properties of various MCMC samplers that are obtained from full conditional Gibbs sampling by grouping and collapsing. Whereas full conditional Gibbs sampling turns out to be sensitive to the parameterization chosen for the mean structure of the model, the alternative sampler is robust in this respect. However, the logical extension of the approach to the sampling of the group variances does not further increase the efficie

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20

Domedel-Puig, Nuria. "Bayesian analysis of dynamic cellular processes." Thesis, Birkbeck (University of London), 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.499232.

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The objective of this thesis is to show how a Bayesian model comparison framework, coupled with the use of a formal mathematical modeling language (ODEs), can assist researchers in the process of modeling dynamic biological systems. The Bayesian approach differs from classical statistics in the way model parameters are treated: our state of knowledge about them can be summarised by probability distributions. All Bayesian inference depends on the data-updated version of these parameter distributions, the posterior densities. Averaging the data likelihood over the posterior results in the model

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21

Kaufmann, Sylvia, and Sylvia Frühwirth-Schnatter. "Bayesian Analysis of Switching ARCH Models." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 2000. http://epub.wu.ac.at/744/1/document.pdf.

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We consider a time series model with autoregressive conditional heteroskedasticity that is subject to changes in regime. The regimes evolve according to a multistate latent Markov switching process with unknown transition probabilities, and it is the constant in the variance process of the innovations that is subject to regime shifts. The joint estimation of the latent process and all model parameters is performed within a Bayesian framework using the method of Markov Chain Monte Carlo simulation. We perform model selection with respect to the number of states and the number of autoregressive

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22

Wakefield, Jon. "The Bayesian analysis of pharmacokinetic models." Thesis, University of Nottingham, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334806.

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23

Whaley, Steven R. J. "Bayesian analysis of sickness absence data." Thesis, University of Aberdeen, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.274884.

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Sickness-absence (SA) is a serious financial burden to UK industry totalling £10-12 billion in 1999 the equivalent of £434 and 7.8 days lost per worker. A major change in the reporting of SA occurred on 14 June 1982 with the introduction of self certification. Up to then all episodes had to be certified by a general practitioner. Since then, events that lasted for seven calendar or less have not required a GP's certificate and are 'self-certified'. A SA episode consists of the date the individual went off sick, the duration of the episode and a medical diagnosis given by either a GP or self di

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24

Welch, Jason. "Bayesian methods in chemical data analysis." Thesis, University of Cambridge, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.319893.

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25

Rigby, Robert Anthony. "Credibility intervals in Bayesian discriminant analysis." Thesis, Imperial College London, 1987. http://hdl.handle.net/10044/1/46292.

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26

Thaithara, Balan Sreekumar. "Bayesian methods for astrophysical data analysis." Thesis, University of Cambridge, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.607847.

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27

Marshall, Philip James. "Bayesian analysis of clusters of galaxies." Thesis, University of Cambridge, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.615701.

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28

Lewis, Stefanie Janneke. "Bayesian data analysis in baryon spectroscopy." Thesis, University of Glasgow, 2014. http://theses.gla.ac.uk/5245/.

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The strong interaction within a nucleon has been the focus of much theoretical and experimental work in nuclear and particle physics. Theorists have been improving lattice QCD calculations and developing quark models that define the inter-quark interactions, and experimentalists have spent years gathering data to support and improve these models. Finding nucleon resonance states provides essential information for the development of these theories and improves our understanding of the excited nucleon spectrum. There are a variety of quark models that have been proposed which each predict a uniq

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29

Alsing, Justin. "Bayesian analysis of weak gravitational lensing." Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/44571.

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This thesis is concerned with how to extract cosmological information from observations of weak gravitational lensing - the modification of observed galaxy images due to gravitational lensing by the large-scale structure of the Universe. Firstly, we are concerned with how we can use all possible observa- tional probes of weak lensing to squeeze out as much cosmological information as possible from future surveys. Up until now, the tra- ditional approach to cosmological weak lensing analyses have focused on the distortion of shapes of distant galaxies measured across the sky - cosmic shear. How

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30

Grapsa, Erofili. "Bayesian analysis for categorical survey data." Thesis, University of Southampton, 2010. https://eprints.soton.ac.uk/197303/.

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In this thesis, we develop Bayesian methodology for univariate and multivariate categorical survey data. The Multinomial model is used and the following problems are addressed. Limited information about the design variables leads us to model the unknown design variables taking into account the sampling scheme. Random effects are incorporated in the model to deal with the effect of sampling design, that produces the Multinomial GLMM and issues such as model comparison and model averaging are also discussed. The methodology is applied in a true dataset and estimates for population counts are obt

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31

ZHOU, RONG. "BAYESIAN ANALYSIS OF LOG-BINOMIAL MODELS." University of Cincinnati / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1115843904.

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32

Smith, Adam Nicholas. "Bayesian Analysis of Partitioned Demand Models." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1497895561381294.

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33

Wang, Xiaoyin. "Bayesian analysis of capture-recapture models /." free to MU campus, to others for purchase, 2002. http://wwwlib.umi.com/cr/mo/fullcit?p3060157.

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34

Thamrin, Sri Astuti. "Bayesian survival analysis using gene expression." Thesis, Queensland University of Technology, 2013. https://eprints.qut.edu.au/62666/1/Sri_Astuti_Thamrin_Thesis.pdf.

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This thesis developed and applied Bayesian models for the analysis of survival data. The gene expression was considered as explanatory variables within the Bayesian survival model which can be considered the new contribution in the analysis of such data. The censoring factor that is inherent of survival data has also been addressed in terms of its impact on the fitting of a finite mixture of Weibull distribution with and without covariates. To investigate this, simulation study were carried out under several censoring percentages. Censoring percentage as high as 80% is acceptable here as the w

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35

Kim, Yong Ku. "Bayesian multiresolution dynamic models." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1180465799.

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36

Noble, Robert Bruce. "Multivariate Applications of Bayesian Model Averaging." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/30180.

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The standard methodology when building statistical models has been to use one of several algorithms to systematically search the model space for a good model. If the number of variables is small then all possible models or best subset procedures may be used, but for data sets with a large number of variables, a stepwise procedure is usually implemented. The stepwise procedure of model selection was designed for its computational efficiency and is not guaranteed to find the best model with respect to any optimality criteria. While the model selected may not be the best possible of those in the

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37

Puza, Borek Dalibor. "Aspects of Bayesian biostatistics." Thesis, Canberra, ACT : The Australian National University, 1994. http://hdl.handle.net/1885/140911.

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38

Rowley, Mark. "Bayesian analysis of fluorescence lifetime imaging data." Thesis, King's College London (University of London), 2013. https://kclpure.kcl.ac.uk/portal/en/theses/bayesian-analysis-of-fluorescence-lifetime-imaging-data(c2fc5ecd-517d-451c-a449-f07e566b3482).html.

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The development of a novel photon-by-photon Bayesian analysis for time-domain Fluorescence Lifetime Imaging Microscopy (FLIM) data, and its application to both real experimental biological and synthetic data, is presented in this thesis. FLIM is an intensity-independent and sensitive optical technique for studying the cellular envi- ronment and can robustly exploit Fo¨rster Resonance Energy Transfer (FRET) to enable protein-protein interactions to be located within living or fixed cells. Careful analysis of fluorescence lifetime data, often comprising multi-exponential kinetics, is crucial to

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39

Padhy, Budhinath. "Bayesian Data Analysis For The Sovenian Plebiscite." Digital WPI, 2011. https://digitalcommons.wpi.edu/etd-theses/444.

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Slovenia became an independent republic with its own constitution passed on December 23, 1991. The important step that led to the independence of Slovenia was the December 1990 plebiscite. It was at this plebiscite that the citizens of Slovenia voted for a sovereign and independent state. A public survey called Slovenian Public Opinion (SPO) survey was taken by the government of Slovenia for the plebiscite. The plebiscite counted `YES voters' only those voters who attended and who voted for independence. Non-voters were counted as `NO voters' and `Don't Know' survey responses that could be tho

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40

Volinsky, Christopher T. "Bayesian model averaging for censored survival models /." Thesis, Connect to this title online; UW restricted, 1997. http://hdl.handle.net/1773/8944.

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41

Lee, Kyeong Eun. "Bayesian models for DNA microarray data analysis." Diss., Texas A&M University, 2005. http://hdl.handle.net/1969.1/2465.

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Selection of signi?cant genes via expression patterns is important in a microarray problem. Owing to small sample size and large number of variables (genes), the selection process can be unstable. This research proposes a hierarchical Bayesian model for gene (variable) selection. We employ latent variables in a regression setting and use a Bayesian mixture prior to perform the variable selection. Due to the binary nature of the data, the posterior distributions of the parameters are not in explicit form, and we need to use a combination of truncated sampling and Markov Chain Monte Carlo (MCMC)

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42

Langseth, Helge. "Bayesian networks with applications in reliability analysis." Doctoral thesis, Norwegian University of Science and Technology, Department of Mathematical Sciences, 2002. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-959.

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<p>A common goal of the papers in this thesis is to propose, formalize and exemplify the use of Bayesian networks as a modelling tool in reliability analysis. The papers span work in which Bayesian networks are merely used as a modelling tool (Paper I), work where models are specially designed to utilize the inference algorithms of Bayesian networks (Paper II and Paper III), and work where the focus has been on extending the applicability of Bayesian networks to very large domains (Paper IV and Paper V).</p><p><b>Paper I </b>is in this respect an application paper, where model building, estima

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43

Meng, Yu. "Bayesian Analysis of a Stochastic Volatility Model." Thesis, Uppsala University, Department of Mathematics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-119972.

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44

Ray, Shubhankar. "Nonparametric Bayesian analysis of some clustering problems." Texas A&M University, 2006. http://hdl.handle.net/1969.1/4251.

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Nonparametric Bayesian models have been researched extensively in the past 10 years following the work of Escobar and West (1995) on sampling schemes for Dirichlet processes. The infinite mixture representation of the Dirichlet process makes it useful for clustering problems where the number of clusters is unknown. We develop nonparametric Bayesian models for two different clustering problems, namely functional and graphical clustering. We propose a nonparametric Bayes wavelet model for clustering of functional or longitudinal data. The wavelet modelling is aimed at the resolution of global an

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45

Karuri, Stella. "Integration in Computer Experiments and Bayesian Analysis." Thesis, University of Waterloo, 2005. http://hdl.handle.net/10012/1187.

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Mathematical models are commonly used in science and industry to simulate complex physical processes. These models are implemented by computer codes which are often complex. For this reason, the codes are also expensive in terms of computation time, and this limits the number of simulations in an experiment. The codes are also deterministic, which means that output from a code has no measurement error. <br /><br /> One modelling approach in dealing with deterministic output from computer experiments is to assume that the output is composed of a drift component and systematic

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46

McCandless, Lawrence Cruikshank. "Bayesian propensity score analysis of observational data." Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/31420.

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Propensity scores analysis (PSA) involves regression adjustment for the estimated propensity scores, and the method can be used for estimating causal effects from observational data. However, confidence intervals for the treatment effect may be falsely precise because PSA ignores uncertainty in the estimated propensity scores. We propose Bayesian propensity score analysis (BPSA) for observational studies with a binary treatment, binary outcome and measured confounders. The method uses logistic regression models with the propensity score as a latent variable. The first regression models the rel

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47

Maimon, Geva. "A Bayesian spatial analysis of glass data /." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=82284.

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In criminal investigations involving glass evidence, refractive index (RI) is the property of glass most commonly used by forensic examiners to determine the association between control samples of glass obtained at the crime scene, and samples of glass found on a suspect. Previous studies have shown that an intrinsic variability of RI exists within a pane of float glass. In this thesis, we attempt to determine whether this variability is spatially determined or random in nature, the conclusion of which plays an important role in the statistical interpretation of glass evidence. We take

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48

Zeryos, Mihail. "Bayesian pursuit analysis and singular stochastic control." Thesis, Imperial College London, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.338932.

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49

Haro, Lopez Ruben Alejandro. "Data adaptive Bayesian analysis using distributional mixtures." Thesis, Imperial College London, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.299509.

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Choudrey, Rizwan A. "Variational methods for Bayesian independent component analysis." Thesis, University of Oxford, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.275566.

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