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Relevant bibliographies by topics / Bayesian design of Experiments / Dissertations / Theses

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Dissertations / Theses on the topic 'Bayesian design of Experiments'

Author: Grafiati

Published: 4 June 2021

Last updated: 15 February 2022

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1

Hu, Kenneth T. "Bayesian design of experiments for complex chemical systems." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/65760.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2011.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 317-322).<br>Engineering design work relies on the ability to predict system performance. A great deal of effort is spent producing models that incorporate knowledge of the underlying physics and chemistry in order to understand the relationship between system inputs and responses. Although models can provide great insight into the behavior of the system, actual design decisions cannot be made based on predictions alone

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2

Valks, Pamela. "Bayesian decision theoretic approach to experimental design with application to usability experiments." Thesis, University of Sunderland, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.414851.

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This thesis looks at the practicality of applying a Bayesian Decision Theoretic approach to the design of HCI usability experiments. It looks at the particular issues involved in following the Bayesian experimental design framework of developing a stochastic model, eliciting priors and utility functions and choosing the option with the maximum expected utility. HeI usability testing may involve user and analyst experimentation and various courses of action may be employed using either one or both types of experiment. The thesis shows that HeI usability experiments can be represented diagrammat

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3

Kapoor, Deepa. "Bayesian design and analysis of small multifactor industrial experiments." Thesis, Queen Mary, University of London, 2011. http://qmro.qmul.ac.uk/xmlui/handle/123456789/1270.

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Unreplicated two level fractional factorial designs are a common type of experimental design used in the early stages of industrial experimentation. They allow considerable information about the e ects of several factors on the response to be obtained with a relatively small number of runs. The aim of this thesis is to improve the guidance available to experimenters in choosing a good design and analysing data. This is particularly important when there is commercial pressure to minimise the size of the experiment. A design is usually chosen based on optimality, either in terms of a variance cr

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4

Bahg, Giwon. "Adaptive Design Optimization in Functional MRI Experiments." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1531836392551605.

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5

Aloef, Fatimah. "Bayesian design of discrete choice experiments for valuing health state utilities." Thesis, University of Sheffield, 2015. http://etheses.whiterose.ac.uk/9446/.

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This thesis concerns about using discrete choice experiment for valuing health state utilities within the QALY framework. Therefore, it discusses the main issues with generating choice design for valuing health state utilities, and then presents an efficient methodology to construct an optimal choice design for valuing health state utilities using the most recent theoretical development in Bayesian optimal design literature. The use of the new design algorithm and the effect of the prior in the Bayesian design are demonstrated in this thesis by constructing Bayesian choice design for asthma qu

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6

Rose, Andrew David. "Bayesian Experimental Design for Model Discrimination." Thesis, University of Southampton, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.494378.

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7

Feng, Chunyao Seaman John Weldon. "Bayesian evaluation of surrogate endpoints." Waco, Tex. : Baylor University, 2006. http://hdl.handle.net/2104/4187.

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8

Tseng, Shih-Hsien. "Bayesian and Semi-Bayesian regression applied to manufacturing wooden products." The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1199240473.

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9

Philipson, Peter M. "Exact Bayesian experimental design for limiting dilution assays." Thesis, University of Newcastle Upon Tyne, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.420016.

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10

Huan, Xun. "Accelerated Bayesian experimental design for chemical kinetic models." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/59678.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2010.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 129-136).<br>The optimal selection of experimental conditions is essential in maximizing the value of data for inference and prediction, particularly in situations where experiments are time-consuming and expensive to conduct. A general Bayesian framework for optimal experimental design with nonlinear simulation-based models is proposed. The formulation accounts for uncertainty in model parameters, observables, an

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11

Huan, Xun. "Numerical approaches for sequential Bayesian optimal experimental design." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/101442.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2015.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 175-186).<br>Experimental data play a crucial role in developing and refining models of physical systems. Some experiments can be more valuable than others, however. Well-chosen experiments can save substantial resources, and hence optimal

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12

Lin, Hefang. "One-Stage and Bayesian Two-Stage Optimal Designs for Mixture Models." Diss., Virginia Tech, 1999. http://hdl.handle.net/10919/30224.

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In this research, Bayesian two-stage D-D optimal designs for mixture experiments with or without process variables under model uncertainty are developed. A Bayesian optimality criterion is used in the first stage to minimize the determinant of the posterior variances of the parameters. The second stage design is then generated according to an optimality procedure that collaborates with the improved model from first stage data. Our results show that the Bayesian two-stage D-D optimal design is more efficient than both the Bayesian one-stage D-optimal design and the non-Bayesian one-stage D-o

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13

Aggarwal, Raghav. "Demonstration of Bayesian inference and Bayesian experimental design in a model film/substrate inference problem." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/104292.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 49-52).<br>In this thesis, we implement Bayesian inference and Bayesian experiment design in a model materials science problem. We demonstrate that by observing the behavior of a film deposited on a substrate, certain features of the substrate may be inferred, with quantified uncertainty. We show that Bayesian experimental design can be used to design efficient experiments. The substrate in this model problem is

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14

Shaw, Simon Charles. "Simplifying Bayesian experimental design for multivariate partially exchangeable systems." Thesis, Durham University, 2000. http://etheses.dur.ac.uk/4525/.

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We adopt a Bayes linear approach to tackle design problems with many variables cross-classified in many ways. We investigate designs where we wish to sample individuals belonging to different groups, exploiting the powerful properties of the adjustment of infinitely second-order exchangeable vectors. The types of information we gain by sampling are identified with the orthogonal canonical directions. We show how we may express these directions in terms of the different factors of the model. This allows us to solve a series of lower dimensional problems, through which we may identify the differ

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15

Feng, Chi S. M. Massachusetts Institute of Technology. "Optimal Bayesian experimental design in the presence of model error." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/97790.

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Thesis: S.M., Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2015.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 87-90).<br>The optimal selection of experimental conditions is essential to maximizing the value of data for inference and prediction. We propose an information theoretic framework and algorithms for robust optimal experimental design with simulation-based models, with the goal of maximizing information gain in targeted subsets of model parameters, particularly in situations where experiments are costl

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16

Marmin, Sebastien. "Warping and sampling approaches to non-stationary gaussian process modelling." Thesis, Ecole centrale de Marseille, 2017. http://www.theses.fr/2017ECDM0007/document.

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Cette thèse traite de l'approximation de fonctions coûteuses à évaluer et présentant un comportement hétérogène selon les régions du domaine d'entrées. Dans beaucoup d’applications industrielles comme celles issues de la sûreté nucléaire et menées à l’IRSN, les codes de calcul de simulation physique ont des coûts numériques importants et leurs réponses sont alors approchées par un modèle. Les modèles par processus gaussien (PG) sont répandus pour construire des plans d'expériences au budget d'évaluations limité. Alors que les méthodes de planifications standard explorent le domaine en partant

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17

Wilson, Kevin James. "Belief representation for counts in Bayesian inference and experimental design." Thesis, University of Newcastle Upon Tyne, 2011. http://hdl.handle.net/10443/1217.

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Bayesian inference for such things as collections of related binomial or Poisson distributions typically involves rather indirect prior specifications and intensive numerical methods (usually Markov chain Monte Carlo) for posterior evaluations. As well as requiring some rather unnatural prior judgements this creates practical difficulties in problems such as experimental design. This thesis investigates some possible alternative approaches to this problem with the aims of making prior specification more feasible and making the calculations necessary for updating beliefs or for designing experi

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18

Li, Fengyi S. M. Massachusetts Institute of Technology. "A combinatorial approach to goal-oriented optimal Bayesian experimental design." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122376.

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This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2019<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 83-87).<br>Optimal experimental design plays an important role in science and engineering. In many situations, we have many observations but only few of them can be selected due to limited resources. We then need to decide which ones to select

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19

Ozbozkurt, Pelin. "Bayesian Inference In Anova Models." Phd thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/3/12611532/index.pdf.

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Estimation of location and scale parameters from a random sample of size n is of paramount importance in Statistics. An estimator is called fully efficient if it attains the Cramer-Rao minimum variance bound besides being unbiased. The method that yields such estimators, at any rate for large n, is the method of modified maximum likelihood estimation. Apparently, such estimators cannot be made more efficient by using sample based classical methods. That makes room for Bayesian method of estimation which engages prior distributions and likelihood functions. A formal combination of the prior kno

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20

Tan, Matthias H. Y. "Contributions to quality improvement methodologies and computer experiments." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/48936.

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This dissertation presents novel methodologies for five problem areas in modern quality improvement and computer experiments, i.e., selective assembly, robust design with computer experiments, multivariate quality control, model selection for split plot experiments, and construction of minimax designs. Selective assembly has traditionally been used to achieve tight specifications on the clearance of two mating parts. Chapter 1 proposes generalizations of the selective assembly method to assemblies with any number of components and any assembly response function, called generalized selecti

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21

Mowll, Deborah. "Bayesian experimental design and its application to engine research and development." Thesis, University of Sussex, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340774.

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22

Zhang, Xiao. "Experiment Design and Reliability Analysis of Accelerated Degradation Test." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1378197282.

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23

Guest, Thomas. "Nonlinear design of geophysical surveys and processing strategies." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/4903.

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The principal aim of all scientific experiments is to infer knowledge about a set of parameters of interest through the process of data collection and analysis. In the geosciences, large sums of money are spent on the data analysis stage but much less attention is focussed on the data collection stage. Statistical experimental design (SED), a mature field of statistics, uses mathematically rigorous methods to optimise the data collection stage so as to maximise the amount of information recorded about the parameters of interest. The uptake of SED methods in geophysics has been limited as the m

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24

Aerts, Xing Qin. "Time Series Data Analysis of Single Subject Experimental Designs Using Bayesian Estimation." Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc804882/.

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This study presents a set of data analysis approaches for single subject designs (SSDs). The primary purpose is to establish a series of statistical models to supplement visual analysis in single subject research using Bayesian estimation. Linear modeling approach has been used to study level and trend changes. I propose an alternate approach that treats the phase change-point between the baseline and intervention conditions as an unknown parameter. Similar to some existing approaches, the models take into account changes in slopes and intercepts in the presence of serial dependency. The Bayes

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25

Huffman, Jennifer Wade. "Optimal Experimental Design for Poisson Impaired Reproduction Studies." Diss., Virginia Tech, 1998. http://hdl.handle.net/10919/30751.

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Impaired reproduction studies with Poisson responses are among a growing class of toxicity studies in the biological and medical realm. In recent years, little effort has been focused on the development of efficient experimental designs for impaired reproduction studies. This research concentrates on two areas: 1) the use of Bayesian techniques to make single regressor designs robust to parameter misspecification and 2) the extension of design optimality methods to the k-regressor model. The standard Poisson model with log link is used. Bayesian designs with priors on the parameters are exp

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26

Murphy, Jonathan Rodgers. "A robust multi-objective statistical improvement approach to electric power portfolio selection." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/45946.

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Motivated by an electric power portfolio selection problem, a sampling method is developed for simulation-based robust design that builds on existing multi-objective statistical improvement methods. It uses a Bayesian surrogate model regressed on both design and noise variables, and makes use of methods for estimating epistemic model uncertainty in environmental uncertainty metrics. Regions of the design space are sequentially sampled in a manner that balances exploration of unknown designs and exploitation of designs thought to be Pareto optimal, while regions of the noise space are sampled t

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27

Azadi, Nammam Ali. "A Bayesian approach to modeling excitability and experimental design of binary response single motor units." Thesis, Lancaster University, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.654553.

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Threshold tacking studies involve studying the excitability of a motor unit (MU), the fundamental physiological unit of our motor system. The excitability property of a MU can be parameterised by its threshold and a range of stimulus intensities over which a MU shows a stochastic behaviour. Statistical methods are seldom used for this purpose and judgments are subjective. Two main interests in threshold tracking studies are i) A novel approach that makes it possible to obtain reliable estimation of the MU's excitability parameters, and ii) The efficient use of the available resources. The aim

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28

Mazur, Johanna [Verfasser], and Stefan [Akademischer Betreuer] Körkel. "Bayesian Inference of Gene Regulatory Networks : From Parameter Estimation to Experimental Design / Johanna Mazur ; Betreuer: Stefan Körkel." Heidelberg : Universitätsbibliothek Heidelberg, 2012. http://d-nb.info/1179786017/34.

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29

Nelson, Jonathan David. "Optimal experimental design as a theory of perceptual and cognitive information acquisition /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2005. http://wwwlib.umi.com/cr/ucsd/fullcit?p3191765.

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30

Toman, Blaza. "Bayesian optimal experimental design for the comparison of treatment with a control in the analysis of variance setting /." The Ohio State University, 1987. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487330761216343.

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31

Lima, Luis Gustavo Guedes Bessa. "Planejamento de experimentos bayesianos: aplicações em experimentos na presença de tendências lineares." Universidade Federal de São Carlos, 2007. https://repositorio.ufscar.br/handle/ufscar/4502.

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Made available in DSpace on 2016-06-02T20:05:58Z (GMT). No. of bitstreams: 1 DissLGGBL.pdf: 694668 bytes, checksum: fbe25c1e4093e12425b0a024c8a95456 (MD5) Previous issue date: 2007-01-11<br>Financiadora de Estudos e Projetos<br>We present a general introduction in the construction of experimental design, spe- cially a general factorial design and factorial design 2k and some Bayesian criteria in the construction of experimental design. In practice, usually the researcher can have a priori knowledge of specialists for estimated quantities from an experiment. The use of Bayesian methods can ta

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32

Rocha, Everton Batista da. "Modelos não-lineares para dados longitudinais provenientes de experimentos em blocos casualizados abordagem bayesiana." Universidade de São Paulo, 2011. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-09022011-154221/.

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Dados consistindo de medidas repetidas tomadas em um mesmo indivíduo são muito comuns na agricultura e biologia. A modelagem de dados desta natureza usualmente envolve a caracterização da relação entre medidas repetidas e covariáveis. Em muitas aplicações, a relação proposta entre as medidas repetidas tem um comportamento não-linear nos parâmetros desconhecidos de interesse. Por exemplo, em estudo de crescimento de arvores, geralmente o comportamento da variável resposta e melhor descrito por um modelo não-linear nos parâmetros porque estes modelos caracterizam melhor a realidade dos fenômenos

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33

Alharthi, Adel Aifan. "An integration of Lean Six Sigma and health and safety management system in Saudi Broadcasting Corporation." Thesis, Brunel University, 2015. http://bura.brunel.ac.uk/handle/2438/13781.

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Lean Six Sigma is a method used to improve the quality and efficiency of processes by reducing variation and eliminating wastes (non-value added activities) in an organisation. The concept of combining the principles and tools of Lean Enterprise and Six Sigma has been discussed in the literature. The majority of Lean Six Sigma applications in private industry have focused primarily on manufacturing applications. The literature has not provided a framework for implementing Lean Six Sigma programmes in non-manufacturing or transactional processes like those in the Entertainment Media industry. T

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34

Taslim, Cenny. "Multi-Stage Experimental Planning and Analysis for Forward-Inverse Regression Applied to Genetic Network Modeling." The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1213286112.

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35

Zheng, Ning. "Discovering interpretable topics in free-style text diagnostics, rare topics, and topic supervision /." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1199237529.

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36

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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37

Sillanpää, Mikko. "Bayesian QTL mapping in inbred and outbred experimental designs." Helsinki : University of Helsinki, 2000. http://ethesis.helsinki.fi/julkaisut/mat/rolfn/vk/sillanpaa/.

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38

Lin, Xiaoyan. "Bayesian hierarchical models for the recognition-memory experiments." Diss., Columbia, Mo. : University of Missouri-Columbia, 2008. http://hdl.handle.net/10355/6047.

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Thesis (Ph. D.)--University of Missouri-Columbia, 2008.<br>The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on August 3, 2009) Vita. Includes bibliographical references.

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39

Espinosa, Valeria. "A Bayesian Perspective on Factorial Experiments Using Potential Outcomes." Thesis, Harvard University, 2013. http://dissertations.umi.com/gsas.harvard:11245.

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Factorial designs have been widely used in many scientific and industrial settings, where it is important to distinguish "active'' or real factorial effects from "inactive" or noise factorial effects used to estimate residual or "error" terms. We propose a new approach to screen for active factorial effects from such experiments that utilizes the potential outcomes framework and is based on sequential posterior predictive model checks. One advantage of the proposed method lies in its ability to broaden the standard definition of active effects and to link their definition to the population of

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40

Chen, Hao. "Bayesian prediction and inference in analysis of computer experiments." Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/44887.

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Gaussian Processes (GPs) are commonly used in the analysis of data from a computer experiment. Ideally, the analysis will provide accurate predictions with correct coverage probabilities of credible intervals. A Bayesian method can, in principle, capture all sources of uncertainty and hence give valid inference. Several implementations are available in the literature, differing in choice of priors, etc. In this thesis, we first review three popular Bayesian methods in the analysis of computer experiments. Two prediction criteria are proposed to measure both the prediction accuracy and the pre

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Blondet, Gaëtan. "Système à base de connaissances pour le processus de plan d'expériences numériques." Thesis, Compiègne, 2017. http://www.theses.fr/2017COMP2363/document.

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Le besoin de compétitivité des entreprises, dans un contexte économique mondialisé, repose sur l'amélioration de la qualité des produits et la réduction des coûts et du temps de mise sur le marché. Pour atteindre ces objectifs, la simulation numérique est couramment utilisée pour la conception de produits complexes et mobilise des expertises diverses. Les Plans d'Expériences Numériques (PEN) sont de plus en plus utilisés pour simuler les variabilités des propriétés et de l’environnement du produit. Un processus de PEN apporte des méthodes de planification et d'analyse d'un ensemble de simulati

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Vaidyanathan, Sivaranjani. "Bayesian Models for Computer Model Calibration and Prediction." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1435527468.

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Vieira, Afrânio Márcio Corrêa. "Modelagem simultânea de média e dispersão e aplicações na pesquisa agronômica." Universidade de São Paulo, 2009. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-10032009-082556/.

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Diversos delineamentos experimentais que são aplicados correntemente tomam como base experimentos agronômicos. Esses dados experimentais são, geralmente, analisados usando-se modelos que consideram uma variância residual constante (ou homogênea), como pressuposto inicial. Entretanto, esta pressuposição mostra-se relativamente forte quando se está diante de situações para as quais fatores ambientais ou externos exercem considerável influência nas medidas experimentais. Neste trabalho, são estudados modelos para a média e a variância, simultaneamente, com a variância estruturada de duas formas:

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44

Ruder, Joshua Austin. "Experiments on system level design." Thesis, Montana State University, 2006. http://etd.lib.montana.edu/etd/2006/ruder/RuderJ0806.pdf.

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Khan, A. Z. "Optimal design of pharmacokinetic experiments." Thesis, University of Manchester, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.377718.

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46

Atherton, Juli. "Bayesian optimal design for changepoint problems." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=102954.

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We consider optimal design for changepoint problems with particular attention paid to situations where the only possible change is in the mean. Optimal design for changepoint problems has only been addressed in an unpublished doctoral thesis, and in only one journal article, which was in a frequentist setting. The simplest situation we consider is that of a stochastic process that may undergo a, change at an unknown instant in some interval. The experimenter can take n measurements and is faced with one or more of the following optimal design problems: Where should these n observations be take

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Bullock, John G. "Experiments on partisanship and public opinion : party cues, false beliefs, and Bayesian updating /." May be available electronically:, 2007. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

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48

Gupta, Abhishek. "Robust design using sequential computer experiments." Thesis, Texas A&M University, 2004. http://hdl.handle.net/1969.1/492.

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Modern engineering design tends to use computer simulations such as Finite Element Analysis (FEA) to replace physical experiments when evaluating a quality response, e.g., the stress level in a phone packaging process. The use of computer models has certain advantages over running physical experiments, such as being cost effective, easy to try out different design alternatives, and having greater impact on product design. However, due to the complexity of FEA codes, it could be computationally expensive to calculate the quality response function over a large number of combinations of design

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Emmett, Marta. "Design of experiments with multivariate response." Thesis, University of Sheffield, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.531108.

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陳令由 and Ling-yau Chan. "Optimal design for experiments with mixtures." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1986. http://hub.hku.hk/bib/B31230799.

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