Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 38 for “"Metropolis-Hastings"”.
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Modeling spatial patterns of mixed-species Appalachian forests with Gibbs point processes
… (MCMC) methods; in particular, a reversible-jump Metropolis-Hastings algorithm with birth, death, and shift proposals was utilized. Parameters for the models were estimated by a Bayesian inferential procedure that utilizes MCMC methods to draw samples from the Gibbs posterior density. Two …
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Modeling Transition Probabilities for Loan States Using a Bayesian Hierarchical Model
… probabilities are estimated using MCMC and the Metropolis-Hastings algorithm.
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Bayesian Interaction and Association Networks From Multiple Replicates of Sparse Time-Course Data
… Bayesian inference in conjunction with the Metropolis-Hastings algorithm. The Bayesian posterior probability is computed for two distinct cases. One case assumes the replicates are independent events, the other assumes the replicates are not independent events (using a hierarchical …
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An Adaptive Bayesian Approach to Bernoulli-Response Clinical Trials
… chain Monte Carlo algorithm. An order restricted Metropolis-Hastings algorithm is implemented to account for these limitations. Modeling clinical trials in a Bayesian framework allows the experiment to be adaptive. In this adaptive design batches of subjects are assigned to doses based on the …
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Formally justified and modular Bayesian inference for probabilistic programs
… basic building blocks corresponding to vanilla Metropolis-Hastings and Sequential Monte Carlo we can implement more advanced algorithms known in the literature, such as Resample-Move Sequential Monte Carlo, Particle Marginal Metropolis-Hastings, and Sequential Monte Carlo squared. These …
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SCL: A Lattice-Based Approach to Infer Three-Dimensional Chromosome Structures from Single-Cell Hi-C Data
… and stored in a 3D cubic lattice. Metropolis-Hastings simulation and simulated annealing are used to simulate the structure and minimize the loss function. We evaluated the SCL-inferred 3D structures (at both 500 kb and 50 kb resolutions) using multiple criteria and compared them …
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Bayesian Inference for Nonlinear Dynamical Systems : Applications and Software Implementation
… the Auxiliary Particle Filter and the Metropolis Hastings Improved Particle Smoother, to handle mixed linear/nonlinear models using Rao Blackwellized methods. This work was motivated by the desire to have a coherent set of methods and model-classes in the software framework so that all …
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Data conditioned simulation and inference
… Computation (dcABC) and the grouped independence Metropolis-Hastings (GIMH) algorithm. The methodology is demonstrated through three examples, a homogeneous mixing SIR epidemic model, a time inhomogeneous Markov chain model and the stochastic Ricker model. The implementation of the methodology is …
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Graphical methods in prior elicitation.
… method, we propose a variation on the Metropolis-Hastings algorithm that provides support for the underlying stochastic scheme in the second of the two elicitation strategies. We apply the methods to data models that are commonly employed in practice, such as Bernoulli, Poisson, and …
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Relative Role of Uncertainty for Predictions of Future Southeastern U.S. Pine Carbon Cycling
… We applied a data assimilation using Metropolis-Hastings Markov Chain Monte Carlo to fuse diverse datasets with the Physiological Principles Predicting Growth model. The spatially and temporally diverse data sets allowed for novel constraints on ecosystem model parameters and allowed …
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COMPARING THREE ESTIMATION METHODS FOR THE THREE-PARAMETER LOGISTIC IRT MODEL
… chain Monte Carlo simulation techniques, and the Metropolis-Hastings Robbin-Monro estimation. With each technique, a prior can be specified to reflect prior belief on each model parameter. Previous studies evaluating the fully Bayesian estimation procedure for this model suggests that the model …
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Investigating the performance of process-observation-error-estimator and robust estimators in surplus production model: a simulation study
… This study used Bayesian method, revised Metropolis Hastings within Gibbs sampling algorithm (MHGS) that was previously used to solve POE_N (Millar and Meyer, 2000), developed the MHGS for the other estimators, and developed the methodologies which enabled all the estimators to deal with …
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Improving Computation for Hierarchical Bayesian Spatial Gaussian Mixture Models with Application to the Analysis of THz image of Breast Tumor
… inference. In particular, we discuss the Metropolis-Hastings and conjugate Gibbs algorithms and explore the computational underpinnings of these methods. The second chapter discusses how to incorporate spatial autocorrelation in linear a regression model with an emphasis on the …
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Curve sampling and geometric conditional simulation
… We create a curve sampling algorithm using the Metropolis-Hastings Markov chain Monte Carlo (MCMC) framework. With this method, samples from a target distribution [pi] (which can be evaluated but not sampled from directly) are generated by creating a Markov chain whose stationary distribution is …
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Firms in Integrated Urban Models: Agglomeration Economies and the Dynamics of Employment Size Decisions
… of the hyperparameters using a nested Gibbs and Metropolis-Hastings sampling algorithm. With a panel micro-dataset of businesses in the Greater Boston Area, I apply the model to explore the heterogeneous impacts of agglomeration economies for manufacturing, professional services, and food and …
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Efficient distributed medium access algorithm
… topology. Our solution blends the classical Metropolis-Hastings sampling mechanism with insights obtained from analysis of time-varying queueing dynamics. Methodically, our theoretical framework is applicable to design of efficient distributed scheduling algorithms for a wide class of …
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Estimability of natural mortality within a statistical catch-at-age model: a framework and simulation study based on Gulf of Mexico red snapper
… parameters, including natural mortality, through Metropolis-Hastings algorithms from Gulf of Mexico red-snapper Lutjanus campechanus data. I investigated the influences of assumptions regarding model configuration of natural mortality and selectivity-at-age parameters by comparing multiple models. …
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Models for Data Analysis in Accelerated Reliability Growth
… to each model parameter, developing a sequential Metropolis-Hastings procedure to sample the posterior distribution of the model parameters, and deriving closed form expressions to aggregate component reliability information to assess the reliability of the system. The second group of methods …
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Three essays on econometrics
… that geometric ergodicity is satisfied under Metropolis Hastings chains with quasi-posterior for the whole class of extremum estimators. The third chapter considers fixed effects estimation and inference in nonlinear panel data models with random coefficients and endogenous regressors. The …
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Machine Learning and Variational Algorithms for Lattice Field Theory
… used as proposals in an asymptotically exact Metropolis-Hastings Markov chain. We also construct models that flexibly parameterize families of distributions while capturing symmetries of interest, including translational and gauge symmetries. By variationally optimizing the distribution …
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