Global ETD Search
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Showing 1 to 4 of 4 for “"adaptive MCMC"”.
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Ergodicity of Adaptive MCMC and its Applications
Markov chain Monte Carlo algorithms (MCMC) and Adaptive Markov chain Monte Carlo algorithms (AMCMC) are most important methods of approximately sampling from complicated probability distributions and are widely used in statistics, computer science, chemistry, physics, etc. The core problem to use …
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Bayesian inference of chemical reaction networks
… proposals for Markov chain Monte Carlo (MCMC). We then introduce a sensitivity-based determination of move types which, when combined with the network-aware proposals, yields further sampling efficiency. These algorithms are tested on example problems with up to 1000 plausible models. We …
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Sequential methodology and applications in sports rating
… and application of sequential methods. A new adaptive sequential Monte Carlo (SMC) methodology is presented. By incorporating adaptive Markov chain Monte Carlo (MCMC) moves into the SMC update, it is possible to utilise the heuristic, computational and theoretical advantages of SMC to make …
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Slice Sampling with Multivariate Steps
Markov chain Monte Carlo (MCMC) allows statisticians to sample from a wide variety of multidimensional probability distributions. Unfortunately, MCMC is often difficult to use when components of the target distribution are highly correlated or have disparate variances. This thesis presents three …