Bayesian Models for Repeated Measures Data Using Markov Chain Monte Carlo Methods
Bayesian models for repeated measures data are fitted to three different data an analysis projects. Markov Chain Monte Carlo (MCMC) methodology is applied to each case with Gibbs sampling and / or an adaptive Metropolis-Hastings (MH ) algorithm used to simulate the posterior distribution of paramete...
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| Format: | Others |
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DigitalCommons@USU
2016
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| Online Access: | https://digitalcommons.usu.edu/etd/6997 https://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=8097&context=etd |