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lse4y
Bayesian Inference
Comparison with Frequentist approaches. Implementation: Asymptotic approximations (Laplace approximation, Variational Bayes, Monte Carlo methods), Markov Chain Monte Carlo (MCMC) simulation (Gibbs ...
University of Bristol2y
MCMC estimation in MLwiN
Markov Chain Monte Carlo (MCMC) methods allow Bayesian models to be fitted, where prior distributions for the model parameters are specified. By default MLwiN sets diffuse priors which can be used to ...
JSTOR Daily6y
An application of MCMC simulation in mortality projection for populations with limited data
30, JANUARY - JUNE 2014 An application of MCMC simulation in mor... In this paper, we investigate the use of Bayesian modeling and Markov chain Monte Carlo (MCMC) simulation, via the software WinBUGS, ...
Concordia University6y
Master Thesis Defense - August 22, 2018: Bayesian Learning of Asymmetric Gaussian-Based Statistical Models Using Markov Chain Monte Carlo Techniques
The Bayesian learning framework is developed by adopting sampling- based Markov chain Monte Carlo (MCMC) methodology. More precisely, the fundamental learning algorithm is a hybrid Metropolis-Hastings ...