R program for a metropolis-hastings based MCMC sampler using a multivariate-normal proposal distribution.
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Updated
Dec 9, 2021 - HTML
R program for a metropolis-hastings based MCMC sampler using a multivariate-normal proposal distribution.
In this repository, software applications in simulation and visualization for various applications are presented with interesting examples.
Bayesian logistic regression using Metropolis-Hastings sampling techniques in R
Decrypt a message with the Metropolis-Hasting Algorithm
An implementation of the BUGS example LSAT: item response (http://www.openbugs.net/Examples/Lsat.html) on R. Parameters for the Rasch model are estimated using Maximum Marginal Likelihood as well as Bayesian Inference using jags and an implementation of Metropolis on R.
The programming part for the second assignment of the course DSC 531 - Statistical Simulations and Data Analysis of the University of Cyprus MSc in Data Science programme
Homeworks from the Bayesian Statistics course of accademic year 2018/2019 at University of Trieste
IRT models using various Bayesian methods
Implementing MCMC sampling from scratch in R for various Bayesian models
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