Flowchart of Metropolis-Hastings (M-H) algorithm for the parameter estimation using the Markov Chain Monte Carlo (MCMC) approach Code Overview We explore three different probability density functions, ...

A proper choice of a proposal distribution for Markov chain Monte Carlo methods, for example for the Metropolis-Hastings algorithm, is well known to be a crucial factor for the convergence of the ...

This article studies the efficacy of the Metropolis algorithm for the minimum-weight codeword problem. The input is a linear code C given by its generator matrix and our task is to compute a nonzero ...

The Metropolis-Hastings algorithm is a popular method for generating samples from complex posterior distributions in Bayesian statistics. It is based on the idea of constructing a Markov chain ...

Simulating from distributions with intractable normalizing constants has been a long-standing problem in machine learning. In this letter, we propose a new algorithm, the Monte Carlo ...

This paper considers the problem of scaling the proposal distribution of a multidimensional random walk Metropolis algorithm in order to maximize the efficiency of the algorithm. The main result is a ...