Markov Chain Monte Carlo

MCMC,Markov Chain Monte Carlo,Markov Chains Monte Carlo

Markov Chain Monte Carlo - MCMC
Publications: 7,072| Citation Count: 75,082
Stemming Variations: Markov Chains Monte Carlo
Cumulative Annual
    • Markov chain Monte Carlo (McMC) simulation is a popular computational tool for making inferences from complex, high-dimensional probability densities. Given a particular target density , the idea behind this technique is to simulate a Markov chain that has as its stationary distribution...


    • Markov chain Monte Carlo (MCMC) is a popular class of algorithms to sample from a complex distribution. A key issue in the design of MCMC algorithms is to improve the proposal mechanism and the mixing behaviour. This has led some authors to propose the use of a population of MCMC chains, while others go even further by integrating techniques from evolutionary computation (EC) into the MCMC framework...

    Madalina M. Druganet al. Evolutionary Markov Chain Monte Carlo

    • Markov chain Monte Carlo (MCMC) is a methodology that is gaining widespread use in the phylogenetics community and is central to phylogenetic software packages such as MrBayes. An important issue for users of MCMC methods is how to select appropriate values for adjustable parameters such as the length of the Markov chain or chains, the sampling density, the proposal mechanism, and, if Metropolis-coupled MCMC is being used, the number of heated chains and their temperatures...

    ROBERT G. BEIKOet al. Searching for Convergence in Phylogenetic Markov Chain Monte Carlo

    • Markov Chain Monte Carlo (MCMC) is a computer-intensive statistical tool that has received considerable attention over the past few years. Using MCMC theory, it is often quite simple to write efficient algorithms for sampling from extremely complicated target distributions; thus, it is not difficult to understand why these techniques have found important applications in a vast number of different areas. Although the literature on MCMC methods is growing rapidly, the excellent book by Gilks, Richardson and Spiegelhalter (1996) provides a good starting point for the interested reader...

    Håkan Anderssonet al. Markov Chain Monte Carlo

    • Markov chain Monte Carlo (MCMC) is an important computational technique for generating samples from non-standard probability distributions. A major challenge in the design of practical MCMC samplers is to achieve efficient convergence and mixing properties...

    Jonathan M. Keithet al. Adaptive independence samplers

Sort by: