# Posts Tagged ‘ slice sampling ’

## Andrew gone NUTS!

November 23, 2011
By

Matthew Hoffman and Andrew Gelman have posted a paper on arXiv entitled “The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo” and developing an improvement on the Hamiltonian Monte Carlo algorithm called NUTS (!). Here is the abstract: Hamiltonian Monte Carlo (HMC) is a Markov chain Monte Carlo (MCMC) algorithm that avoids the

## A slice of infinity

July 27, 2011
By

Peng Yu sent me an email about the conditions for convergence of a Gibbs sampler: The following statement mentions convergence. But I’m not familiar what the regularity condition is. “But it is necessary to have a finite probability of moving away from the current state at all times in order to satisfy the regularity conditions on which

## Slices and crumbs [arXiv:1011.4722]

November 29, 2010
By
$Slices and crumbs [arXiv:1011.4722]$

An interesting note was arXived a few days ago by Madeleine Thompson and Radford Neal. Beside the nice touch of mixing crumbs and slices, the neat idea is to have multiple-try proposals for simulating within a slice and to decrease the dimension of the simulation space at each try. This dimension diminution is achieved via

## Monte Carlo Statistical Methods third edition

September 23, 2010
By

Last week, George Casella and I worked around the clock on starting the third edition of Monte Carlo Statistical Methods by detailing the changes to make and designing the new table of contents. The new edition will not see a revolution in the presentation of the material but rather a more mature perspective on what

## Confusing slice sampler

May 18, 2010
By

Most embarrassingly, Liaosa Xu from Virginia Tech sent the following email almost a month ago and I forgot to reply: I have a question regarding your example 7.11 in your book Introducing Monte Carlo Methods with R.  To further decompose the uniform simulation by sampling a and b step by step, how you determine the