![A survey of [the 60's] Monte Carlo methods](http://xianblog.files.wordpress.com/2011/05/img_8170.jpg?w=450&h=337)
“The only good Monte Carlos are the dead Monte Carlos” (Trotter and Tukey, quoted by Halton) When I presented my history of MCM methods in Bristol two months ago, at the Julian Besag memorial, Christophe Andrieu mentioned a 1970 SIAM survey by John Halton on A retrospective and prospective survey of the Monte Carlo 
I received this email last week from Ian Langmore, a postdoc in Columbia: I’m looking for literature on a subject and can’t find it: I have a Metropolis sampler where the acceptance probability is evaluated with some error. This error is not simply error in evaluation of the target density. It occurs due to the 
Here is the poster presented at MCMSki III next week by Pierre Jacob about our joint paper on parallelisation: Filed under: R, Statistics, Travel Tagged: Adapski, MCMC, MCMSki, Metropolis-Hastings, Monte Carlo Statistical Methods, parallelisation, pos...
![Robust adaptive Metropolis algorithm [arXiv:10114381]](http://www.r-bloggers.com/wp-content/uploads/2010/11/am-adapt-student.jpg?w=102&h=117)
Matti Vihola has posted a new paper on arXiv about adaptive (random walk) Metropolis-Hastings algorithms. The update in the (lower diagonal) scale matrix is where is the current acceptance probability and the target acceptance rate; is the current random noise for the proposal, ; is a step size sequence decaying to zero. The spirit of 
With Pierre Jacob, my PhD student, and Murray Smith, from National Institute of Water and Atmospheric Research, Wellington, who actually started us on this project at the last and latest Valencia meeting, we have completed a paper on using parallel computing in independent Metropolis-Hastings algorithms. The paper is arXived and the abstract goes as follows: 
A new Metropolis-Hastings algorithm that I would call “universal” was posted by Somak Dutta yesterday on arXiv. Multiplicative random walk Metropolis-Hastings on the real line contains a different Metropolis-Hastings algorithm called the random dive. The proposed new value x’ given the current value x is defined by when is a random variable on . Thus, 
![Vanilla Rao-Blackwellisation [re]revised](http://l.wordpress.com/latex.php?latex=%5Cleft%7C+%5Cbegin%7Bmatrix%7D+%5Ctau+%26%5Ctext%7Bmedian%7D+%26%5Ctext%7Bmean+%7D%26q_%7B.8%7D+%26q_%7B.9%7D+%26%5Ctext%7Btime%7D%5C%5C+0.25+%260.0+%268.85+%264.9+%2613+%264.2%5C%5C+0.50+%260.0+%266.76+%264+%2611+%262.25%5C%5C+1.00+%260.25+%266.15+%264+%2610+%262.5%5C%5C+2.00+%260.20+%265.90+%263.5+%268.5+%264.5%5C%5C%5Cend%7Bmatrix%7D+%5Cright%7C&bg=000000&fg=B0B0B0&s=0)
Although the revision is quite minor, it took us two months to complete from the time I received the news in the Atlanta airport lounge… The vanilla Rao-Blackwellisation paper with Randal Douc has thus been resubmitted to the Annals of Statistics. And rearXived. The only significant change is the inclusion of two tables detailing computing 
Glancing perchance at the back of my Amstat News, I was intrigued by the SAS advertisement Bayesian Methods Specify Bayesian analysis for ANOVA, logistic regression, Poisson regression, accelerated failure time models and Cox regression through the GENMOD, LIFEREG and PHREG procedures. Analyze a wider variety of models with the MCMC procedure, a general purpose Bayesian 
A few months ago, Latuszyński, Kosmidis, Papaspiliopoulos and Roberts arXived a paper I should have noticed earlier as its topic is very much related to our paper with Randal Douc on the vanilla Rao-Blackwellisation scheme. It is motivated by the Bernoulli factory problem, which aims at (unbiasedly) estimating f(p) from an iid sequence of Bernoulli 
The vanilla Rao-Blackwellisation paper with Randal Douc that had been resubmitted to the Annals of Statistics is now back for a revision, with quite encouraging comments: The paper has been reviewed by two referees both of whom comment on the clear exposition and the novelty of the results. Both referees point to the empirical results 
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
