Special issue of TOMACS

March 9, 2011
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(This article was first published on Xi'an's Og » R, and kindly contributed to R-bloggers)

TOMACS (ACM Transactions on Modeling and Computer Simulation) is launching a call for paper submission. The special topic is Monte Carlo Methods in Statistics and Arnaud Doucet and myself are the special issue editors. Here are the details.:

Over the last two decades Monte Carlo methods have attracted much attention from statisticians as they provide enormous scope for realistic statistical modeling. This is a very active research field with recent developments including adaptive Markov chain Monte Carlo methods, population Monte Carlo methods and approximate Bayesian computation among others. The recent introduction of Graphics Processing Units shows also great promise and open new research
directions.

The purpose of this special issue of TOMACS is to propose a selection of high quality papers reporting the latest research covering the methodology and implementation of recent developments in Monte Carlo methodology for statistics. Topics include but are not limited to:

  • Markov chain Monte Carlo
  • Sequential Monte Carlo
  • Stochastic approximation
  • Approximate Bayesian computation and other approximations
  • Massive parallelization for high-dimensional problems

The submission deadline is October 30, 2011. The special issue should appear in early 2012. For the editorial policy, instructions to authors, and further details, please consult the ACM TOMACS Web page.

The submission process is electronic only. When submitting your paper, select the appropriate special issue, on Monte Carlo Methods in Statistics, and make sure that you carefully follow the instructions.

We are thus looking forwards your submissions!


Filed under: Books, R, Statistics, University life Tagged: ABC, adaptive MCMC methods, Association for Computer Machinery, MCMC, population Monte Carlo, TOMACS

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