[Pomp-commits] r276 - www/content

[noreply at r-forge.r-project.org]

Author: kingaa
Date: 2010-06-30 21:30:43 +0200 (Wed, 30 Jun 2010)
New Revision: 276

Modified:
   www/content/pomp.bib
   www/content/refs.htm
   www/content/refs.tex
Log:
- add PMCMC method from Andrieu et al. (2010)


Modified: www/content/pomp.bib
===================================================================
--- www/content/pomp.bib	2010-06-30 19:30:22 UTC (rev 275)
+++ www/content/pomp.bib	2010-06-30 19:30:43 UTC (rev 276)
@@ -1,6 +1,34 @@
 % This file was created with JabRef 2.6.
 % Encoding: ISO8859_1
 
+ at ARTICLE{Andrieu2010,
+  author = {Andrieu, Christophe and Doucet, Arnaud and Holenstein, Roman},
+  title = {Particle Markov chain Monte Carlo methods},
+  journal = {Journal of the Royal Statistical Society, Series B},
+  year = {2010},
+  volume = {72},
+  pages = {269--342},
+  number = {3},
+  abstract = {Markov chain Monte Carlo and sequential Monte Carlo methods have emerged
+	as the two main tools to sample from high dimensional probability
+	distributions. Although asymptotic convergence of Markov chain Monte
+	Carlo algorithms is ensured under weak assumptions, the performance
+	of these algorithms is unreliable when the proposal distributions
+	that are used to explore the space are poorly chosen and/or if highly
+	correlated variables are updated independently. We show here how
+	it is possible to build efficient high dimensional proposal distributions
+	by using sequential Monte Carlo methods. This allows us not only
+	to improve over standard Markov chain Monte Carlo schemes but also
+	to make Bayesian inference feasible for a large class of statistical
+	models where this was not previously so. We demonstrate these algorithms
+	on a non-linear state space model and a Levy-driven stochastic volatility
+	model.},
+  doi = {10.1111/j.1467-9868.2009.00736.x},
+  file = {Andrieu2010.pdf:Andrieu2010.pdf:PDF},
+  owner = {kingaa},
+  timestamp = {2010.06.30}
+}
+
 @ARTICLE{Arulampalam2002,
   author = {Arulampalam, M. S. and Maskell, S. and Gordon, N. and Clapp, T.},
   title = {A Tutorial on Particle Filters for Online Nonlinear, Non-{G}aussian

Modified: www/content/refs.htm
===================================================================
--- www/content/refs.htm	2010-06-30 19:30:22 UTC (rev 275)
+++ www/content/refs.htm	2010-06-30 19:30:43 UTC (rev 276)
@@ -1,6 +1,11 @@
 <h3><a name="SECTIONREF">References</a></h3>
 
 <dl compact>
+  <dt><a name="Andrieu2010">Andrieu, C., A.&nbsp;Doucet, and R.&nbsp;Holenstein. 2010.</a></dt>
+
+  <dd>Particle markov chain monte carlo methods.<br>
+  Journal of the Royal Statistical Society, Series B, <b>72</b>:269-342.<br></dd>
+
   <dt><a name="Arulampalam2002">Arulampalam, M.&nbsp;S., S.&nbsp;Maskell, N.&nbsp;Gordon, and T.&nbsp;Clapp. 2002.</a></dt>
 
   <dd>A tutorial on particle filters for online nonlinear, non-Gaussian Bayesian tracking.<br>

Modified: www/content/refs.tex
===================================================================
--- www/content/refs.tex	2010-06-30 19:30:22 UTC (rev 275)
+++ www/content/refs.tex	2010-06-30 19:30:43 UTC (rev 276)
@@ -6,6 +6,7 @@
 \begin{document}
 
 \nocite{Arulampalam2002}
+\nocite{Andrieu2010}
 \nocite{Breto2009}
 \nocite{Ellner1998}
 \nocite{He2010}