Particle Markov chain Monte Carlo methods

Particle Markov chain Monte Carlo methods (2010)

Cached

Download Links

by Christophe Andrieu , Arnaud Doucet , Roman Holenstein

Citations:

BibTeX

@MISC{Andrieu10particlemarkov,
    author = {Christophe Andrieu and Arnaud Doucet and Roman Holenstein},
    title = {Particle Markov chain Monte Carlo methods},
    year = {2010}
}

Bookmark

OpenURL

Abstract

Citations

751	Novel Approach to Nonlinear/Non-Gaussian Bayesian State Estimation - Gordon, Salmond, et al. - 1993
360	Filtering via simulation: Auxiliary particle filter - Pitt, Shephard - 1999
276	Monte Carlo filter and smoother for non-Gaussian nonlinear state space models - Kitagawa - 1996
240	On Gibbs Sampling for State Space Models - Carter, Kohn - 1994
161	Non-Gaussian Ornstein-Uhlenbeck-Based Models and some of their Uses in Financial Econometrics (with discussion - Barndorff-Nielsen, Shephard - 2001
135	Rate of convergences of the Hasting and Metropolis algorithms - Mengersen, Tweedie - 1996
132	Monte Carlo Strategies - Liu
125	Likelihood analysis of non-Gaussian measurement time series - Shephard, Pitt - 1997
114	An improved particle filter for non-linear problems - Carpenter, Clifford, et al. - 1999
94	Following A Moving Target–Monte Carlo Inference for Dynamic Bayesian Models - Gilks, Berzuini - 2001
93	Feynman Kac Formulae. Genealogical and Interacting Particle Systems with Applications. Probability and its Applications - Moral - 2004
87	Data augmentation and dynamic linear models - Frühwirth-Schnatter - 1994
82	2006b). Sequential Monte Carlo samplers - Moral, P, et al.
44	A sequential particle filter method for static models - Chopin - 2002
36	Estimating macroeconomic models: A likelihood approach - Rubio-Ramirez - 2007
34	An efficient Markov chain Monte Carlo method for distributions with intractable normalisation constants - Møller, Pettitt, et al. - 2006
33	A tutorial on particle filtering and smoothing: Fifteen years later,” in The Oxford Handbook of Nonlinear Filtering - Doucet, Johansen - 2011
27	The multiple-try method and local optimization in Metropolis sampling - Liu, Liang, et al. - 2000
19	Inference for nonlinear dynamical systems - Ionides, Breto, et al. - 2006
14	sufficient statistics and particle filters - Fearnhead, “MCMC - 2007
13	Bayesian inference for non-Gaussian Ornstein-Uhlenbeck stochastic volatility processes - Roberts, Papaspiliopoulos, et al. - 2004
9	Configurational-bias monte carlo - a new sampling scheme for flexible chains, Molecular Physics 75 - Siepmann, Frenkel - 1992
7	Normal modified stable processes, Theory Probab - Barndorff-Nielsen, Shepard - 2002
7	Estimation of population growth or decline in genetically monitored populations - Beaumont - 2003
6	A non asymptotic variance theorem for unnormalized Feynman-Kac particle models, HAL-INRIA Research Report 6716 - Cerou, Moral, et al. - 2008
4	The pseudo-marginal approach for efficient computation - Andrieu, Roberts - 2009
4	Bayesian inference based only on simulated likelihood:Particle filter analysis of dynamic economic models. Econometric Theory - Flury, Shephard, et al. - 2011
4	Waste-recycling monte carlo - Frenkel - 2006
3	The expected auxiliary variable method for Monte Carlo simulation - Andrieu, Berthelesen, et al. - 2008
3	Sequential Markov chain Monte Carlo for Bayesian model selection - Andrieu, Freitas, et al. - 1999
2	Particle filter estimation of duration-type models - Belmonte, Papaspiliopoulos, et al. - 2008
2	Dynamic pruned-enriched Rosenbluth method - Combe, Vlugt, et al.
2	Bayesian estimation of stochastic volatility models based on OU processes with marginal gamma - Frühwirth-Schnatter, Sögner
2	Stochastic volatility modelling in continuous time with general marginal distributions: Inference, prediction and model selection - Gander, Stephens
1	Analysis of filtering and smoothing algorithms for Lévy-driven stochastic volatility models - Creal - 2008