Unbiased Smoothing using Particle Independent Metropolis-Hastings
暂无分享,去创建一个
Arnaud Doucet | Pierre E. Jacob | George Deligiannidis | Lawrence Middleton | A. Doucet | George Deligiannidis | P. Jacob | Lawrence Middleton
[1] Pierre E. Jacob,et al. Path storage in the particle filter , 2013, Statistics and Computing.
[2] A. Doucet,et al. A Tutorial on Particle Filtering and Smoothing: Fifteen years later , 2008 .
[3] Ralph S. Silva,et al. On Some Properties of Markov Chain Monte Carlo Simulation Methods Based on the Particle Filter , 2012 .
[4] Matti Vihola,et al. Coupled conditional backward sampling particle filter , 2018, The Annals of Statistics.
[5] Theodore Kypraios,et al. Efficient SMC2 schemes for stochastic kinetic models , 2017, Stat. Comput..
[6] R. Kohn,et al. Diagnostics for Time Series Analysis , 1999 .
[7] D. Gillespie. Exact Stochastic Simulation of Coupled Chemical Reactions , 1977 .
[8] P. Moral,et al. Sharp Propagation of Chaos Estimates for Feynman–Kac Particle Models , 2007 .
[9] P. Moral,et al. Sequential Monte Carlo samplers , 2002, cond-mat/0212648.
[10] A. Doucet,et al. Particle Markov chain Monte Carlo methods , 2010 .
[11] Yan Zhou,et al. Toward Automatic Model Comparison: An Adaptive Sequential Monte Carlo Approach , 2016 .
[12] Christophe Andrieu,et al. Uniform ergodicity of the iterated conditional SMC and geometric ergodicity of particle Gibbs samplers , 2013, 1312.6432.
[13] Sumeetpal S. Singh,et al. On particle Gibbs sampling , 2013, 1304.1887.
[14] P. Moral. Feynman-Kac Formulae: Genealogical and Interacting Particle Systems with Applications , 2004 .
[15] Peter W. Glynn,et al. Exact estimation for Markov chain equilibrium expectations , 2014, Journal of Applied Probability.
[16] N. Shephard,et al. Econometric analysis of realized volatility and its use in estimating stochastic volatility models , 2002 .
[17] P. Moral,et al. On adaptive resampling strategies for sequential Monte Carlo methods , 2012, 1203.0464.
[18] Arnaud Doucet,et al. On Particle Methods for Parameter Estimation in State-Space Models , 2014, 1412.8695.
[19] N. Shephard,et al. Non‐Gaussian Ornstein–Uhlenbeck‐based models and some of their uses in financial economics , 2001 .
[20] Radford M. Neal. Annealed importance sampling , 1998, Stat. Comput..
[21] John O'Leary,et al. Unbiased Markov chain Monte Carlo with couplings , 2017, 1708.03625.
[22] Philip Heidelberger,et al. Analysis of parallel replicated simulations under a completion time constraint , 1991, TOMC.
[23] A. Doucet,et al. Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator , 2012, 1210.1871.
[24] Arnaud Doucet,et al. On the Utility of Graphics Cards to Perform Massively Parallel Simulation of Advanced Monte Carlo Methods , 2009, Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America.
[25] Arnaud Doucet,et al. Large-sample asymptotics of the pseudo-marginal method , 2018, Biometrika.
[26] Arnaud Doucet,et al. Unbiased Markov chain Monte Carlo for intractable target distributions , 2020, Electronic Journal of Statistics.
[27] J. N. Corcoran,et al. Perfect sampling from independent Metropolis-Hastings chains☆ , 2002 .
[28] Fredrik Lindsten,et al. Smoothing With Couplings of Conditional Particle Filters , 2017, Journal of the American Statistical Association.
[29] J. Heng,et al. Unbiased Hamiltonian Monte Carlo with couplings , 2017, Biometrika.
[30] A. Doucet,et al. A lognormal central limit theorem for particle approximations of normalizing constants , 2013, 1307.0181.
[31] D. Wilkinson,et al. Bayesian Inference for Stochastic Kinetic Models Using a Diffusion Approximation , 2005, Biometrics.