Particle approximations of the score and observed information matrix for parameter estimation in state space models with linear computational cost

4 June 2013

Papers citing "Particle approximations of the score and observed information matrix for parameter estimation in state space models with linear computational cost"

10 / 10 papers shown

Title
R-VGAL: A Sequential Variational Bayes Algorithm for Generalised Linear Mixed Models Bao Anh Vu David Gunawan A. Zammit‐Mangion DRL 12 1 0 01 Jun 2023
Nonlinear System Identification: Learning while respecting physical models using a sequential Monte Carlo method A. Wigren Johan Wågberg Fredrik Lindsten A. Wills Thomas B. Schon 24 10 0 26 Oct 2022
Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters Conor Rosato Vincent Beraud P. Horridge Thomas B. Schon Simon Maskell 18 14 0 02 Nov 2021
Augmented pseudo-marginal Metropolis-Hastings for partially observed diffusion processes Andrew Golightly Chris Sherlock 39 3 0 11 Sep 2020
Regularized Zero-Variance Control Variates Leah F. South Chris J. Oates Antonietta Mira Christopher C. Drovandi BDL 14 19 0 13 Nov 2018
On Particle Methods for Parameter Estimation in State-Space Models N. Kantas Arnaud Doucet Sumeetpal S. Singh J. Maciejowski Nicolas Chopin 43 427 0 30 Dec 2014
Particle Metropolis-adjusted Langevin algorithms Christopher Nemeth Chris Sherlock Paul Fearnhead 33 24 0 23 Dec 2014
Particle Metropolis adjusted Langevin algorithms for state space models Christopher Nemeth Paul Fearnhead 36 19 0 04 Feb 2014
Particle Metropolis-Hastings using gradient and Hessian information J. Dahlin Fredrik Lindsten Thomas B. Schon 50 46 0 04 Nov 2013
On Particle Learning Nicolas Chopin A. Iacobucci Jean-Michel Marin Kerrie Mengersen Christian P. Robert Robin J. Ryder Christian Schafer 70 28 0 03 Jun 2010