Year: 2013
Type: article
Abstract: This is a short review of Monte Carlo methods for approximating filter distributions in state space models. The basic algorithm and different strategies to reduce imbalance of the weights are discussed. Finally, methods for more difficult problems like smoothing and parameter estimation and applications outside the state space model context are presented.
Source: Bernoulli
DOI: 10.3150/12-bejsp07
Author: Hans R. Künsch
Institutions: ETH Zurich, Seminar for Statistics
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W3037042468