Multilevel particle filters

Ajay Jasra, Kengo Kamatani, Kody J.H. Law, Yan Zhou

Research output: Contribution to journalArticlepeer-review

52 Scopus citations


In this paper the filtering of partially observed diffusions, with discrete-time observa- tions, is considered. It is assumed that only biased approximations of the diffusion can be obtained for choice of an accuracy parameter indexed by l. A multilevel estimator is proposed consisting of a telescopic sum of increment estimators associated to the successive levels. The work associated to O("ϵ2) mean-squared error between the multilevel estimator and average with respect to the filtering distribution is shown to scale optimally, for example, as O("ϵ2) for optimal rates of convergence of the underlying diffusion approximation. The method is illustrated with some toy examples as well as estimation of interest rate based on real S&P 500 stock price data.
Original languageEnglish (US)
JournalSIAM Journal on Numerical Analysis
Issue number6
StatePublished - Jan 1 2017
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2019-11-20


Dive into the research topics of 'Multilevel particle filters'. Together they form a unique fingerprint.

Cite this