Transition density estimation for stochastic differential equations via forward-reverse representations

Grigori N. Milstein, John G.M. Schoenmakers, Vladimir Spokoiny

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)

Abstract

The general reverse diffusion equations are derived and applied to the problem of transition density estimation of diffusion processes between two fixed states. For this problem we propose density estimation based on forward-reverse representations and show that this method allows essentially better results to be achieved than the usual kernel or projection estimation based on forward representations only.

Original languageEnglish
Pages (from-to)281-312
Number of pages32
JournalBernoulli
Volume10
Issue number2
DOIs
Publication statusPublished - Apr 2004
Externally publishedYes

Keywords

  • Forward and reverse diffusion
  • Monte Carlo simulation
  • Statistical estimation
  • Transition density

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