BACKWARD NONLINEAR SMOOTHING DIFFUSIONS

B. D.O. Anderson, A. N. Bishop, P. Del Moral, C. Palmier

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    1 Citation (Scopus)

    Abstract

    We present a backward diffusion flow (i.e., a backward-in-time stochastic differential equation) whose marginal distribution at any (earlier) time is equal to the smoothing distribution when the terminal state (at a later time) is distributed according to the filtering distribution. This is a novel interpretation of the smoothing solution in terms of a nonlinear diffusion (stochastic) flow. This solution contrasts with, and complements, the (backward) deterministic flow of probability distributions (viz. a type of Kushner smoothing equation) studied in a number of prior works. A number of corollaries of our main result are given, including a derivation of the time-reversal of a stochastic differential equation, and an immediate derivation of the classical Rauch–Tung–Striebel smoothing equations in the linear setting.

    Original languageEnglish
    Pages (from-to)245-262
    Number of pages18
    JournalTheory of Probability and its Applications
    Volume66
    Issue number2
    DOIs
    Publication statusPublished - 2022

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