A Laplace transform inversion method for probability distribution functions

Stephen G. Walker

    Research output: Contribution to journalArticle

    Abstract

    This paper introduces a new Laplace transform inversion method designed specifically for when the target function is a probability distribution function. In particular, we use fixed point theory and Mann type iterative algorithms to provide a means by which to estimate and sample from the target probability distribution.

    Original languageEnglish (US)
    Pages (from-to)439-448
    Number of pages10
    JournalStatistics and Computing
    Volume27
    Issue number2
    DOIs
    StatePublished - Mar 1 2017

    Fingerprint

    Probability distribution function
    Laplace transform
    Inversion
    Target
    Probability distributions
    Laplace transforms
    Distribution functions
    Fixed point theory
    Iterative algorithm
    Probability distribution
    Estimate
    Fixed point

    Keywords

    • Fixed point solution
    • Recursive estimation

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Statistics and Probability
    • Statistics, Probability and Uncertainty
    • Computational Theory and Mathematics

    Cite this

    A Laplace transform inversion method for probability distribution functions. / Walker, Stephen G.

    In: Statistics and Computing, Vol. 27, No. 2, 01.03.2017, p. 439-448.

    Research output: Contribution to journalArticle

    Walker, Stephen G. / A Laplace transform inversion method for probability distribution functions.

    In: Statistics and Computing, Vol. 27, No. 2, 01.03.2017, p. 439-448.

    Research output: Contribution to journalArticle

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