An iterative algorithm to bound partial moments

Sander Muns*

*Corresponding author for this work

    Research output: Contribution to journalArticleScientificpeer-review

    Abstract

    This paper presents an iterative algorithm that bounds the lower and upper partial moments of an arbitrary univariate random variable X by using the information contained in a sequence of finite moments of X. The obtained bounds on the partial moments imply bounds on the moments of the transformation f(X) for a certain function  f:\mathbb {R}\rightarrow \mathbb {R} . Two examples illustrate the performance of the algorithm.
    Original languageEnglish
    Pages (from-to)89-122
    JournalComputational Statistics
    Volume34
    Issue number1
    DOIs
    Publication statusPublished - Mar 2019

    Keywords

    • Moment problem
    • Bounds
    • Censored distributions
    • Iteration convergence
    • PROBABILITY-DISTRIBUTIONS
    • INFORMATION
    • RECONSTRUCTION
    • EXPECTATION
    • TAIL

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