An iterative algorithm to bound partial moments

Sander Muns ()
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Sander Muns: Tilburg University, Netspar

Computational Statistics, 2019, vol. 34, issue 1, No 5, 89-122

Abstract: 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 $$f:\mathbb {R}\rightarrow \mathbb {R}$$ f : R → R . Two examples illustrate the performance of the algorithm.

Keywords: Moment problem; Bounds; Censored distributions; Iteration convergence (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s00180-018-0825-8

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