A note on proximity of distributions in terms of coinciding moments.
type: Item
instance of: scholarly article
title: A note on proximity of distributions in terms of coinciding moments.
zbMATH Open document ID: 1038.62012
DOI: 10.1016/S0096-3003(02)00477-0
author: Aldo Tagliani
published in: Applied Mathematics and Computation
publication date: 2003-11-25T00:00:00Z
review text: The aim of this article is to obtain a uniform approximation of a distribution function for which is considered to be known a finite set of its moments. The author introduces a bound on the absolute difference between two distributions having a determined moment problem and sharing the information contents of their first few moments. Using the well-known principle of maximum entropy, the approximation process is proved to be convergent. Two particular examples illustrate the proposed (continuous and discrete) upper bounds of the two distributions in terms of their entropies. Applications in the field of (mathematical) finance (evaluation of value at risk) are suggested.
Mathematics Subject Classification ID: 62E17
Mathematics Subject Classification ID: 60E15
Mathematics Subject Classification ID: 62B10
Mathematics Subject Classification ID: 91B30
zbMATH DE Number: 2008961
zbMATH Keywords: moment-based distribution approximation
zbMATH Keywords: Hankel matrix
zbMATH Keywords: Lévy and Zolotarev distance
zbMATH Keywords: maximum entropy
zbMATH Keywords: proximity of distributions
zbMATH Keywords: value-at-risk evaluation
reviewed by: Neculai Curteanu
MaRDI profile type: Publication
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description: scientific article; zbMATH DE number 2008961