Stieltjes and Hamburger Reduced Moment Problem When MaxEnt Solution Does Not Exist

Pier Luigi Novi Inverardi and Aldo Tagliani
Additional contact information
Pier Luigi Novi Inverardi: Department of Economics and Management, University of Trento, 38122 Trento, Italy
Aldo Tagliani: Department of Economics and Management, University of Trento, 38122 Trento, Italy

Mathematics, 2021, vol. 9, issue 4, 1-15

Abstract: For a given set of moments whose predetermined values represent the available information, we consider the case where the Maximum Entropy (MaxEnt) solutions for Stieltjes and Hamburger reduced moment problems do not exist. Genuinely relying upon MaxEnt rationale we find the distribution with largest entropy and we prove that this distribution gives the best approximation of the true but unknown underlying distribution. Despite the nice properties just listed, the suggested approximation suffers from some numerical drawbacks and we will discuss this aspect in detail in the paper.

Keywords: probability distribution; Stieltjes and Hamburger reduced moment problem; entropy; maximum entropy; moment space (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2227-7390/9/4/309/pdf (application/pdf)
https://www.mdpi.com/2227-7390/9/4/309/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:9:y:2021:i:4:p:309-:d:493208

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().