Quasi-Exponentiated Normal Distributions: Mixture Representations and Asymmetrization

Author:

Korolev Victor123ORCID,Zeifman Alexander245ORCID

Affiliation:

1. Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Leninskie Gory, 119899 Moscow, Russia

2. Federal Research Center “Computer Sciences and Control” of the Russian Academy of Sciences, 44-2 Vavilova Str., 119333 Moscow, Russia

3. Moscow Center for Fundamental and Applied Mathematics, Moscow State University, 119991 Moscow, Russia

4. Department of Applied Mathematics, Vologda State University, 15 Lenina Str., 160000 Vologda, Russia

5. Vologda Research Center of the Russian Academy of Sciences, 556A Gorky Str., 160014 Vologda, Russia

Abstract

In the paper, quasi-exponentiated normal distributions are introduced for any real power (exponent) no less than two. With natural exponents, the quasi-exponentiated normal distributions coincide with the distributions of the corresponding powers of normal random variables with zero mean. Their representability as scale mixtures of normal and exponential distributions is proved. The mixing distributions are written out in the closed form. Two approaches to the construction of asymmetric quasi-exponentiated normal distributions are described. A limit theorem is proved for sums of a random number of independent random variables in which the asymmetric quasi-exponentiated normal distribution is the limit law.

Funder

Russian Science Foundation

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

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