2011arXiv (Cornell University)Open access

A note on the infinite divisibility of a class of transformations of normal variables

Antonio Murillo-Salas, Francisco J. Rubio

Open full text 1 citations

Abstract

This note examines the infinite divisibility of density-based transformations of normal random variables. We characterize a class of density-based transformations of normal variables which produces non-infinitely divisible distributions. We relate our result with some known skewing mechanisms.

Open-access reader

About this research paper

What this paper is about

This note examines the infinite divisibility of density-based transformations of normal random variables. We characterize a class of density-based transformations of normal variables which produces non-infinitely divisible distributions. We relate our result with some known skewing mechanisms.

Why it matters

OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

This note examines the infinite divisibility of density-based transformations of normal random variables. We characterize a class of density-based transformations of normal variables which produces non-infinitely divisible distributions. We relate our result with some known skewing mechanisms.

Key concepts: Infinite divisibility, Divisibility rule, Class (philosophy), Mathematics, Random variable, Pure mathematics, Statistical physics, Statistics

Related papers

Back to paper searchBrowse research topicsOriginal source
A note on the infinite divisibility of a class of transformations of normal variables — Research Paper | ScholarLens