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Class of skew-distributions: theory and applications in biology 

Authors: Nelson P. Barrera a;  Manuel Galea b;  Soledad Torres c; Manuel Villaloacuten a
Affiliations:   a Departamento de Fisiologiacutea, Pontificia Universidad Catoacutelica de Chile,
b Departamento de Estadiacutestica, Universidad de Valparaiacuteso, Valparaiacuteso, Chile
c Departamento de Estadiacutestica and CIMFAV, Universidad de Valparaiacuteso, Valparaiacuteso, Chile
DOI: 10.1080/02331880600741780
Publication Frequency: 6 issues per year
Published in: journal Statistics, Volume 40, Issue 4 August 2006 , pages 365 - 375
Formats available: HTML (English) : PDF (English)
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Abstract

In this paper, we study a class of skew-normal distributions driven by the convolution of two independent random variables: a normal and a beta distributed random variables. This problem is motivated by the numerical simulation of the oviductal egg transport in mammals, expressed as a series of microsphere instant velocities regulated by ovarian hormones including estradiol. We propose a closed form convolution formula, represented in terms of the infinite series expanded using Hermite polynomials. We also analyse the convergence of such series and perform the numerical experiments to illustrate these formulae.
Keywords: Beta distribution; Skew distributions; Hermite polynomials; Convolution formula
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