Class of skew-distributions: theory and applications in biology
Authors:
Nelson P. Barrera a;
Manuel Galea b;
Soledad Torres c;
Manuel Villal
n a
n a
| Affiliations: | a Departamento de Fisiolog a, Pontificia Universidad Cat lica de Chile, |
b Departamento de Estad stica, Universidad de Valpara so, Valpara so, Chile |
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c Departamento de Estad stica and CIMFAV, Universidad de Valpara so, Valpara so, Chile |
DOI:
10.1080/02331880600741780
Publication Frequency:
6 issues per year
Subjects:
Mathematical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
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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.
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| Keywords: Beta distribution; Skew distributions; Hermite polynomials; Convolution formula |
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