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Mahdi Rasekhi

Mahdi Rasekhi

Academic rank: Assistant Professor
ORCID:
Education: PhD.
ScopusId:
HIndex:
Faculty: Mathematical Sciences and Statistics
Address:
Phone: 0813-33339843 داخلی 391

Research

Title
A flexible generalization of the skew normal distribution based on a weighted normal distribution
Type
JournalPaper
Keywords
Skew normal distribution Moments Kurtosis Skewness Stochastic representation
Year
2016
Journal Statistical Methods and Applications
DOI
Researchers Mahdi Rasekhi

Abstract

The skew normal distribution of Azzalini (Scand J Stat 12:171–178, 1985) has been found suitable for unimodal density but with some skewness present. Through this article, we introduce a flexible extension of the Azzalini (Scand J Stat 12:171–178, 1985) skew normal distribution based on a symmetric component normal distribution (Gui et al. in J Stat Theory Appl 12(1):55–66, 2013). The proposed model can efficiently capture the bimodality, skewness and kurtosis criteria and heavy-tail property. The paper presents various basic properties of this family of distributions and provides two stochastic representations which are useful for obtaining theoretical properties and to simulate from the distribution. Further, maximum likelihood estimation of the parameters is studied numerically by simulation and the distribution is investigated by carrying out comparative fitting of three real datasets.