Epsilon half-normal model: Properties and inference

Luis M. Castro, Héctor W. Gómez and Maria Valenzuela

Computational Statistics & Data Analysis, 2012, vol. 56, issue 12, 4338-4347

Abstract: The half-normal distribution is one of the widely used probability distribution for non-negative data modeling, specifically, to describe the lifetime process under fatigue. In this paper, we introduce a new type of non-negative distribution that extends the half-normal distribution. We refer to this new distribution as the epsilon half-normal distribution. We provide mathematical properties of this new distribution. In particular, we derive the stochastic representation, explicit formulas for the n-th moment, the asymmetry and kurtosis coefficients and the moment generating function. We also discuss some inferential aspects related to the maximum likelihood estimation. We illustrate the flexibility of this type of distribution with an application to a real dataset of stress-rupture.

Keywords: EM algorithm; Epsilon skew-symmetric distribution; Half-normal distribution; Nonnegative distributions; Stochastic representation (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167947312001466
Full text for ScienceDirect subscribers only.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:56:y:2012:i:12:p:4338-4347

DOI: 10.1016/j.csda.2012.03.020

Access Statistics for this article

Computational Statistics & Data Analysis is currently edited by S.P. Azen

More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().