A new weighted distribution as an extension of the generalized half-normal distribution with applications

Acitas S.

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, vol.88, no.12, pp.2325-2341, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 88 Issue: 12
  • Publication Date: 2018
  • Doi Number: 10.1080/00949655.2018.1462812
  • Journal Name: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.2325-2341
  • Keywords: Generalized half-normal distribution, weighted distribution, hazard rate, estimation, fitting, EXPONENTIAL-DISTRIBUTIONS, LIFE DISTRIBUTIONS, FAMILY, PARAMETERS, MODELS
  • Anadolu University Affiliated: Yes

Abstract

In this study, a new extension of generalized half-normal (GHN) distribution is introduced. Since this new distribution can be viewed as weighted version of GHN distribution, it is called as weighted generalized half-normal (WGHN) distribution. It is shown that WGHN distribution can be observed as a single constrained and hidden truncation model. Therefore, the new distribution is more flexible than the GHN distribution. Some statistical properties of the WGHN distribution are studied, i.e. moments, cumulative distribution function, hazard rate function are derived. Furthermore, maximum likelihood estimation of the parameters is considered. Some real-life data sets taken from the literature are modelled using the WGHN distribution. It is seen that for these data sets the WGHN distribution provides better fitting than the GHN and slashed generalized half-normal (SGHN) distributions.