Document Type

Article

Language

eng

Format of Original

18 p.

Publication Date

12-2013

Publisher

Atlantis Press

Source Publication

Journal of Statistical Theory and Applications

Source ISSN

1538-7887

Original Item ID

doi: 10.2991/jsta.2013.12.4.2

Abstract

We introduce a log-linear regression model based on the beta generalized half-normal distribution (Pescim et al., 2010).We formulate and develop a log-linear model using a new distribution so-called the log-beta general- ized half normal distribution.We derive expansions for the cumulative distribution and density functions which do not depend on complicated functions. We obtain formal expressions for the moments and moment gener- ating function. We characterize the proposed distribution using a simple relationship between two truncated moments. An advantage of the new distribution is that it includes as special sub-models classical distributions reported in the lifetime literature. We also show that the new regression model can be applied to censored data since it represents a parametric family of models that includes as special cases several widely-known regression models. It therefore can be used more effectively in the analysis of survival data. We investigate the maximum likelihood estimates of the model parameters by considering censored data. We demonstrate that our extended regression model is very useful to the analysis of real data and may give more realistic fits than other special regression models.

Comments

Published version. Journal of Statistical Theory and Applications, Vol. 12, No. 4 (December 2013): 330-347. DOI. © Atlantis Press 2013. Used with permission.

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