The bivariate generalized linear failure rate distribution and its multivariate extension

Ammar M. Sarhan, David C. Hamilton, Bruce Smith and Debasis Kundu

Computational Statistics & Data Analysis, 2011, vol. 55, issue 1, 644-654

Abstract: The two-parameter linear failure rate distribution has been used quite successfully to analyze lifetime data. Recently, a new three-parameter distribution, known as the generalized linear failure rate distribution, has been introduced by exponentiating the linear failure rate distribution. The generalized linear failure rate distribution is a very flexible lifetime distribution, and the probability density function of the generalized linear failure rate distribution can take different shapes. Its hazard function also can be increasing, decreasing and bathtub shaped. The main aim of this paper is to introduce a bivariate generalized linear failure rate distribution, whose marginals are generalized linear failure rate distributions. It is obtained using the same approach as was adopted to obtain the Marshall-Olkin bivariate exponential distribution. Different properties of this new distribution are established. The bivariate generalized linear failure rate distribution has five parameters and the maximum likelihood estimators are obtained using the EM algorithm. A data set is analyzed for illustrative purposes. Finally, some generalizations to the multivariate case are proposed.

Keywords: Marshall-Olkin; copula; Maximum; likelihood; estimator; Failure; rate; EM; algorithm; Fisher; information; matrix (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (9)

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