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Activity Number: 336
Type: Contributed
Date/Time: Tuesday, July 31, 2007 : 2:00 PM to 3:50 PM
Sponsor: IMS
Abstract - #309254
Title: Asymptotic Properties of MLEs for Extended Generalized Log-Logistic Families of Lifetime Distributions
Author(s): James U. Gleaton*+ and M. Mahbubur Rahman
Companies: University of North Florida and University of North Florida
Address: 4567 St Johns Bluff Road South, Jacksonville, FL, 32224,
Keywords: extended generalized log-logistic transformation ; maximum likelihood estimator ; asymptotic properties
Abstract:

An EGLL family of lifetime distributions is one in which any pair of distributions are related through an EGLL transformation, which is a composition of a proportional odds transformation and a generalized log-logistic transformation. It may be that one member of the family has a simple form, e.g. two-parameter Weibull, and may be considered the generating member. Any other member is called a composite distribution, having two additional parameters, due to the transformation. It is shown that if the generating distribution has certain regularity properties, then the MLEs for the parameters of a composite distribution have the properties of consistency and asymptotic normality and efficiency, for a certain range of values of the transformation parameters.

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