BAYESIAN ESTIMATION OF THE SHAPE PARAMETER OF GENERALIZED RAYLEIGH DISTRIBUTION UNDER SYMMETRIC AND ASYMMETRIC LOSS FUNCTIONS
BAYESIAN ESTIMATION OF THE SHAPE PARAMETER OF GENERALIZED RAYLEIGH DISTRIBUTION UNDER SYMMETRIC AND ASYMMETRIC LOSS FUNCTIONS
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Date
2016-04
Authors
ALIYU, YAKUBU
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Abstract
In 2001, Surles & Padgett introduced Generalized Rayleigh Distribution (GRD). This
skewed distribution can be used quiet effectively in modeling life time data. In this work,
Bayesian estimates of the shape parameter of a GRD were determined under the
assumption of both informative (gamma) and non-informative (Extended Jeffery’s and
Uniform) priors. The Bayes estimates were obtained under both symmetric and asymmetric
loss functions. The performances of these estimates were compared to the Maximum
Likelihood Estimates (MLEs) using Monte Carlo simulation.
Description
DISSERTATION SUBMITTED TO THE SCHOOL OF POSTGRADUATE STUDIES,
AHMADU BELLO UNIVERSITY, ZARIA
IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE AWARD OF A
MASTER DEGREE IN STATISTICS
DEPARTMENT OF MATHEMATICS,
FACULTY OF SCIENCE
AHMADU BELLO UNIVERSITY, ZARIA
NIGERIA
Keywords
BAYESIAN ESTIMATION,, SHAPE PARAMETER,, GENERALIZED RAYLEIGH DISTRIBUTION,, SYMMETRIC,, ASYMMETRIC LOSS FUNCTIONS,