الفهرس 
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Abstract
In this chapter, we discussed the estimation of the unknown parameters
( , , p) of the Weibull-Geometric distribution and the acceleration parameter
, based on constant partially accelerated life tests. Based on a progressive
first-failure censored sample the maximum likelihood and the Bayes estimates
are obtained. It is observed that the Bayes estimators cannot be obtained in
explicit forms and they need complicated integrals to be performed numerically.
Because of that, the MCMC method, namely the Metropolis-Hastings
sampling technique, is applied to obtain the Bayes estimates under squared
error and Linex loss functions.
from the results, in Tables (5.1) - (5.4), it can be observed that the Bayes
estimates under the symmetric (SEL) and the asymmetric (Linex) loss functions
are better than their corresponding MLEs. It can also be seen that the
mean squared errors decrease as the sample sizes increase. Also there is no
large effect of exchanging the censoring scheme on results.
Note:
Some results of this chapter have been submitted for publications in Assiut
University Journal of Mathematics and Computer Science under the title ”Estimation
for the Weibull-Geometric Distribution based on constant partially
accelerated life tests via MCMC technique”.