Volume no :19, Issue no: 2, June (2018)

Journal of Statistics: Advances in Theory and Applications

PROGRESSIVELY CENSORED DATA FROM THE GENERALIZED LINEAR EXPONENTIAL DISTRIBUTION MOMENTS AND ESTIMATION

Author's: N. M. Yhiea
Pages: [105] - [126]
Received Date: May 24, 2018; Revised June 23, 2018
Submitted by:
DOI: http://dx.doi.org/10.18642/jsata_7100121970

Abstract

In this paper, we derive approximate moments of progressively type-II right censored order statistics from the generalized linear exponential distribution. Depending on these moments, the best linear unbiased estimators and maximum likelihoods estimators of the location and scale parameters are found. In addition, we use Monte-Carlo simulation method to obtain the mean square error of the best linear unbiased estimates, maximum likelihood estimates and make comparison between them. Finally, we determine the optimal progressive censoring scheme for some practical choices of n and m when progressively type-II right censored samples are from the considered distribution and present numerical example to illustrate the developed inference procedures.

Keywords

progressively type-II censored sample, generalized linear exponential distribution, approximate moments, best linear unbiased estimates (BLUEs), maximum likelihood estimates (MLEs), Monte-Carlo method, optimal scheme.