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

N. M. Yhiea | Zendy

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

Author(s) -

N. M. Yhiea

Publication year - 2018

Publication title -

journal of statistics advances in theory and applications

Language(s) - English

Resource type - Journals

ISSN - 0975-1262

DOI - 10.18642/jsata_7100121970

Subject(s) - exponential distribution , natural exponential family , mathematics , estimation , exponential function , exponentially modified gaussian distribution , gamma distribution , laplace distribution , statistics , distribution (mathematics) , exponential family , mathematical analysis , economics , management

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 typeII right censored samples are from the considered distribution and present numerical example to illustrate the developed inference procedures. N. M. YHIEA 106

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