Estimation of the Mean of Truncated Exponential Distribution
Author(s) -
Faris M. Al-Athari
Publication year - 2008
Publication title -
journal of mathematics and statistics
Language(s) - English
Resource type - Journals
eISSN - 1558-6359
pISSN - 1549-3644
DOI - 10.3844/jmssp.2008.284.288
Subject(s) - mathematics , estimator , minimum variance unbiased estimator , statistics , bias of an estimator , efficient estimator , restricted maximum likelihood , delta method , variance (accounting) , m estimator , efficiency , exponential family , trimmed estimator , exponential distribution , asymptotic distribution , exponential function , mean squared error , maximum likelihood , mathematical analysis , accounting , business
Problem statement: In this study, the researcher considers the problem of estimation of the mean of the truncated exponential distribution. Approach: This study contracted with maximum likelihood and unique minimum variance unbiased estimators and gives a modification for the maximum likelihood estimator, asymptotic variances and asymptotic confidence intervals for the estimators. The properties of these estimators in small, moderate and large samples were investigated via asymptotic theory and computer simulation. Results: It turns out that the modified maximum likelihood estimator was more efficient than the others and exists with probability 1. Conclusion: The modified maximum likelihood estimator was always exist, fast and straightforward to compute and more likely to yield feasible values than the unique minimum variance unbiased estimator. Its variance was well approximated by the large sample variance of the other estimators
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