Bias Reduction for the Maximum Likelihood Estimators of the Parameters in the Half-Logistic Distribution |
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Authors: | David E Giles |
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Institution: | 1. Department of Economics , University of Victoria , Victoria , B.C. , Canada dgiles@uvic.ca |
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Abstract: | We derive analytic expressions for the biases of the maximum likelihood estimators of the scale parameter in the half-logistic distribution with known location, and of the location parameter when the latter is unknown. Using these expressions to bias-correct the estimators is highly effective, without adverse consequences for estimation mean squared error. The overall performance of the first of these bias-corrected estimators is slightly better than that of a bootstrap bias-corrected estimator. The bias-corrected estimator of the location parameter significantly out-performs its bootstrapped-based counterpart. Taking computational costs into account, the analytic bias corrections clearly dominate the use of the bootstrap. |
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Keywords: | Bias reduction Half-logistic distribution Life testing |
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