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Bias Reduction for the Maximum Likelihood Estimator of the Scale Parameter in the Half-Logistic Distribution

We derive an analytic expression for the bias, to O(n-1) of the maximum likelihood estimator of the scale parameter in the half-logistic distribution. Using this expression to bias-correct the estimator is shown to be very effective in terms of bias reduction, without adverse consequences for the estimator’s precision. The analytic bias-corrected estimator is also shown to be dramatically superior to the alternative of bootstrap-bias-correction.

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Paper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number 0901.

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Length: 12 pages
Date of creation: 20 Jan 2009
Handle: RePEc:vic:vicewp:0901
Note: ISSN 1485-6441
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  1. Balakrishnan, N. & Chan, P. S., 1992. "Estimation for the scaled half logistic distribution under Type II censoring," Computational Statistics & Data Analysis, Elsevier, vol. 13(2), pages 123-141, March.
  2. Cordeiro, Gauss M. & Klein, Ruben, 1994. "Bias correction in ARMA models," Statistics & Probability Letters, Elsevier, vol. 19(3), pages 169-176, February.
  3. Adatia, A., 1997. "Approximate BLUEs of the parameters of the half logistic distribution based on fairly large doubly censored samples," Computational Statistics & Data Analysis, Elsevier, vol. 24(2), pages 179-191, April.
  4. Adatia, A., 2000. "Estimation of parameters of the half-logistic distribution using generalized ranked set sampling," Computational Statistics & Data Analysis, Elsevier, vol. 33(1), pages 1-13, March.
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