Bias Reduction for the Maximum Likelihood Estimator of the Parameters of the Generalized Rayleigh Family of Distributions
AbstractWe derive analytic expressions for the biases, to O(n-1), of the maximum likelihood estimators of the parameters of the generalized Rayleigh distribution family. Using these expressions to bias-correct the estimators is found to be extremely effective in terms of bias reduction, and generally results in a small reduction in relative mean squared error. In general, the analytic bias-corrected estimators are also found to be superior to the alternative of bias-correction via the bootstrap.
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Bibliographic InfoPaper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number 1111.
Length: 22 pages
Date of creation: 17 Nov 2011
Date of revision:
Note: ISSN 1485-6441
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Postal: PO Box 1700, STN CSC, Victoria, BC, Canada, V8W 2Y2
Web page: http://web.uvic.ca/econ
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Generalized Rayleigh distribution; maximum likelihood; bias; mean squared error; bias correction;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
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- Meagher Kieron J & Teo Ernie G.S. & Wang Wen, 2008. "A Duopoly Location Toolkit: Consumer Densities Which Yield Unique Spatial Duopoly Equilibria," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 8(1), pages 1-23, April.
- Beenstock, Michael, 1995. "The stochastic economics of windpower," Energy Economics, Elsevier, vol. 17(1), pages 27-37, January.
- Clements, Kenneth W & Selvanathan, Antony & Selvanathan, Saroja, 1996. "Applied Demand Analysis: A Survey," The Economic Record, The Economic Society of Australia, vol. 72(216), pages 63-81, March.
- Cordeiro, Gauss M. & Klein, Ruben, 1994. "Bias correction in ARMA models," Statistics & Probability Letters, Elsevier, vol. 19(3), pages 169-176, February.
- Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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