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Modified Moment, Maximum Likelihood and Percentile Estimators for the Parameters of the Power Function Distribution
Abstract
This paper is concerned with the modifications of maximum likelihood, moments and percentile estimators of the two parameter Power function distribution. Sampling behavior of the estimators is indicated by Monte Carlo simulation. For some combinations of parameter values, some of the modified estimators appear better than the traditional maximum likelihood, moments and percentile estimators with respect to bias, mean square error and total deviation.
Keywords
Parameter estimation, percentile estimators, maximum likelihood estimators, moment estimators, modified estimators, monte carlo study, total deviation, mean square error.
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PDFDOI: http://dx.doi.org/10.18187/pjsor.v10i4.614
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Copyright (c) 2014 Pakistan Journal of Statistics and Operation Research
This work is licensed under a Creative Commons Attribution 4.0 International License.
Title
Modified Moment, Maximum Likelihood and Percentile Estimators for the Parameters of the Power Function Distribution
Keywords
Parameter estimation, percentile estimators, maximum likelihood estimators, moment estimators, modified estimators, monte carlo study, total deviation, mean square error.
Description
This paper is concerned with the modifications of maximum likelihood, moments and percentile estimators of the two parameter Power function distribution. Sampling behavior of the estimators is indicated by Monte Carlo simulation. For some combinations of parameter values, some of the modified estimators appear better than the traditional maximum likelihood, moments and percentile estimators with respect to bias, mean square error and total deviation.
Date
2014-10-13
Identifier
Source
Pakistan Journal of Statistics and Operation Research; Vol. 10 No. 4, 2014
Print ISSN: 1816-2711 | Electronic ISSN: 2220-5810