Modified Moment, Maximum Likelihood and Percentile Estimators for the Parameters of the Power Function Distribution

Azam Zaka, Ahmad Saeed Akhter

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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DOI: http://dx.doi.org/10.18187/pjsor.v10i4.614

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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