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Efficient estimation of Pareto model: Some modified percentile estimators.

ABSTRACT: The article proposes three modified percentile estimators for parameter estimation of the Pareto distribution. These modifications are based on median, geometric mean and expectation of empirical cumulative distribution function of first-order statistic. The proposed modified estimators are compared with traditional percentile estimators through a Monte Carlo simulation for different parameter combinations with varying sample sizes. Performance of different estimators is assessed in terms of total mean square error and total relative deviation. It is determined that modified percentile estimator based on expectation of empirical cumulative distribution function of first-order statistic provides efficient and precise parameter estimates compared to other estimators considered. The simulation results were further confirmed using two real life examples where maximum likelihood and moment estimators were also considered.

SUBMITTER: Bhatti SH

PROVIDER: S-EPMC5929531 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Efficient estimation of Pareto model: Some modified percentile estimators.

Bhatti Sajjad Haider SH Hussain Shahzad S Ahmad Tanvir T Aslam Muhammad M Aftab Muhammad M Raza Muhammad Ali MA

PloS one 20180501 5

The article proposes three modified percentile estimators for parameter estimation of the Pareto distribution. These modifications are based on median, geometric mean and expectation of empirical cumulative distribution function of first-order statistic. The proposed modified estimators are compared with traditional percentile estimators through a Monte Carlo simulation for different parameter combinations with varying sample sizes. Performance of different estimators is assessed in terms of tot ...[more]

PMID: 29715280

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