Efficient estimation of Pareto model: Some modified percentile estimators

Sajjad Haider Bhatti, Shahzad Hussain, Tanvir Ahmad, Muhammad Aslam, Muhammad Aftab and Muhammad Ali Raza

PLOS ONE, 2018, vol. 13, issue 5, 1-15

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.

Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0196456 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 96456&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0196456

DOI: 10.1371/journal.pone.0196456

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().