Open AccessComparison of Two New Robust Parameter Estimation Methods for the Power Function Distribution
Author(s) -
Muhammad Shakeel,
Muhammad Ahsan ul Haq,
Ijaz Hussain,
Alaa Mohamd Abdulhamid,
Muhammad Faisal
Publication year - 2016
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0160692
Subject(s) - statistics , mathematics , sample size determination , probability density function , moment (physics) , probability distribution , moment generating function , mean squared error , distribution (mathematics) , standard deviation , mathematical analysis , physics , classical mechanics
Estimation of any probability distribution parameters is vital because imprecise and biased estimates can be misleading. In this study, we investigate a flexible power function distribution and introduced new two methods such as, probability weighted moments, and generalized probability weighted methods for its parameters. We compare their results with L-moments, trimmed L-moments by a simulation study and a real data example based on performance measures such as, mean square error and total deviation. We concluded that all the methods perform well in the case of large sample size (n>30), however, the generalized probability weighted moment method performs better for small sample size.