title: Comparison of Two New Robust Parameter Estimation Methods for the Power Function Distribution.
abstract: 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.
authors: Department of Statistics, Government Degree College for Boys Hujra Shah Muqeem, Okara, Pakistan.
authors: Muhammad
authors: M
authors: Shakeel
authors: College of Statistical and Actuarial Sciences, University of the Punjab, Lahore, Pakistan.
authors: Muhammad Ahsan Ul
authors: MA
authors: Haq
authors: Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan.
authors: Ijaz
authors: http://orcid.org/0000-0002-1586-1503
authors: I
authors: Hussain
authors: Arriyadh Community College, King Saud University, Riyadh, Saudi Arabia.
authors: Alaa Mohamd
authors: AM
authors: Abdulhamid
authors: Bradford Institute for Health Research, Bradford Teaching Hospitals, NHS Foundation Trust, Bradford, United Kingdom.
authors: Muhammad
authors: M
authors: Faisal
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D018401:Sample Size