Improved EDF-Based Tests for Weibull Distribution Using Ranked Set Sampling

Safar M. Alghamdi, Rashad A. R. Bantan, Amal S. Hassan (), Heba F. Nagy, Ibrahim Elbatal and Mohammed Elgarhy
Additional contact information
Safar M. Alghamdi: Department of Mathematics and Statistics, College of Science, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
Rashad A. R. Bantan: Department of Marine Geology, Faculty of Marine Science, King Abdulaziz University, Jeddah 21551, Saudi Arabia
Amal S. Hassan: Faculty of Graduate Studies for Statistical Research, Cairo University, Giza 12613, Egypt
Heba F. Nagy: Faculty of Graduate Studies for Statistical Research, Cairo University, Giza 12613, Egypt
Ibrahim Elbatal: Faculty of Graduate Studies for Statistical Research, Cairo University, Giza 12613, Egypt
Mohammed Elgarhy: The Higher Institute of Commercial Sciences, Al Mahalla Al Kubra 31951, Egypt

Mathematics, 2022, vol. 10, issue 24, 1-24

Abstract: It is well known that ranked set sampling (RSS) is superior to conventional simple random sampling (SRS) in that it frequently results in more effective inference techniques. One of the most popular and broadly applicable models for lifetime data is the Weibull distribution. This article proposes different modified goodness-of-fit tests based on the empirical distribution function (EDF) for the Weibull distribution. The recommended RSS tests are compared to their SRS counterparts. For each scheme, the critical values of the relevant test statistics are computed. A comparison of the power of the suggested goodness-of-fit tests based on a number of alternatives is investigated. RSS tests are more effective than their SRS equivalents, according to simulated data.

Keywords: goodness-of-fit tests; ranked set sampling; power test; Weibull distribution (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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