Hypothesis testing for the inverse Gaussian distribution mean based on ranked set sampling

KARADAĞ ÇAMAN Ö., BACANLI S.

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, vol.90, no.13, pp.2384-2394, 2020 (SCI-Expanded, Scopus) identifier identifier

  • Publication Type: Article / Article
  • Volume: 90 Issue: 13
  • Publication Date: 2020
  • Doi Number: 10.1080/00949655.2020.1777294
  • Journal Name: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Business Source Elite, Business Source Premier, CAB Abstracts, Communication Abstracts, Metadex, Veterinary Science Database, zbMATH, Civil Engineering Abstracts
  • Page Numbers: pp.2384-2394
  • Hacettepe University Affiliated: Yes

Abstract

In this study, the hypothesis test for the population mean of inverse Gaussian distribution using ranked set sampling is considered when the scale parameter is both known and unknown. In order to obtain critical values, a simulation study is conducted for different sample sizes and significance levels. Also, power comparisons are made between ranked set sampling and simple random sampling for the inverse Gaussian distribution. The simulation results show that ranked set sampling performs much better compared to simple random sampling when the underlying distribution is inverse Gaussian.