Power comparison of the Kolmogorov-Smirnov test under ranked set sampling and simple random sampling

Sevil Y. C., YILDIZ T.

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, vol.87, no.11, pp.2175-2185, 2017 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 87 Issue: 11
  • Publication Date: 2017
  • Doi Number: 10.1080/00949655.2017.1319948
  • Journal Name: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.2175-2185
  • Keywords: Ranked set sampling, level-2 sampling design, PROS, auxiliary variables, goodness-of-fit test, GOODNESS-OF-FIT, FINITE POPULATION, STATISTICS
  • Dokuz Eylül University Affiliated: Yes

Abstract

Many studies have been used to compare the power of several goodness-of-fit (GOF) tests under simple random sampling (SRS) and ranked set sampling (RSS). In our study, a different design procedure and ranking process in RSS are thoroughly investigated. A simulation study is conducted to compare the power of the Kolmogorov-Smirnov test under SRS and RSS with different sets and cycle sizes for several distributions. Level-2 sampling design and partially rank-ordered sets are used. Also, we benefited from auxiliary variables in the ranking process. Finally, results are presented with tables and figures. Under these conditions we show that the RSS has better performance against the SRS in finite population.