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

DOI10.1080/00949655.2017.1319948OpenAlexW2611801942MaRDI QIDQ5106919

Yusuf Can Sevil, Tugba Ozkal Yildiz

Publication date: 22 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2017.1319948

zbMATH Keywords

goodness-of-fit testranked set samplingauxiliary variableslevel-2 sampling designPROS

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (6)

Empirical distribution function estimators based on sampling designs in a finite population using single auxiliary variable ⋮ New distribution function estimators and tests of perfect ranking in concomitant-based ranked set sampling ⋮ Design-based estimators of the distribution function in ranked set sampling with an application ⋮ Unnamed Item ⋮ Unnamed Item ⋮ Performances of some goodness-of-fit tests for sampling designs in ranked set sampling

Cites Work

• Unnamed Item
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• Quantile inference based on partially rank-ordered set samples
• Two sample distribution-free inference based on partially rank-ordered set samples
• Estimation of population mean and total in a finite population setting using multiple auxiliary variables
• EDF-based goodness-of-fit tests for ranked-set sampling
• Characterization of a Ranked-Set Sample with Application to Estimating Distribution Functions

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