Two-sample inference based on one-sample ranked set sample sign statistics
Author:
mer
zt
rk a
mer
zt
rk a
| Affiliation: | a Department of Statistics, The Ohio State University, Marion, Ohio |
DOI:
10.1080/10485259908832760
Publication Frequency:
8 issues per year
Subjects:
Mathematical Economics;
Mathematical Finance;
Medical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
Formats available:
PDF
(English)
View Article:
View Article (PDF)
Abstract
A two-sample sign test is developed for ranked set samples. It is shown that the testing procedure is distribution free but requires evaluation of the incomplete beta function. Efficiency and type I error, in general, depend on the measured observations and the ratio of cycle sizes. It is shown that there is a substantial gain in the efficiency of the test even when there are ranking errors. On the other hand, the type I error is inflated for imperfect ranking. The proposed test is superior to the two-sample Mann-Whitney-Wilcoxon ranked set sample test when the underlying probability model has heavy and long tail distribution, and the number of quantified observations in each cycle is small. We provide a simple way to implement the procedure.
|
| Keywords: Confidence interval; efficiency; nonparametric test; distribution free |
| view references (15) : view citations |

Download Citation


CiteULike
Del.icio.us
BibSonomy
Connotea