Non-parametric inferences based on general unbalanced ranked-set samples

Authors
Citation
Z. Chen, Non-parametric inferences based on general unbalanced ranked-set samples, J NONPARA S, 13(2), 2001, pp. 291-310
Citations number
25
Language
INGLESE
art.tipo
Article
Categorie Soggetti
Mathematics
Journal title
JOURNAL OF NONPARAMETRIC STATISTICS
ISSN journal
1048-5252 → ACNP
Volume
13
Issue
2
Year of publication
2001
Pages
291 - 310
Database
ISI
SICI code
1048-5252(2001)13:2<291:NIBOGU>2.0.ZU;2-Q
Abstract
A general unbalanced ranked-set sample consists of independent order statis tics each of which is out of a subsample from a common population. Such dat a can arise from two situations: (a) a designed ranked-set sampling (RSS) a nd (b) certain experimental process, e.g., the r-out-of-k systems in life t esting experiments. There is no well accepted approach available so far in the literature for the effective analysis of such data. In this article, we develop methods for making inferences on various features of the populatio n such as quantile, distribution function and moments etc., based on data o f the above nature. The asymptotic properties of the methods are well estab lished. Some simulation results are also provided for the vindication of th e methods.