New Nonparametric Ranked Set Sampling

dc.contributor.author	Bhoj , Dinesh S.
dc.date.accessioned	2018-08-01T05:35:19Z
dc.date.available	2018-08-01T05:35:19Z
dc.date.issued	2016
dc.identifier.issn	2384-4795
dc.identifier.uri	https://journal.uob.edu.bh:443/handle/123456789/2024
dc.description.abstract	A new nonparametric ranked set sampling (NNRSS) procedure is proposed to estimate the mean of a population. The estimator based on NNRSS is compared with the estimators based on ranked set sampling (RSS) and median ranked set sampling (MRSS) procedures. It is shown that the relative precisions of the estimators based on NNRSS are higher than those based on RSS and MRSS schemes for unimodal symmetric distributions around the mean and the distributions with low skewness.	en_US
dc.language.iso	en	en_US
dc.publisher	University of Bahrain	en_US
dc.rights	Attribution-NonCommercial-ShareAlike 4.0 International	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-sa/4.0/	*
dc.subject	Laplace distribution
dc.subject	Logistic distribution
dc.subject	Mean square error
dc.subject	Median ranked set sampling
dc.subject	Normal distribution
dc.subject	Ranked set sampling
dc.subject	Relative precision
dc.subject	Skew distributions
dc.subject	Symmetric distribution
dc.title	New Nonparametric Ranked Set Sampling	en_US
dc.type	Article	en_US
dc.identifier.doi	http://dx.doi.org/10.12785/IJCTS/030103
dc.volume	03
dc.issue	01
dc.source.title	International Journal of Computational and Theoretical Statistics
dc.abbreviatedsourcetitle	IJCTS