Estimation of Distribution Function under Multistage Median Ranked Set Sampling

Samuh, Monjed H.

dc.contributor.author	Samuh, Monjed H.
dc.date.accessioned	2019-10-08T11:02:32Z
dc.date.accessioned	2022-05-22T08:52:07Z
dc.date.available	2019-10-08T11:02:32Z
dc.date.available	2022-05-22T08:52:07Z
dc.date.issued	2018-11
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/8050
dc.description.abstract	As a modification of ranked set sampling (RSS), multistage median RSS (MMRSS), is used for distribution function estimation. The performance of the empirical distribution function obtained by MMRSS is examined in terms of relative efficiency. The effect of the set size, number of cycles, and number of stages of MMRSS on the performance of the proposed estimator is addressed. Generally speaking, the empirical distribution function when using MMRSS is more efficient than when using simple random sampling for some quantiles. The comparison is carried out theoretically and numerically.	en_US
dc.language.iso	en_US	en_US
dc.publisher	ISOSS Journal of Applied Probability and Statistics	en_US
dc.subject	Distribution function estimation, efficiency, ranked set sampling, Simple random sampling	en_US
dc.title	Estimation of Distribution Function under Multistage Median Ranked Set Sampling	en_US
dc.type	Article	en_US