Estimation of Distribution Function under Multistage Median Ranked Set Sampling

dc.contributor.authorSamuh, Monjed H.
dc.date.accessioned2019-10-08T11:02:32Z
dc.date.accessioned2022-05-22T08:52:07Z
dc.date.available2019-10-08T11:02:32Z
dc.date.available2022-05-22T08:52:07Z
dc.date.issued2018-11
dc.description.abstractAs 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.identifier.urihttp://localhost:8080/xmlui/handle/123456789/8050
dc.language.isoen_USen_US
dc.publisherISOSS Journal of Applied Probability and Statisticsen_US
dc.subjectDistribution function estimation, efficiency, ranked set sampling, Simple random samplingen_US
dc.titleEstimation of Distribution Function under Multistage Median Ranked Set Samplingen_US
dc.typeArticleen_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
13(2)3 12001.pdf
Size:
82.06 KB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Plain Text
Description: