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Edgar Allan Poe/Sullivan's Island Library
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West Ashley Library
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Village Library
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St. Paul's/Hollywood Library
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Otranto Road Library
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McClellanville Library
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Keith Summey North Charleston Library
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John's Island Library
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Hurd/St. Andrews Library
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Miss Jane's Building (Edisto Library Temporary Location)
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VARIANCE ESTIMATORS USING NON-PARAMETRIC APPROACH UNDER DIFFERENT RANKED SET SAMPLING SCHEMES.
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- Author(s): BEGUM, NAEEMA; HANIF, MUHAMMAD; SHAHZAD, USMAN; ALI, NASIR
- Source:
Journal of Science & Arts; Sep2023, Vol. 23 Issue 3, p571-586, 16p- Subject Terms:
- Source:
- Additional Information
- Abstract: Estimation of variance is a commonly discussed topic under simple random sampling (SRS) scheme. The current article deals the issue of variance estimation utilizing supplementary information with the nonparametric approach under different ranked set sampling (RSS) schemes. We propose a class of nonparametric variance estimators utilizing kernel regression [1] with different bandwidths (Plug-in and Cross-validation), under RSS schemes. Simulation study is provided utilizing diverse data sets. The comparison of simulation results has been made between the members of the proposed class with respect to the unbiased variance estimator. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of Journal of Science & Arts is the property of Journal of Science & Arts and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Abstract:
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