Please use this identifier to cite or link to this item:
|Title:||Density estimation using ranked-set sampling data||Authors:||Chen, Z.||Keywords:||Mean integrated square error
|Issue Date:||1999||Citation:||Chen, Z. (1999). Density estimation using ranked-set sampling data. Environmental and Ecological Statistics 6 (2) : 135-146. ScholarBank@NUS Repository.||Abstract:||The ranked-set sampling (RSS) is applicable in practical problems where the variable of interest for an observed item is costly or time-consuming but the ranking of a set of items according to the variable can be easily done without actual measurement. In the context of RSS, the need for density estimation arises in certain statistical procedures. The density estimation also has its own interest. In this article, we develop a method for the density estimation using RSS data. We derive the properties of the resulted density estimate and compare it with its counterpart in simple random sampling (SRS). It is shown that the density estimate using RSS data provides a better estimate of the density than the usual density estimate using SRS data. The density estimate developed in this article can well serve various purposes in the context of RSS.||Source Title:||Environmental and Ecological Statistics||URI:||http://scholarbank.nus.edu.sg/handle/10635/105082||ISSN:||13528505|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Jan 26, 2023
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.