Jones, M. C.
|DOI (Digital Object Identifier) Link:||http://doi.org/10.1093/biomet/78.3.511|
|Google Scholar:||Look up in Google Scholar|
A new kernel density estimator for length biased data which derives from smoothing the nonparametric maximum likelihood estimator is proposed and investigated. It has various advantages over an alternative method suggested by Bhattacharyya, Franklin & Richardson (1988): it is necessarily a probability density, it is particularly better behaved near zero, it has better asymptotic mean integrated squared error properties and it is more readily extendable to related problems such as density derivative estimation.
|Item Type:||Journal Article|
|Copyright Holders:||1991 Biometrika Trust|
|Keywords:||density estimation; nonparametric maximum likelihood estimator; smoothing; weighted distribution|
|Academic Unit/Department:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Depositing User:||Sarah Frain|
|Date Deposited:||22 Mar 2011 11:57|
|Last Modified:||04 Oct 2016 11:01|
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