Jones, M. C.
|DOI (Digital Object Identifier) Link:||http://doi.org/10.1007/BF02562622|
|Google Scholar:||Look up in Google Scholar|
Recent papers of Copas (1995), Hjort and Jones (1996) and Loader (1996) have developed closely related methods for “local likelihood” density estimation. In various places, however, a more “simple-minded” and explicit analogue of local polynomial fitting in regression has been proposed for density estimation. By introducing the usual kind of binning procedure into Hjor and Jones' method, it is shown how the more and less sophisticated versions can be reconciled. Also, we attempt to understand better the role of the attractive subclass of local likelihood methodology proposed by Loader. Finally, we look at a further subset of methods and make some theoretical comparisons between members of this class.
|Item Type:||Journal Article|
|Copyright Holders:||1996 Springer Science + Business Media|
|Keywords:||kernel smoothing; local linear regression; semiparametric density estimation; transformations|
|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:||02 Jun 2011 11:59|
|Last Modified:||02 Aug 2016 13:51|
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