Jones, M. C.
|DOI (Digital Object Identifier) Link:||http://doi.org/10.1016/0167-7152(91)90163-L|
|Google Scholar:||Look up in Google Scholar|
There is disagreement in the literature concerning the roles of integrated squared error (ISE) and mean integrated squared error (MISE) in kernel density estimation. The issues are reviewed. If best estimation of the underlying density is truly considered to be the objective, conclusions are that ISE is more appropriate than MISE for assessing the performance of density estimates using data-based bandwidth choices and, relatedly, that, in choosing bandwidths initially, aiming for the ISE-optimal bandwidth is more appropriate than aiming for the MISE-optimal target. However, it turns out that practical procedures based on MISE considerations remain one particularly sensible way to go about making automatic bandwidth selections aimed at the ISE-optimal target. Moreover, it is then argued that hoping to be able to estimate a density well from every data set associated with it is unrealistic and that one can only expect to do well in some average sense. This leads back to a conceptual preference for MISE-related procedures, a viewpoint the author commends for general use.
|Item Type:||Journal Article|
|Copyright Holders:||Elsevier Science B.V.|
|Keywords:||adaptive procedure; bandwidth selection; kernel estimation; risk function; squared error|
|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:||17 Mar 2011 15:29|
|Last Modified:||02 Aug 2016 14:00|
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