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Kernel estimation of relative risk.

Kelsall, Julia E. and Diggle, Peter J. (1995) Kernel estimation of relative risk. Bernoulli, 1 (1-2). pp. 3-16. ISSN 1350-7265

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Abstract

Estimation of a relative risk function using a ratio of two kernel density estimates is considered, concentrating on the problem of choosing the smoothing parameters. A cross-validation method is proposed, compared with a range of other methods and found to be an improvement when the actual risk is close to constant. In particular, theoretical and empirical comparisons demonstrate the advantage of choosing the smoothing parameters jointly. The methodology was motivated by a class of problems in environmental epidemiology, and an application in this area is described.

Item Type: Article
Journal or Publication Title: Bernoulli
Uncontrolled Keywords: cross-validation ; epidemiology ; kernel density estimation ; smoothing parameters
Subjects: Q Science > QA Mathematics
Departments: Faculty of Health and Medicine > Medicine
VC's Office
ID Code: 19573
Deposited By: ep_ss_importer
Deposited On: 11 Nov 2008 09:08
Refereed?: Yes
Published?: Published
Last Modified: 26 Jul 2012 15:32
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/19573

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