["page_head" not defined] ["page_js" not defined] ["page_preload" not defined]
["page_header" not defined]

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

Full text not available from this repository.


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: Journal Article
Journal or Publication Title: Bernoulli
Uncontrolled Keywords: /dk/atira/pure/researchoutput/libraryofcongress/qa
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: 14 Dec 2019 06:08
URI: https://eprints.lancs.ac.uk/id/eprint/19573

Actions (login required)

View Item View Item
["page_footer" not defined]