Open Access
March 1995 Kernel estimation of relative risk
Julia E. Kelsall, Peter J. Diggle
Bernoulli 1(1-2): 3-16 (March 1995).

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.

Citation

Download Citation

Julia E. Kelsall. Peter J. Diggle. "Kernel estimation of relative risk." Bernoulli 1 (1-2) 3 - 16, March 1995.

Information

Published: March 1995
First available in Project Euclid: 2 August 2007

zbMATH: 0830.62039
MathSciNet: MR1354453

Keywords: cross-validation , epidemiology , kernel density estimation , smoothing parameters

Rights: Copyright © 1995 Bernoulli Society for Mathematical Statistics and Probability

Vol.1 • No. 1-2 • March 1995
Back to Top