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Kernel estimation of relative risk.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Kernel estimation of relative risk. / Kelsall, Julia E.; Diggle, Peter J.
In: Bernoulli, Vol. 1, No. 1-2, 1995, p. 3-16.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Kelsall, JE & Diggle, PJ 1995, 'Kernel estimation of relative risk.', Bernoulli, vol. 1, no. 1-2, pp. 3-16. <http://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.bj/1186078359>

APA

Kelsall, J. E., & Diggle, P. J. (1995). Kernel estimation of relative risk. Bernoulli, 1(1-2), 3-16. http://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.bj/1186078359

Vancouver

Kelsall JE, Diggle PJ. Kernel estimation of relative risk. Bernoulli. 1995;1(1-2):3-16.

Author

Kelsall, Julia E. ; Diggle, Peter J. / Kernel estimation of relative risk. In: Bernoulli. 1995 ; Vol. 1, No. 1-2. pp. 3-16.

Bibtex

@article{6304a9e242b04a0fbc76517becd00cb3,
title = "Kernel estimation of relative risk.",
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.",
keywords = "cross-validation, epidemiology, kernel density estimation, smoothing parameters",
author = "Kelsall, {Julia E.} and Diggle, {Peter J.}",
year = "1995",
language = "English",
volume = "1",
pages = "3--16",
journal = "Bernoulli",
issn = "1350-7265",
publisher = "International Statistical Institute",
number = "1-2",

}

RIS

TY - JOUR

T1 - Kernel estimation of relative risk.

AU - Kelsall, Julia E.

AU - Diggle, Peter J.

PY - 1995

Y1 - 1995

N2 - 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.

AB - 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.

KW - cross-validation

KW - epidemiology

KW - kernel density estimation

KW - smoothing parameters

M3 - Journal article

VL - 1

SP - 3

EP - 16

JO - Bernoulli

JF - Bernoulli

SN - 1350-7265

IS - 1-2

ER -