Journal
SPATIAL AND SPATIO-TEMPORAL EPIDEMIOLOGY
Volume 5, Issue -, Pages 51-65Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.sste.2013.04.001
Keywords
Asymptotic error; Case-control; Geographical epidemiology; Kernel density estimation; Relative risk surface
Categories
Funding
- early-career University of Otago Research Grant-in-aid (UORG): Spatial Methods for Intensity Estimation and their Performance in Epidemiology''
Ask authors/readers for more resources
The kernel-smoothed density-ratio or 'relative risk' function for planar point data is a useful tool for examining disease rates over a certain geographical region. Instrumental to the quality of the resulting risk surface estimate is the choice of bandwidth for computation of the required numerator and denominator densities. The challenge associated with finding some 'optimal' smoothing parameter for standalone implementation of the kernel estimator given observed data is compounded when we deal with the density-ratio per se. To date, only one method specifically designed for calculation of density-ratio optimal bandwidths has received any notable attention in the applied literature. However, this method exhibits significant variability in the estimated smoothing parameters. In this work, the first practical comparison of this selector with a little-known alternative technique is provided. The possibility of exploiting an asymptotic MISE formulation in an effort to control excess variability is also examined, and numerical results seem promising. (C) 2013 Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available