Tutorial on kernel estimation of continuous spatial and spatiotemporal relative risk

Volume: 37, Issue: 7, Pages: 1191 - 1221
Published: Dec 11, 2017
Abstract
Kernel smoothing is a highly flexible and popular approach for estimation of probability density and intensity functions of continuous spatial data. In this role, it also forms an integral part of estimation of functionals such as the density-ratio or “relative risk” surface. Originally developed with the epidemiological motivation of examining fluctuations in disease risk based on samples of cases and controls collected over a given...
Paper Details
Title
Tutorial on kernel estimation of continuous spatial and spatiotemporal relative risk
Published Date
Dec 11, 2017
Volume
37
Issue
7
Pages
1191 - 1221
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