A comparison of estimators of the geographical relative risk function

DOI10.1080/00949655.2012.748055zbMath1453.62723OpenAlexW2066195254MaRDI QIDQ5220001

S. Ganesalingam, W. T. P. S. Fernando, Martin L. Hazelton

Publication date: 9 March 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2012.748055

zbMATH Keywords

bandwidthkernel smoothingplug-incross-validationspatial smoothingdensity ratiolocal linear

Mathematics Subject Classification ID

Density estimation (62G07) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (2)

Symmetric adaptive smoothing regimens for estimation of the spatial relative risk function ⋮ Shrinkage estimators of the spatial relative risk function

Uses Software

• KernSmooth
• pyuvdata

Cites Work

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• An evaluation of non-parametric relative risk estimators for disease maps
• A flexible spatial scan test for case event data
• Kernel estimation of relative risk
• Local Likelihood Estimation
• Spatial Variation in Risk of Disease: A Nonparametric Binary Regression Approach
• Plug-in bandwidth matrices for bivariate kernel density estimation
• Local Polynomial Kernel Regression for Generalized Linear Models and Quasi-Likelihood Functions
• Inference Based on Kernel Estimates of the Relative Risk Function in Geographical Epidemiology
• Comparison of Smoothing Parameterizations in Bivariate Kernel Density Estimation
• Kernel Estimators for Univariate Binary Regression

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