Comparing adaptive and fixed bandwidth-based kernel density estimates in spatial cancer epidemiology

sparr: Analyzing Spatial Relative Risk Using Fixed and Adaptive Kernel Density Estimation inR

(2015) Tilman M. Davies et al.   Journal of Statistical Software

A cross-sectional study on informed choice in the mammography screening programme in Germany (InEMa): a study protocol

(2014) E.-M. Berens et al.   BMJ Open

Identification of high-risk regions for schistosomiasis in the Guichi region of China: an adaptive kernel density estimation-based approach

(2013) ZHI-JIE ZHANG et al.   PARASITOLOGY

Detecting cancer clusters in a regional population with local cluster tests and Bayesian smoothing methods: a simulation study

(2013) Dorothea Lemke et al.   International Journal of Health Geographics

Multi-level geospatial modeling of human exposure patterns and vulnerability indicators

(2012) Christoph Aubrecht et al.   NATURAL HAZARDS

Adaptive normal reference bandwidth based on quantile for kernel density estimation

(2011) Jin Zhang   JOURNAL OF APPLIED STATISTICS

Narrowing the Equity Gap: The Impact of Organized versus Opportunistic Cancer Screening in Catalonia (Spain)

(2011) Josep A Espinas et al.   JOURNAL OF MEDICAL SCREENING

Inference Based on Kernel Estimates of the Relative Risk Function in Geographical Epidemiology

(2009) Martin L. Hazelton et al.   BIOMETRICAL JOURNAL

Boundary kernels for adaptive density estimators on regions with irregular boundaries

(2009) Jonathan C. Marshall et al.   JOURNAL OF MULTIVARIATE ANALYSIS

Identifying high-risk regions for schistosomiasis in Guichi, China: A spatial analysis

(2008) Zhijie Zhang et al.   ACTA TROPICA

Nonparametric spatial analysis to detect high-risk regions for schistosomiasis in Guichi, China

(2008) Zhijie Zhang et al.   TRANSACTIONS OF THE ROYAL SOCIETY OF TROPICAL MEDICINE AND HYGIENE