Analysing point patterns on networks—A review
We review recent research on statistical methods for analysing spatial patterns of points on a
network of lines, such as road accident locations along a road network. Due to geometrical …
network of lines, such as road accident locations along a road network. Due to geometrical …
Tutorial on kernel estimation of continuous spatial and spatiotemporal relative risk
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 …
density and intensity functions of continuous spatial data. In this role, it also forms an integral …
[BUCH][B] Multivariate kernel smoothing and its applications
Kernel smoothing has greatly evolved since its inception to become an essential
methodology in the data science tool kit for the 21st century. Its widespread adoption is due …
methodology in the data science tool kit for the 21st century. Its widespread adoption is due …
Adaptive kernel estimation of spatial relative risk
Kernel smoothing is routinely used for the estimation of relative risk based on point locations
of disease cases and sampled controls over a geographical region. Typically, fixed …
of disease cases and sampled controls over a geographical region. Typically, fixed …
Sparr: analyzing spatial relative risk using fixed and adaptive kernel density estimation in R
The estimation of kernel-smoothed relative risk functions is a useful approach to examining
the spatial variation of disease risk. Though there exist several options for performing kernel …
the spatial variation of disease risk. Though there exist several options for performing kernel …
Fast kernel smoothing of point patterns on a large network using two‐dimensional convolution
We propose a computationally efficient and statistically principled method for kernel
smoothing of point pattern data on a linear network. The point locations, and the network …
smoothing of point pattern data on a linear network. The point locations, and the network …
[HTML][HTML] Prevalence and risk-map** of bovine brucellosis in Maranhão State, Brazil
MR Borba, MA Stevenson, VSP Gonçalves… - Preventive veterinary …, 2013 - Elsevier
Between 2007 and 2009, a cross-sectional survey was carried out in Maranhão State, Brazil
to estimate the seroprevalence of and risk factors for bovine brucellosis. In total, 749 herds …
to estimate the seroprevalence of and risk factors for bovine brucellosis. In total, 749 herds …
Fast computation of spatially adaptive kernel estimates
Kernel smoothing of spatial point data can often be improved using an adaptive, spatially
varying bandwidth instead of a fixed bandwidth. However, computation with a varying …
varying bandwidth instead of a fixed bandwidth. However, computation with a varying …
Bayesian nonparametric general regression with adaptive kernel bandwidth and its application to seismic attenuation
Abstract General Regression Neural Network (GRNN) possesses distinct function
approximation capability and predictive power without the requirement of a prescribed …
approximation capability and predictive power without the requirement of a prescribed …
Bivariate frequency analysis of floods using a diffusion based kernel density estimator
D Santhosh, VV Srinivas - Water Resources Research, 2013 - Wiley Online Library
Recent focus of flood frequency analysis (FFA) studies has been on development of
methods to model joint distributions of variables such as peak flow, volume, and duration …
methods to model joint distributions of variables such as peak flow, volume, and duration …