kernstadapt is an R package for adaptive kernel estimation of the intensity of spatio-temporal point processes.
kernstadapt implements functionalities to estimate the intensity of a spatio-temporal point pattern by kernel smoothing with adaptive bandwidth methodology when each data point has its own bandwidth associated as a function of the crowdedness of the region (in space and time) in which the point is observed.
The package presents the intensity estimation through a direct estimator and the partitioning algorithm methodology presented in González and Moraga (2022).
The stable version on CRAN can be installed using:
install.packages("kernstadapt")
The development version can be installed using devtools:
# install.packages("devtools") # if not already installed
devtools::install_github("jagm03/kernstadapt")
library(kernstadapt)
Direct adaptive estimation of the intensity
dens.direct() (non-separable)dens.direct.sep() (separable)Adaptive intensity estimation using a partition algorithm
dens.par() (non-separable)dens.par.sep() (separable)Bandwidths calculation
bw.abram.temp() (temporal)Separability test
separability.test()
