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:

{r, eval=FALSE} install.packages("kernstadapt")

The development version can be installed using devtools:

{r, eval=FALSE} # install.packages("devtools") # if not already installed devtools::install_github("jagm03/kernstadapt") library(kernstadapt)

Main functions

Direct adaptive estimation of the intensity

Adaptive intensity estimation using a partition algorithm

Bandwidths calculation

Separability test

Amazon fires intensity
Variable bandwidth in a spatio-temporal point pattern