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).

Installation

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

dens.direct() (non-separable)

dens.direct.sep() (separable)

Adaptive intensity estimation using a partition algorithm