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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)
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()
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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