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Description

Spatio-Temporal Adaptive Kernel Estimators for Intensities.

Adaptive estimation of the first-order intensity function of a spatio-temporal point process using kernels and variable bandwidths. The methodology used for estimation is presented in González and Moraga (2022). <arXiv:2208.12026>.

kernstadapt

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:

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)

Main functions

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()

Amazon fires intensity

Variable bandwidth in a spatio-temporal point pattern

Metadata

Version

0.0.2

License

Unknown

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