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spatialkernel

An R package for nonparametric estimation of spatial segregation in a multivariate point process. Contains functionality for edge-corrected kernel density estimation and binary kernel regression estimation for multivariate spatial point process data.

The original spatialkernel package has been archived from CRAN. This version fixes failing checks, with the intention of having it restored to CRAN. Original import to github and fixes by @richierocks.

Installation

You can install spatialkernel from github with:

# install.packages("devtools")
devtools::install_github("becarioprecario/spatialkernel")

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Install

install.packages('spatialkernel')

Monthly Downloads

74

Version

0.4-23

License

CC BY-NC-SA 4.0

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Last Published

August 8th, 2017

Functions in spatialkernel (0.4-23)

kinhat

Inhomogeneous K-function Estimation Estimate the inhomogeneous K function of a non-stationary point pattern.
lambdahat

Kernel Density Estimation of Intensity Function
data

Lansing Woods Trees
filled.contour.poly

areapoly

Signed Area of Polygon
cvloglk

Cross-Validated Log-Likelihood Function Calculate the cross-validated log-likelihood function.
metre

Plot Color Level Metre
package.version

Listing Loaded/Installed Package Versions List version numbers of loaded or installed packages.
mcpat.test

Monte Carlo Inference of Temporal Changes in Spatial Segregation An approximate Monte Carlo test of temporal changes in a multivariate spatial-temporal point process.
mcseg.test

Monte Carlo Test of Spatial Segregation in Multivariate Point Process
risk.colors

Color Palette
setkernel

Select Smoothing Kernel Function
phat

Estimate Type-Specific Probabilities
pinpoly

Check if Points are within Polygon
spatialkernel-package

The Spatialkernel Package
spseg.matrix

Integrated Functions for Spatial Segregation Analysis Spatial segregation analysis to be performed by a single function and presentations by associated plot functions.