Learn R Programming

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The original spatialkernel package has been archived from CRAN.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")

Copy Link

Version

Install

install.packages('spatialkernel')

Monthly Downloads

56

Version

0.4-23

License

CC BY-NC-SA 4.0

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/becarioprecario/spatialkernel

Maintainer

Virgilio Gf3mez-Rubio

Last Published

August 8th, 2017

Functions in spatialkernel (0.4-23)

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

Kernel Density Estimation of Intensity Function

Lansing Woods Trees

filled.contour.poly

Level (Contour) Plots with Polygonal Boundary This is a revised version of the base R function filled.contour. It additionally plots a polygonal boundary.

Signed Area of Polygon

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

Plot Color Level Metre

package.version

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

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

Monte Carlo Test of Spatial Segregation in Multivariate Point Process

Select Smoothing Kernel Function

Estimate Type-Specific Probabilities

Check if Points are within Polygon

spatialkernel-package

The Spatialkernel Package

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