spatstat.explore

Exploratory/nonparametric data analysis for the spatstat family

You are viewing the GitHub repository which holds the latest development version of spatstat.explore. For the latest public release on CRAN, see the CRAN page.

Overview of spatstat.explore
Detailed contents of package
Installing the package
Bug reports
Questions
Proposing changes to code
Future development

Overview of `spatstat.explore`

The original spatstat package has been split into several sub-packages (See spatstat/spatstat)

This package spatstat.explore is one of the sub-packages. It contains the main user-level functions that perform exploratory and nonparametric statistical analysis of spatial data, with the exception of data on linear networks.

Most of the functionality is for spatial point patterns in two dimensions. There is a very modest amount of functionality for 3D and higher dimensional patterns and space-time patterns.

spatstat.explore supports

data manipulation and exploratory graphics
exploratory analysis
smoothing
cluster detection
nonparametric estimation
hypothesis tests (simulation-based and nonparametric)

Detailed contents of `spatstat.explore`

For a full list of functions, see the help file for spatstat.explore-package.

Exploratory analysis

Clark-Evans index, Hopkins-Skellam index
quadrat counting estimates of intensity, quadrat counting test
Fry plot
Morisita plot
scan statistic
cluster detection (Allard-Fraley cluster set, Byers-Raftery cleaning)

Nonparametric estimation of trend

kernel estimation of intensity of a point pattern
kernel smoothing of mark values attached to point locations
kernel estimation of relative risk
kernel smoothing of a line segment pattern
bandwidth selection
spatial CDF
nonparametric estimation of intensity as a function of a covariate
ROC curve, AUC
Sufficient Data Reduction
optimal thresholding of a covariate

Nonparametric estimation of dependence between points

summary functions (K-function, pair correlation function, empty space function, nearest neighbour distance function, J-function, etc) and multi-type versions of these functions
mark correlation function, mark independence diagnostic
local summary functions (LISA)
simulation envelopes of summary functions
manipulation of summary functions (plot, evaluate, differentiate, smooth etc)

Formal inference

spatial bootstrap
asymptotic variance estimates
hypothesis tests (quadrat test, Clark-Evans test, Berman test, Diggle-Cressie-Loosmore-Ford test, scan test, studentised permutation test, segregation test, envelope tests, Dao-Genton test, balanced independent two-stage test)

Data manipulation

image blurring
Choi-Hall data sharpening of point locations
transects of an image along a line or curve
programming tools

Installing the package

This repository contains the development version of spatstat.explore. The easiest way to install the development version is to start R and type

repo <- c('https://spatstat.r-universe.dev', 'https://cloud.r-project.org')
install.packages("spatstat.explore", dependencies=TRUE, repos=repo)

To install the latest public release of spatstat.explore, type

install.packages("spatstat.explore")

Bug reports

Users are encouraged to report bugs. If you find a bug in a spatstat function, please identify the sub-package containing that function. Visit the GitHub repository for the sub-package, click the Issues tab at the top of the page, and press new issue to start a new bug report, documentation correction or feature request.

Please do not post questions on the Issues pages, because they are too clunky for correspondence.

Questions about spatstat

For questions about the spatstat package family, first check the question-and-answer website stackoverflow to see whether your question has already been asked and answered. If not, you can either post your question at stackoverflow, or email the authors.

Proposing changes to the code

Feel free to fork spatstat.explore, make changes to the code, and ask us to include them in the package by making a github pull request.

Future development

The spatstat package family is the result of 30 years of software development and contains over 200,000 lines of code. It is still under development, motivated by the needs of researchers in many fields, and driven by innovations in statistical science. We welcome contributions of code, and suggestions for improvements.