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spatstat.explore (version 3.5-2)

Exploratory Data Analysis for the 'spatstat' Family

Description

Functionality for exploratory data analysis and nonparametric analysis of spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) Methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported.

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Version

Install

install.packages('spatstat.explore')

Monthly Downloads

56,843

Version

3.5-2

License

GPL (>= 2)

Maintainer

Adrian Baddeley

Last Published

July 22nd, 2025

Functions in spatstat.explore (3.5-2)

Subset of spatially sampled function

Estimate the Empty Space Function or its Hazard Rate

Diagnostics for random marking

Inhomogeneous Empty Space Function

Extract Subset of Function Array

Empty Space Function of a Three-Dimensional Point Pattern

Multitype Nearest Neighbour Distance Function (i-to-j)

Inhomogeneous Multitype G Dot Function

Spherical Contact Distribution Function

Inhomogeneous Multitype G Cross Function

Marked Nearest Neighbour Distance Function

Nearest Neighbour Distance Function G

Multitype Nearest Neighbour Distance Function (i-to-any)

Foxall's Distance Functions

Integrated Squared Error on an Envelope Object

Inhomogeneous Nearest Neighbour Function

Inhomogeneous Marked G-Function

Inhomogeneous Multitype J function (i-to-any)

Inhomogeneous Marked J-Function

Inhomogeneous J-function

Estimate the I-function

K-function of a Three-Dimensional Point Pattern

Multitype J Function (i-to-j)

Estimate the J-function

Marked J Function

Multitype J Function (i-to-any)

Inhomogeneous Multitype J function (i-to-j)

Marked K-Function

Reduced Second Moment Measure

Multitype K Function (Cross-type)

K-function using FFT

Multitype K Function (i-to-any)

Inhomogeneous K-function

Inhomogeneous Multitype K Dot Function

Mark-Weighted K Function

Inhomogeneous Cross K Function

Multitype L-function (i-to-any)

Multitype L-function (cross-type)

Sector K-function

Inhomogeneous Cross Type L Function

Inhomogeneous Multitype L Dot Function

Locally Scaled K-function

Inhomogeneous Marked K-Function

Mean Integrated Squared Error on an Envelope Object

Inhomogeneous L-function

S3 Group Generic Methods for Function Arrays

Apply Smoothing to Function Values

S3 Group Generic Methods for Function Tables

Smooth Interpolation of Marks as a Spatial Function

Spatial Smoothing of Observations using Diffusion Estimate of Density

Spatial smoothing of data

Transform a Function into its P-P or Q-Q Version

SpatialMedian.ppp

Spatially Weighted Median of Values at Points

Smooth a Spatially Sampled Function

Spatial Smoothing of Data by Diffusion

Calculate four standard summary functions of a point pattern.

as.data.frame.envelope

Coerce Envelope to Data Frame

SpatialQuantile

Spatially Weighted Median or Quantile

Spatial smoothing of observations at irregular points

Calculate Summary Statistic for All Types in a Multitype Point Pattern

Window.quadrattest

Extract Window of Spatial Object

adaptive.density

Adaptive Estimate of Intensity of Point Pattern

SpatialQuantile.ppp

Spatially Weighted Quantile of Values at Points

Third order summary statistic

Convert Function Value Table to Function

Berman's Tests for Point Process Model

Global Envelopes for Balanced Independent Two-Stage Test

Convert Data To Tessellation

Combine Function Value Tables

Convert Data To Class fv

Balanced Independent Two-Stage Monte Carlo Test

Apply Gaussian Blur to a Pixel Image

as.owin.quadrattest

Convert Data To Class owin

Area Under ROC Curve for Point Pattern Data

as.function.rhohat

Convert Function Table to Function

Bandwidth Selection for Diffusion Smoother by Cronie-van Lieshout Rule

bw.optim.object

Class of Optimized Bandwidths

Abramson's Adaptive Bandwidths For Spatial Point Pattern

Bandwidth Selection Based on Window Geometry

Cronie and van Lieshout's Criterion for Bandwidth Selection for Kernel Density

bw.CvL.adaptive

Select Adaptive Bandwidth for Kernel Estimation Using Cronie-Van Lieshout Criterion

Adjust Bandwidth Selection Rule to Account for Inhomogeneity

Scott's Rule for Bandwidth Selection for Kernel Density

Cross Validated Bandwidth Selection for Kernel Density

Stoyan's Rule of Thumb for Bandwidth for Estimating Pair Correlation

Cross Validated Bandwidth Selection for Relative Risk Estimation

bw.relriskHeatppp

Bandwidth Selection for Relative Risk using Diffusion

Cross Validated Bandwidth Selection for Spatial Smoothing

Cross Validated Bandwidth Selection for Inhomogeneous Pair Correlation Function

Cross Validated Bandwidth Selection for Pair Correlation Function

Spatial Distribution Test for Point Pattern or Point Process Model

Bandwidth Selection for Diffusion Smoother by Likelihood Cross-Validation

Likelihood Cross Validation Bandwidth Selection for Kernel Density

Density Estimation for Circular Data

Allard-Fraley Estimator of Cluster Feature

Collapse Several Function Tables into One

Test Whether Function Objects Are Compatible

clarkevans.test

Clark and Evans Test

compatible.fasp

Test Whether Function Arrays Are Compatible

Clark and Evans Aggregation Index

Generic Calculation of K Function and Pair Correlation Function

Covariance and Correlation between Images

Generic Calculation of Cumulative Distribution Function of Distances

Progress Plot of Test of Spatial Pattern

Significance Trace of Cressie-Loosmore-Ford or Maximum Absolute Deviation Test

Kernel Smoothing of Line Segment Pattern

Diffusion Estimate of Point Pattern Intensity

density.splitppp

Kernel Smoothed Intensity of Split Point Pattern

Diggle-Cressie-Loosmore-Ford and Maximum Absolute Deviation Tests

densityHeat.ppp

Diffusion Estimate of Point Pattern Intensity

densityAdaptiveKernel.ppp

Adaptive Kernel Estimate of Intensity of Point Pattern

densityAdaptiveKernel.splitppp

Adaptive Kernel Estimate of Intensity for Split Point Pattern

Kernel Smoothed Intensity of Point Pattern

Estimate Dimension of Central Subspace

Global Envelopes for Dao-Genton Test

Distribution Function of Interpoint Distance

Calculate Derivative of Function Values

Significance Trace of Dao-Genton Test

domain.quadrattest

Extract the Domain of any Spatial Object

Progress Plot of Dao-Genton Test of Spatial Pattern

Kernel Estimate of Intensity as a Spatial Function

Intensity Estimate of Point Pattern Using Voronoi-Dirichlet Tessellation

Dao-Genton Adjusted Goodness-Of-Fit Test

Ripley's Isotropic Edge Correction

envelope.envelope

Recompute Envelopes

Evaluate Expression Involving Function Arrays

Simulation Envelopes of Summary Function for 3D Point Pattern

Function Arrays for Spatial Patterns

Simulation Envelopes of Summary Function

Translation Edge Correction

Extract or Change the Plot Formula for a Function Value Table

Array of Simulation Envelopes of Summary Function

Evaluate Expression Involving Functions

Fry Plot of Point Pattern

Create a Function Value Table

Make Function Tables Compatible

Hopkins-Skellam Test

Heat Kernel for a Two-Dimensional Rectangle

Inverse-distance weighted smoothing of observations at irregular points

Local Multitype K Function (Cross-Type)

localKcross.inhom

Inhomogeneous Multitype K Function

Increments of a Function

Compute Integral of Function Object

Local Multitype K Function (Dot-Type)

Abbreviations for Groups of Columns in Function Value Table

Function Value Table

Inhomogeneous Neighbourhood Density Function

methods.rho2hat

Methods for Intensity Functions of Two Spatial Covariates

Methods for Intensity Functions of Spatial Covariate

Neighbourhood density function

Tabulate Marks in Neighbourhood of Every Point in a Point Pattern

Nearest Neighbour Clutter Removal

Local pair correlation function

Bootstrap Confidence Bands for Summary Function

Laslett's Transform

Mark Cross-Correlation Function

Nearest-Neighbour Correlation Indices of Marked Point Pattern

Morisita Index Plot

markmarkscatter

Mark-Mark Scatter Plot

Mean of a Function of Interpoint Distance

Methods for Spatially Sampled Functions

Mark Correlation Function

Mark Connection Function

Point Pair Orientation Distribution

Pair Correlation Function obtained from array of K functions

Pair Correlation Function

Estimate Intensity of Point Pattern Using Nearest Neighbour Distances

Nearest Neighbour Orientation Distribution

Pair Correlation Function obtained from K Function

Pair Correlation Function of Point Pattern

Panel Plots using Colour Image or Contour Lines

Scatterplot Matrix for Pixel Images

Inhomogeneous Multitype Pair Correlation Function (Type-i-To-Any-Type)

Inhomogeneous Pair Correlation Function

Inhomogeneous Multitype Pair Correlation Function (Cross-Type)

Multitype pair correlation function (i-to-any)

Multitype pair correlation function (cross-type)

Pair Correlation Function of a Three-Dimensional Point Pattern

Plot a Function Array

Plot a Spatial Distribution Test

Plot Result of Scan Test

Plot a Spatially Sampled Function

Plot Laslett Transform

plot.quadrattest

Display the result of a quadrat counting test.

Plot Function Values

Marked pair correlation function

Pool Data from a List of Objects

ptwise.envelope

Pointwise Statistics on an Envelope Object

Pool Data from Several Envelopes

plot.bermantest

Plot Result of Berman Test

Plot a Simulation Envelope

Dispersion Test for Spatial Point Pattern Based on Quadrat Counts

reload.or.compute

Perform Computations or Retrieve Results From File

plot.studpermutest

Plot a Studentised Permutation Test

Receiver Operating Characteristic

Spatial Scan Test

Likelihood Ratio Test Statistic for Scan Test

Receiver Operating Characteristic

spatstat.explore-deprecated

Deprecated spatstat.explore functions

spatstat.explore-internal

Internal spatstat.explore functions

thresholdSelect

Select Threshold to Convert Numerical Predictor to Binary Predictor

Estimate Variance of Summary Statistic by Subdivision

subspaceDistance

Distance Between Linear Spaces

Confidence Interval for Threshold of Numerical Predictor

Evaluate Expression in a Spatially Sampled Function

Youden Statistic

Inhomogeneous Marked F-Function

Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern

Extract or Replace Subset of Function Values

Pool Data from Several Ratio Objects

pool.quadrattest

Pool Several Quadrat Tests

Pool Data from Several Function Arrays

Smoothed Relative Density of Pairs of Covariate Values

Pool Several Functions

Nonparametric Estimate of Intensity as Function of a Covariate

Rotational Average of a Pixel Image

Contact Distribution Function using Rectangular Structuring Element

Data Sharpening of Point Pattern

Estimate of Spatially-Varying Relative Risk

segregation.test

Test of Spatial Segregation of Types

Estimate the Spatial Covariance Function of a Random Field

quadrat.test.splitppp

Dispersion Test of CSR for Split Point Pattern Based on Quadrat Counts

Radial Cumulative Integral

Spatial Cumulative Distribution Function

Evaluate an Expression in a Function Table

Stienen Diagram

Sufficient Dimension Reduction

Spatially Sampled Function

Compute Predictors from Sufficient Dimension Reduction

Diffusion Estimate of Conditional Probabilities

Nonparametric Estimate of Spatially-Varying Relative Risk

spatstat.explore-package

The spatstat.explore Package

Studentised Permutation Test

Pixel Values Along a Transect