Learn R Programming

spatstat.explore (version 3.4-2)

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.

Copy Link

Version

Install

install.packages('spatstat.explore')

Monthly Downloads

61,089

Version

3.4-2

License

GPL (>= 2)

Maintainer

Adrian Baddeley

Last Published

March 21st, 2025

Functions in spatstat.explore (3.4-2)

Diagnostics for random marking

Empty Space Function of a Three-Dimensional Point Pattern

Inhomogeneous Empty Space Function

Estimate the Empty Space Function or its Hazard Rate

Subset of spatially sampled function

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

Inhomogeneous Marked F-Function

Extract or Replace Subset of Function Values

Extract Subset of Function Array

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

Marked Nearest Neighbour Distance Function

Inhomogeneous Multitype G Cross Function

Inhomogeneous Marked G-Function

Spherical Contact Distribution Function

Inhomogeneous Multitype G Dot Function

Nearest Neighbour Distance Function G

Integrated Squared Error on an Envelope Object

Foxall's Distance Functions

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

Inhomogeneous Nearest Neighbour Function

Inhomogeneous Multitype J function (i-to-any)

Multitype J Function (i-to-j)

Estimate the I-function

K-function of a Three-Dimensional Point Pattern

Estimate the J-function

Inhomogeneous Multitype J function (i-to-j)

Inhomogeneous Marked J-Function

Multitype J Function (i-to-any)

Inhomogeneous J-function

Marked J Function

Reduced Second Moment Measure

Inhomogeneous K-function

K-function using FFT

Inhomogeneous Cross K Function

Multitype K Function (Cross-type)

Mark-Weighted K Function

Multitype K Function (i-to-any)

Inhomogeneous Multitype K Dot Function

Marked K-Function

Inhomogeneous Marked K-Function

Inhomogeneous Multitype L Dot Function

Inhomogeneous L-function

Mean Integrated Squared Error on an Envelope Object

Sector K-function

Locally Scaled K-function

Inhomogeneous Cross Type L Function

SpatialQuantile.ppp

Spatially Weighted Quantile of Values at Points

Multitype L-function (i-to-any)

Multitype L-function (cross-type)

S3 Group Generic Methods for Function Arrays

Third order summary statistic

S3 Group Generic Methods for Function Tables

Smooth a Spatially Sampled Function

Apply Smoothing to Function Values

as.data.frame.envelope

Coerce Envelope to Data Frame

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

Spatial Smoothing of Data by Diffusion

Convert Function Value Table to Function

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

as.owin.quadrattest

Convert Data To Class owin

bw.CvL.adaptive

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

Spatial smoothing of data

Calculate four standard summary functions of a point pattern.

Calculate Summary Statistic for All Types in a Multitype Point Pattern

Spatial smoothing of observations at irregular points

Convert Data To Tessellation

Scott's Rule for Bandwidth Selection for Kernel Density

Bandwidth Selection for Diffusion Smoother by Cronie-van Lieshout Rule

Spatial Smoothing of Observations using Diffusion Estimate of Density

as.function.rhohat

Convert Function Table to Function

Abramson's Adaptive Bandwidths For Spatial Point Pattern

Cross Validated Bandwidth Selection for Spatial Smoothing

Progress Plot of Test of Spatial Pattern

Collapse Several Function Tables into One

Smooth Interpolation of Marks as a Spatial Function

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

SpatialMedian.ppp

Spatially Weighted Median of Values at Points

compatible.fasp

Test Whether Function Arrays Are Compatible

Convert Data To Class fv

Balanced Independent Two-Stage Monte Carlo Test

Calculate Derivative of Function Values

SpatialQuantile

Spatially Weighted Median or Quantile

Likelihood Cross Validation Bandwidth Selection for Kernel Density

densityAdaptiveKernel.ppp

Adaptive Kernel Estimate of Intensity of Point Pattern

Apply Gaussian Blur to a Pixel Image

Area Under ROC Curve

Global Envelopes for Dao-Genton Test

densityAdaptiveKernel.splitppp

Adaptive Kernel Estimate of Intensity for Split Point Pattern

Distribution Function of Interpoint Distance

domain.quadrattest

Extract the Domain of any Spatial Object

Simulation Envelopes of Summary Function for 3D Point Pattern

Window.quadrattest

Extract Window of Spatial Object

adaptive.density

Adaptive Estimate of Intensity of Point Pattern

Bandwidth Selection for Diffusion Smoother by Likelihood Cross-Validation

Combine Function Value Tables

Global Envelopes for Balanced Independent Two-Stage Test

Test Whether Function Objects Are Compatible

Berman's Tests for Point Process Model

Cross Validated Bandwidth Selection for Relative Risk Estimation

Bandwidth Selection Based on Window Geometry

Array of Simulation Envelopes of Summary Function

bw.optim.object

Class of Optimized Bandwidths

Generic Calculation of Cumulative Distribution Function of Distances

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

Function Arrays for Spatial Patterns

Local Multitype K Function (Dot-Type)

Extract or Change the Plot Formula for a Function Value Table

Fry Plot of Point Pattern

Spatial Distribution Test for Point Pattern or Point Process Model

Diffusion Estimate of Point Pattern Intensity

Create a Function Value Table

bw.relriskHeatppp

Bandwidth Selection for Relative Risk using Diffusion

clarkevans.test

Clark and Evans Test

Adjust Bandwidth Selection Rule to Account for Inhomogeneity

densityHeat.ppp

Diffusion Estimate of Point Pattern Intensity

Inhomogeneous Neighbourhood Density Function

Cross Validated Bandwidth Selection for Kernel Density

Allard-Fraley Estimator of Cluster Feature

Cross Validated Bandwidth Selection for Pair Correlation Function

Cross Validated Bandwidth Selection for Inhomogeneous Pair Correlation Function

Generic Calculation of K Function and Pair Correlation Function

Covariance and Correlation between Images

Kernel Smoothing of Line Segment Pattern

Density Estimation for Circular Data

Intensity Estimate of Point Pattern Using Voronoi-Dirichlet Tessellation

density.splitppp

Kernel Smoothed Intensity of Split Point Pattern

Kernel Estimate of Intensity as a Spatial Function

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

Ripley's Isotropic Edge Correction

Kernel Smoothed Intensity of Point Pattern

Progress Plot of Dao-Genton Test of Spatial Pattern

Function Value Table

Clark and Evans Aggregation Index

Laslett's Transform

Abbreviations for Groups of Columns in Function Value Table

Translation Edge Correction

Methods for Spatially Sampled Functions

Dao-Genton Adjusted Goodness-Of-Fit Test

Mark Connection Function

Neighbourhood density function

Mark Cross-Correlation Function

Heat Kernel for a Two-Dimensional Rectangle

Morisita Index Plot

Significance Trace of Dao-Genton Test

Estimate Dimension of Central Subspace

Evaluate Expression Involving Function Arrays

Inverse-distance weighted smoothing of observations at irregular points

Pair Correlation Function

Simulation Envelopes of Summary Function

Mark Correlation Function

Tabulate Marks in Neighbourhood of Every Point in a Point Pattern

envelope.envelope

Recompute Envelopes

Evaluate Expression Involving Functions

Increments of a Function

markmarkscatter

Mark-Mark Scatter Plot

Compute Integral of Function Object

Pair Correlation Function obtained from K Function

Pair Correlation Function of Point Pattern

Make Function Tables Compatible

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

Inhomogeneous Pair Correlation Function

Local pair correlation function

Pair Correlation Function obtained from array of K functions

Local Multitype K Function (Cross-Type)

Mean of a Function of Interpoint Distance

Pool Data from a List of Objects

Point Pair Orientation Distribution

Hopkins-Skellam Test

Plot Result of Scan Test

Pair Correlation Function of a Three-Dimensional Point Pattern

Plot a Spatially Sampled Function

Bootstrap Confidence Bands for Summary Function

Marked pair correlation function

Multitype pair correlation function (cross-type)

localKcross.inhom

Inhomogeneous Multitype K Function

Nearest Neighbour Clutter Removal

Nearest-Neighbour Correlation Indices of Marked Point Pattern

Plot a Function Array

plot.bermantest

Plot Result of Berman Test

methods.rho2hat

Methods for Intensity Functions of Two Spatial Covariates

Scatterplot Matrix for Pixel Images

Panel Plots using Colour Image or Contour Lines

Plot a Spatial Distribution Test

Plot a Simulation Envelope

Pool Data from Several Envelopes

Plot Function Values

Pool Data from Several Function Arrays

Contact Distribution Function using Rectangular Structuring Element

Rotational Average of a Pixel Image

ptwise.envelope

Pointwise Statistics on an Envelope Object

Spatial Scan Test

Plot Laslett Transform

Pool Several Functions

reload.or.compute

Perform Computations or Retrieve Results From File

plot.quadrattest

Display the result of a quadrat counting test.

Dispersion Test for Spatial Point Pattern Based on Quadrat Counts

Estimate of Spatially-Varying Relative Risk

Methods for Intensity Functions of Spatial Covariate

Estimate Intensity of Point Pattern Using Nearest Neighbour Distances

spatstat.explore-internal

Internal spatstat.explore functions

Spatial Cumulative Distribution Function

quadrat.test.splitppp

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

Receiver Operating Characteristic

Nonparametric Estimate of Spatially-Varying Relative Risk

Diffusion Estimate of Conditional Probabilities

spatstat.explore-package

The spatstat.explore Package

Data Sharpening of Point Pattern

Radial Cumulative Integral

Confidence Interval for Threshold of Numerical Predictor

thresholdSelect

Select Threshold to Convert Numerical Predictor to Binary Predictor

Estimate the Spatial Covariance Function of a Random Field

Compute Predictors from Sufficient Dimension Reduction

Nearest Neighbour Orientation Distribution

spatstat.explore-deprecated

Deprecated spatstat.explore functions

Spatially Sampled Function

segregation.test

Test of Spatial Segregation of Types

Inhomogeneous Multitype Pair Correlation Function (Cross-Type)

Stienen Diagram

Pixel Values Along a Transect

Multitype pair correlation function (i-to-any)

plot.studpermutest

Plot a Studentised Permutation Test

Studentised Permutation Test

subspaceDistance

Distance Between Linear Spaces

pool.quadrattest

Pool Several Quadrat Tests

Pool Data from Several Ratio Objects

Estimate Variance of Summary Statistic by Subdivision

Smoothed Relative Density of Pairs of Covariate Values

Nonparametric Estimate of Intensity as Function of a Covariate

Likelihood Ratio Test Statistic for Scan Test

Sufficient Dimension Reduction

Evaluate an Expression in a Function Table

Evaluate Expression in a Spatially Sampled Function