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spatstat (version 1.10-2)

Spatial Point Pattern analysis, model-fitting, simulation, tests

Description

A package for analysing spatial data, mainly Spatial Point Patterns, including multitype/marked points and spatial covariates, in any two-dimensional spatial region. Contains functions for exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns, spatial windows, and pixel images. Point process models can be fitted to point pattern data. Cluster type models are fitted by the method of minimum contrast. Very general Gibbs point process models can be fitted to point pattern data using a function ppm similar to lm or glm. Models may include dependence on covariates, interpoint interaction and dependence on marks. Fitted models can be simulated automatically. Also provides facilities for formal inference (such as chi-squared tests) and model diagnostics (including simulation envelopes, residuals, residual plots and Q-Q plots).

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Version

Install

install.packages('spatstat')

Monthly Downloads

17,668

Version

1.10-2

License

GPL version 2 or newer

Maintainer

Adrian Baddeley

Last Published

March 22nd, 2025

Functions in spatstat (1.10-2)

Test Whether Two Function Objects Are Compatible

Extract Original Data from a Fitted Point Process Model

Kernel Smoothing of Line Segment Pattern

Chorley-Ribble Cancer Data

Distance Map of Line Segment Pattern

is.multitype.ppm

Test Whether A Point Process Model is Multitype

Lansing Woods Point Pattern

Nearest-Neighbour Correlation of Marked Point Pattern

Plot a List of Point Patterns

Quadrat counting for a point pattern

California Redwoods Point Pattern (Ripley's Subset)

Extract Subset of Image

The Spatstat Package

Spokes pattern of dummy points

Extract Unique Points from a Spatial Point Pattern

The Multitype Strauss Point Process Model

Calculate Statistic for All Types in a Multitype Point Pattern

Area of a Window

Crossing Points of Two Line Segment Patterns

Simulation envelopes of summary function

Convert Point Pattern Marks from Numeric to Factor

Test Whether An Object Is A Pixel Image

pairdist.default

Pairwise distances

Simulate Matern Model II

Plot a Spatial Window

selfcrossing.psp

Crossing Points in a Line Segment Pattern

Basis for Harmonic Functions

Kaplan-Meier and Reduced Sample Estimator using Histograms

Simulate Baddeley-Silverman Cell Process

Apply Affine Transformation To Window

Generate N Random Points

Summary of a Point Pattern Dataset

Convert to Pixel Image

Sample Quantiles of Pixel Image

Pair Correlation Function obtained from array of K functions

Superimpose Several Point Patterns

Marked K-Function

The Strauss / Hard Core Point Process Model

Diagnostic Plots for Fitted Point Process Model

Profile Maximum Pseudolikelihood

Class of Line Segment Patterns

Class of Quadrature Schemes

rshift.splitppp

Randomly Shift a List of Point Patterns

Generate N Uniform Random Points

Pairwise distances

Randomly Shift a Point Pattern

Class of Point Patterns

Summarizing a Quadrature Scheme

Fit the Thomas Point Process by Minimum Contrast

Convert Data To Class ppp

Coefficients of Fitted Point Process Model

density.splitppp

Kernel Smoothed Intensity of Split Point Pattern

Distance Map of Window

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

Apply Affine Transformation To Point Pattern

Test Whether Marks Are Present

Beta Ganglion Cells in Cat Retina

complement.owin

Take Complement of a Window

Nearest neighbour

Exponential Energy Marks

spatstat-internal

Internal spatstat functions

Lengths of Line Segments

Pairwise distances between two different line segment patterns

Level Set of a Pixel Image

Kernel Smoothed Intensity of Point Pattern

Multitype J Function (i-to-any)

Print Brief Details of a Point Pattern Dataset

Fit a Log-Gaussian Cox Point Process by Minimum Contrast

Generate a Quadrature Scheme from a Point Pattern

Reduced Second Moment Measure

Data and Code From JRSS Discussion Paper on Residuals

Window in Shape of Letter R

Generate N Uniform Random Points in a Disc

Pairwise distances between two different point patterns

Apply Vector Translation To Pixel Image

ANOVA for Fitted Point Process Models

Japanese Pines Point Pattern

Artificial Data Point Pattern

Lurking variable plot

Extract Subset of Function Array

Pairwise distances between line segments

Saturated Pairwise Interaction model

Simulate Matern Model I

Generate Poisson Point Pattern

Combine Two Line Segment Patterns

Swedish Pines Point Pattern

Convert Pixel Image to Matrix

Extract or Replace Subset of Point Pattern

Tropical rain forest trees

Simulate Thomas Process

Sufficient Statistic of Point Process Model

Simulate Stratified Random Point Pattern

spatstat-deprecated

Deprecated spatstat functions

Expand Window By Factor

Estimate the I-function

Dilate a Window

The Soft Core Point Process Model

K-function using FFT

Identify Points in a Point Pattern

Determine Duplicated Points in a Spatial Point Pattern

Midpoints of Line Segment Pattern

The Strauss Point Process Model

Summary of a Line Segment Pattern Dataset

Multitype J Function (i-to-j)

Print a Fitted Point Process Model

Apply Vector Translation

Cut margins from rectangle

Simulate Point Process Models using the Metropolis-Hastings Algorithm.

Pair Correlation Function obtained from K Function

crossdist.default

Pairwise distances between two different sets of points

Data Frames of Function Values

Remove Marks from a Marked Point Pattern

Plot a Function Array

Ord Interaction Process Family

Q-Q Plot of Residuals from Fitted Point Process Model

Determine Initial State for Metropolis-Hastings Simulation.

Print Brief Details of a Line Segment Pattern Dataset

Cartesian Coordinates for a Pixel Raster

Apply Vector Translation To Line Segment Pattern

The Piecewise Constant Pairwise Interaction Point Process Model

Apply Function to Every Neighbourhood in a Point Pattern

Optimal Match Between Two Point Patterns

Apply Vector Translation To Point Pattern

Rotate a Line Segment Pattern

Interactively Add Points

Summary of a Spatial Window

Summarizing a Fitted Point Process Model

Berman-Huntington points and lines data

Extract Subset of Function Values

Simulate Neyman-Scott Process

Diameter of a Window Frame

Evaluate Expression Involving Functions

Intersection or Union of Two Windows

Inhomogeneous Multitype K Dot Function

Fit the Matern Cluster Point Process by Minimum Contrast

plot a Spatial Point Pattern

Print Brief Details of a Spatial Window

dirichlet.weights

Compute Quadrature Weights Based on Dirichlet Tessellation

Multitype K Function (Cross-type)

Pixel Image Approximation of a Window

The Lennard-Jones Potential

Pairwise distances

Generate a Default Pattern of Dummy Points

Rectangular grid of points

Function Arrays for Spatial Patterns

Test Whether An Object Is A Point Pattern

Estimate the J-function

Poisson Point Process Model

nearest.raster.point

Find Pixel Nearest to a Given Point

Hutchings' Bramble Canes data

New Zealand Trees Point Pattern

Extract Dummy Points Used to Fit a Point Process Model

Simulate systematic random point pattern

Test Whether A Point Pattern is Marked

Test Whether An Object Is A Fitted Point Process Model

is.multitype.ppp

Test Whether A Point Pattern is Multitype

Mean Pixel Value in an Image

Summarise Marks in Every Neighbourhood in a Point Pattern

Create a Point Pattern

Read Point Pattern From Data File

Estimate window from points alone

Apply Vector Translation To Window

Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True

Summarizing a Pixel Image

Set Covariance of a Window

Generic Ord Interaction model

Convert Data To Class psp

Corners of a rectangle

Calculate four standard summary functions of a point pattern.

Convert Data To Class owin

Contour plot of pixel image

Concatenate x,y Coordinate Vectors

Distance to Boundary of Window

Distance to Boundary of Window

Areas of Morphological Erosions

Beta Ganglion Cells in Cat Retina, Old Version

Print Brief Details of an Image

Compute Quadrature Weights Based on Grid Counts

plot a Spatial Quadrature Scheme

Pair Correlation Function

Fit Point Process Model to Data

Set or Reset the Marks in a Point Pattern

Extract Quadrature Scheme Used to Fit a Point Process Model

Reduced Sample Estimator using Histogram Data

Rotate a Window

Nearest Neighbour Distance Function G

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

Harkness-Isham ants' nests data

Aherne's hamster tumour data

Plot a Pixel Image

Plot a List of Things

Random Re-Labelling of Point Pattern

pairwise.family

Pairwise Interaction Process Family

Simulate point patterns using the Metropolis-Hastings algorithm.

Rotate a Point Pattern

Generate Multitype Poisson Point Pattern

Divide Point Pattern into Sub-patterns

Update a Fitted Point Process Model

Marked J Function

Generic Pairwise Interaction model

Bounding Box of a Window

Biological Cells Point Pattern

Determine Whether One Window is Contained In Another

Prediction from a Fitted Point Process Model

Estimate the empty space function F

Ord's Interaction model

Orientation Angles of Line Segments

Convert Pixel Image from Numeric to Factor

Endpoints of Line Segment Pattern

Evaluate Expression Involving Pixel Images

Create a Window

plot a Spatial Line Segment Pattern

plot a Fitted Point Process Model

Print a Quadrature Scheme

Spruces Point Pattern

Marked Nearest Neighbour Distance Function

Hughes' Amacrine Cell Data

Circular Window

Humberside Data on Childhood Leukaemia and Lymphoma

Test Whether Points Are Inside A Window

Test whether Object is Multitype

Mark Correlation Function

Nearest neighbour distances

Method of Minimum Contrast

Saturated Pairwise Interaction Point Process Family

Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts

Class of Fitted Point Process Models

California Redwoods Point Pattern (Entire Dataset)

Residuals for Fitted Point Process Model

Set Control Parameters for Metropolis-Hastings Algorithm.

Diggle-Gratton model

Apply Affine Transformation

Pine saplings in Finland.

Histogram of Pixel Values in an Image

Test Whether An Object Is A Window

Perfect Simulation of the Strauss Process

Pairwise distances

rescue.rectangle

Convert Window Back To Rectangle

Randomly Shift a Line Segment Pattern

Multitype K Function (i-to-any)

Distance Map of Point Pattern

Inhomogeneous K-function

Create a Pixel Image Object

Test Whether A Point Process Model is Marked

Simulate Matern Cluster Process

Interaction Distance of a Point Process

Simulate from a Fitted Point Process Model

Generate N Random Multitype Points

Random Thinning

Name for Unit of Length

Geyer's Saturation Point Process Model

Inhomogeneous Cross K Function

MultiStraussHard

The Multitype/Hard Core Strauss Point Process Model

Test Whether Two Pixel Images Are Compatible

Fitted Conditional Intensity for Point Process Model

multiplicity.ppp

Count Multiplicity of Duplicate Points

Longleaf Pines Point Pattern

Plot Function Valuesn

Create a Line Segment Pattern

Class of Images

Simulate Simple Sequential Inhibition

Generate Poisson Random Line Process

spatstat.options

Internal Options in Spatstat Package

Variance-Covariance Matrix for a Fitted Point Process Model

Union of Data and Dummy Points

Simulated Point Pattern

Extract Subset of Line Segment Pattern

Apply Affine Transformation To Line Segment Pattern

Centroid of a window

Kaplan-Meier Estimator using Histogram Data

Nearest Neighbour in Another Point Pattern

Perspective Plot of Pixel Image

Define Point Process Model for Metropolis-Hastings Simulation.

Plot a plotppm Object Created by plot.ppm

Pair Correlation Function of Point Pattern