The Connected Component Process Model
Cumulative Distribution Function From Kernel Density Estimate
Diagnostics for random marking
Diggle-Gates-Stibbard Point Process Model
Diggle-Gratton model
Extract Subset of Influence Object
Extract or Replace Subset of Function Values
Nearest Neighbour Distance Distribution Function
of a Three-Dimensional Point Pattern
Model Compensator of Nearest Neighbour Function
Inhomogeneous Marked F-Function
Inhomogeneous Empty Space Function
Extract Subset of Function Array
Extract Subset of Leverage Object
Extract Subset of Signed or Vector Measure
The Area Interaction Point Process Model
Marked Nearest Neighbour Distance Function
Residual G Function
The Hard Core Point Process Model
Inhomogeneous Marked G-Function
Subset of spatially sampled function
Empty Space Function of a Three-Dimensional Point Pattern
Hybrid Geyer Point Process Model
Multitype Nearest Neighbour Distance Function (i-to-any)
Multitype Nearest Neighbour Distance Function (i-to-j)
Estimate the Empty Space Function or its Hazard Rate
The Fiksel Interaction
The Hierarchical Strauss Point Process Model
Foxall's Distance Functions
Nearest Neighbour Distance Function G
Estimate the I-function
Geyer's Saturation Point Process Model
Inhomogeneous Nearest Neighbour Function
Hybrid Interaction Point Process Model
The Hierarchical Strauss Hard Core Point Process Model
The Hierarchical Hard Core Point Process Model
Spherical Contact Distribution Function
Multitype J Function (i-to-any)
Multitype J Function (i-to-j)
K-function using FFT
Model Compensator of K Function
Inhomogeneous Cross K Function
Inhomogeneous K-function
Multitype K Function (Cross-type)
Inhomogeneous J-function
Estimate the J-function
K Function or Pair Correlation Function of Cluster Model or Cox model
K Function or Pair Correlation Function of Gibbs Point Process model
Multitype K Function (i-to-any)
Marked J Function
K-function of a Three-Dimensional Point Pattern
Mark-Weighted K Function
L-function
Marked K-Function
The Lennard-Jones Potential
Reduced Second Moment Measure
The Piecewise Constant Pairwise Interaction Point Process Model
Residual K Function
Locally Scaled K-function
Inhomogeneous Marked K-Function
Inhomogeneous L-function
Ord's Interaction model
Multitype L-function (cross-type)
Transform a Function into its P-P or Q-Q Version
The Multitype Hard Core Point Process Model
Inhomogeneous Multitype K Dot Function
K-function
Piecewise Constant Saturated Pairwise Interaction Point Process Model
Saturated Pairwise Interaction model
Arithmetic Operations on Measures
Sector K-function
Lambert's W Function
Generic Ord Interaction model
Inhomogeneous Cross Type L Function
Generic Pairwise Interaction model
Extract Interaction Structure
Convert Measure To Layered Object
Smooth a Spatially Sampled Function
Smooth Interpolation of Marks as a Spatial Function
The Multitype Strauss Point Process Model
Smooth a Signed or Vector-Valued Measure
K-function or Pair Correlation Function of a
Determinantal Point Process Model
K Function or Pair Correlation Function of a Point Process Model
Spatial smoothing of observations at irregular points
Multitype L-function (i-to-any)
Inhomogeneous Multitype L Dot Function
Third order summary statistic
Extract Window of Spatial Object
Cross Validated Bandwidth Selection for Relative Risk Estimation
Bandwidth Selection for Diffusion Smoother by Likelihood Cross-Validation
The Strauss / Hard Core Point Process Model
Adaptive Estimate of Intensity of Point Pattern
Spatial Distribution Test for Multiple Point Process Model
The Triplet Point Process Model
Poisson Point Process Model
Penttinen Interaction
Added Variable Plot for Point Process Model
The Multitype/Hard Core Strauss Point Process Model
Density Estimation for Circular Data
Convert Function Table to Function
Convert Data To Class owin
Extract Fitted Point Process Model
Convert Data To Class fv
Test Whether Function Objects Are Compatible
Apply Gaussian Blur to a Pixel Image
The Soft Core Point Process Model
Generic Calculation of K Function and Pair Correlation Function
Analysis of Deviance for Spatial Logistic Regression Models
Coerce Envelope to Data Frame
Spatial smoothing of data
Apply Smoothing to Function Values
The Strauss Point Process Model
Cronie and van Lieshout's Criterion for Bandwidth Selection for Kernel Density
ANOVA for Fitted Point Process Models for Replicated Patterns
ANOVA for Fitted Point Process Models
Abramson's Adaptive Bandwidths
Bandwidth Selection for Diffusion Smoother by Cronie-van Lieshout Rule
Scott's Rule for Bandwidth Selection for Kernel Density
Cross Validated Bandwidth Selection for Spatial Smoothing
Convert Function Value Table to Function
Parameter Influence Measure
Construct a New Determinantal Point Process Model Family Function
Global Envelopes for Balanced Independent Two-Stage Test
Balanced Independent Two-Stage Monte Carlo Test
Convert Leverage Object to Function of Coordinates
Calculate four standard summary functions of a point pattern.
Calculate Summary Statistic for All Types in a Multitype Point Pattern
Dimension of Determinantal Point Process Model
Extract Cluster Offspring Kernel
Fit Cluster or Cox Point Process Model via Minimum Contrast
Estimate Dimension of Central Subspace
Cross Validated Bandwidth Selection for Kernel Density
Berman's Tests for Point Process Model
Combine Function Value Tables
Fit the Neyman-Scott cluster process with Cauchy kernel
Stoyan's Rule of Thumb for Bandwidth Selection
Spatial Distribution Test for Point Pattern or Point Process Model
Bandwidth Selection Based on Window Geometry
Fit the Neyman-Scott cluster process with Cauchy kernel
Area Under ROC Curve
Bias Correction for Fitted Model
Residual Diagnostics for Multiple Fitted Models
Test Whether Function Arrays Are Compatible
Cross Validated Bandwidth Selection for Pair Correlation Function
Coefficients of Fitted Spatial Logistic Regression Model
Collapse Several Function Tables into One
Clark and Evans Test
Clark and Evans Aggregation Index
Likelihood Cross Validation Bandwidth Selection for Kernel Density
Translation Edge Correction
Exponential Energy Marks
Calculate Derivative of Function Values
Significance Trace of Cressie-Loosmore-Ford or Maximum Absolute
Deviation Test
Progress Plot of Test of Spatial Pattern
Set Default Control Parameters for Metropolis-Hastings Algorithm.
Kernel Smoothed Intensity of Point Pattern
Coefficients of Fitted Point Process Model
Coefficients of Point Process Model Fitted to Multiple Point Patterns
Diffusion Estimate of Point Pattern Intensity
Adaptive Kernel Estimate of Intensity of Point Pattern
Ripley's Isotropic Edge Correction
Compute or Extract Effective Range of Cluster Kernel
Distribution Function of Interpoint Distance
Kernel Estimate of Intensity as a Spatial Function
Simulation Envelopes of Summary Function for 3D Point Pattern
Kernel distributions and random generation
Count Close Pairs of Points
Diagnostic Plots for Fitted Point Process Model
Dao-Genton Adjusted Goodness-Of-Fit Test
Allard-Fraley Estimator of Cluster Feature
Model Formulae for Gibbs Point Process Models
Hierarchical Pairwise Interaction Process Family
Quantiles of a Density Estimate
Extract or Change the Plot Formula for a Function Value Table
Hopkins-Skellam Test
Field of clusters
Power Exponential Spectral Determinantal Point Process Model
Array of Simulation Envelopes of Summary Function
Leverage Measure for Spatial Point Process Model
Improve Intensity Estimate of Fitted Cluster Point Process Model
Increments of a Function
Diggle-Cressie-Loosmore-Ford and Maximum Absolute Deviation Tests
Default Expansion Rule for Simulation of Model
Pair Correlation Function of a Three-Dimensional Point Pattern
Approximate Determinantal Point Process Kernel
Extract Dummy Points Used to Fit a Point Process Model
Loglikelihood of Spatial Logistic Regression
Fitted Probabilities for Spatial Logistic Regression
Gaussian Determinantal Point Process Model
Whittle-Matern Determinantal Point Process Model
Covariance and Correlation between Images
Extract Original Data from a Fitted Point Process Model
Laslett's Transform
Intensity Estimate of Point Pattern Using Voronoi-Dirichlet Tessellation
Diffusion Estimate of Point Pattern Intensity
Progress Plot of Dao-Genton Test of Spatial Pattern
Convert Data to Numeric Values by Constructing Dummy Variables
Range of Spectral Density of a Determinantal Point Process Model
Approximate Pair Correlation Function of Determinantal Point Process Model
Mark-Mark Scatter Plot
Kernel Smoothing of Line Segment Pattern
Saturated Pairwise Interaction Point Process Family
Methods for Cluster Models
Lurking Variable Plot for Multiple Point Patterns
Kernel Smoothed Intensity of Split Point Pattern
Significance Trace of Dao-Genton Test
Fit Determinantal Point Process Model
Extract Kernel from Determinantal Point Process Model Object
Log Likelihood and AIC for Fitted Determinantal Point Process Model
Internal function calculating eig and index
Function Value Table
Evaluate Expression Involving Function Arrays
Exact Maximum Pseudolikelihood Estimate for Stationary Strauss Process
Compute Fitted Effect of a Spatial Covariate in a Point Process Model
Global Envelopes for Dao-Genton Test
Case Deletion Effect Measure of Fitted Model
Mixed Poisson Distribution
Extract the Domain of any Spatial Object
Evaluate Expression Involving Functions
Nearest Neighbour Clutter Removal
Force Point Process Model to be Valid
Test Whether A Point Process Model is Multitype
Bessel Type Determinantal Point Process Model
Force Spatial Logistic Regression Model to be Valid
Heat Kernel for a Two-Dimensional Rectangle
Force Model to be Valid
Compute Images of Constructed Covariates
Extract Fixed Effects from Point Process Model
Generalized Cauchy Determinantal Point Process Model
Gauss-Hermite Quadrature Approximation to Expectation for Normal Distribution
Log Likelihood and AIC for Point Process Model
Pool Data from Several Envelopes
Intensity of Fitted Point Process Model
Recognise Stationary and Poisson Point Process Models
Hybrid Interaction Family
Intensity of Fitted Spatial Logistic Regression Model
Pair Correlation Function
Interaction Structure Family Objects
Integral of a Measure
Extract the Interaction from a Fitted Point Process Model
Basis for Harmonic Functions
Function Arrays for Spatial Patterns
Simulate Product Shot-noise Cox Process
Infinite Order Interaction Family
Nearest-Neighbour Correlation Indices of Marked Point Pattern
Methods for Spatially Sampled Functions
Abbreviations for Groups of Columns in Function Value Table
Partial Residuals for Point Process Model
Intensity of Determinantal Point Process Model
Methods for Spatial Logistic Regression Models
Test Whether A Point Process Model is Marked
Test Whether An Object Is A Fitted Point Process Model
Fit Point Process Model Involving Irregular Trend Parameters
Parameter Bound for a Determinantal Point Process Model
Extract Spectral Density from Determinantal Point Process Model Object
Apply Expansion Rule
Tabulate Marks in Neighbourhood of Every Point in a Point Pattern
Fitted Conditional Intensity for Point Process Model
Fitted Conditional Intensity for Multiple Point Process Model
Generate N Uniform Random Points
Class of Fitted Point Process Models
Plot Function Values
Moment of Smoothing Kernel
Print a Fitted Point Process Model
Recompute Envelopes
Kaplan-Meier Estimator using Histogram Data
Simulation Envelopes of Summary Function
Influence Measure for Spatial Point Process Model
Parametric Estimate of Spatially-Varying Relative Risk
Model selection criteria for the intensity function of a point process
Fit a Log-Gaussian Cox Point Process by Minimum Contrast
Recognise Fitted Determinantal Point Process Models
Test Whether Object is a Hybrid
Mark Correlation Function
Create a Function Value Table
Kaplan-Meier and Reduced Sample Estimator using Histograms
Inverse-distance weighted smoothing of observations at irregular points
Simulate Neyman-Scott Process
Integral of Squared Kernel
Local pair correlation function
Morisita Index Plot
Methods for Objective Function Surfaces
Fit Cluster or Cox Point Process Model
Make Function Tables Compatible
Log Likelihood and AIC for Multiple Point Process Model
Neighbourhood density function
Pair Correlation Function of Point Pattern
Pairwise Interaction Process Family
Simulate Matern Model II
Fit the Matern Cluster Point Process by Minimum Contrast Using Pair Correlation
Simulate Thomas Process
Fry Plot of Point Pattern
Make Measures Compatible
Plot a Recursively Partitioned Point Process Model
Leverage and Influence Diagnostics for Spatial Logistic Regression
Generate N Random Multitype Points
Plot a fitted determinantal point process
Pool Data
Local Multitype K Function (Cross-Type)
Lurking Variable Plot
Plot a Spatial Distribution Test
Extract the Variables in a Point Process Model
Bootstrap Confidence Bands for Summary Function
Plot a Simulation Envelope
Inhomogeneous Multitype K Function
Prune a Recursively Partitioned Point Process Model
Plot a Function Array
Fit Models by Profile Maximum Pseudolikelihood or AIC
Pool Data from Several Function Arrays
Scale factor for density kernel
Log Likelihood and AIC for Fitted Cox or Cluster Point Process Model
Generate N Uniform Random Points in a Disc
Fit Point Process Model to Point Pattern Data
Fit a Log-Gaussian Cox Point Process by Minimum Contrast
Plot a Fitted Spatial Logistic Regression
Mark Cross-Correlation Function
Identify Covariates Involved in each Model Term
Methods for Cluster Point Process Models
Methods for Leverage Objects
Mark Connection Function
Chi-Squared Test for Multiple Point Process Model Based on
Quadrat Counts
Pool Several Quadrat Tests
Panel Plots using Colour Image or Contour Lines
Mosaic Random Field
Interaction Distance of a Point Process
Simulation of a Determinantal Point Process
Local Multitype K Function (Dot-Type)
Simulate Neyman-Scott Point Process with Variance Gamma cluster kernel
Resample a Point Pattern by Resampling Quadrats
Plot a Signed or Vector-Valued Measure
Generate Poisson Random Line Process
Residuals for Fitted Point Process Model
Predicted or Fitted Values from Spatial Logistic Regression
Fit the Matern Cluster Point Process by Minimum Contrast
Methods for Intensity Functions of Spatial Covariate
Method of Minimum Contrast
Discrete and Continuous Components of a Measure
Extract Model Parameters in Understandable Form
Methods for Fitted Interactions
plot a Fitted Point Process Model
Estimate Intensity of Point Pattern Using Nearest Neighbour Distances
Simulate from a Fitted Point Process Model
Simulate Log-Gaussian Cox Process
Plot a fitted cluster point process
Methods for Intensity Functions of Two Spatial Covariates
Define Point Process Model for Metropolis-Hastings Simulation.
Test Expansion Rule
Specify Simulation Window or Expansion Rule
Residuals for Fitted Spatial Logistic Regression Model
Sufficient Statistic of Point Process Model
Dummy Function Returns Number of Points
Calculate Pseudo-R-Squared for Point Process Model
Point Pair Orientation Distribution
Prediction for Fitted Multiple Point Process Model
Compute Unless Previously Saved
Plot Laslett Transform
Mark Variogram
Inhomogeneous Neighbourhood Density Function
Fit Point Process Model to Several Point Patterns
Positive and Negative Parts, and Variation, of a Measure
Inhomogeneous Pair Correlation Function
Inhomogeneous Multitype Pair Correlation Function (Type-i-To-Any-Type)
Pair Correlation Function obtained from array of K functions
Objective Function Surface
Generate N Random Points
Simulate Simple Sequential Inhibition
Display the result of a quadrat counting test.
Estimate of Spatially-Varying Relative Risk
Mean of a Function of Interpoint Distance
Plot a plotppm Object Created by plot.ppm
Multitype pair correlation function (i-to-any)
Estimate the Spatial Covariance Function of a Random Field
Scatterplot Matrix for Pixel Images
Pseudoscore Diagnostic For Fitted Model against General Alternative
Extract Design Matrix from Spatial Logistic Regression Model
Marked pair correlation function
plot a Fitted Multiple Point Process Model
Randomly Shift a Point Pattern
Pair Correlation Function obtained from K Function
Pool Data from a List of Objects
Prediction from a Fitted Cluster Point Process Model
Methods for Determinantal Point Process Models
Nearest Neighbour Orientation Distribution
Mosaic Random Set
Plot Influence Measure
Generate Poisson Point Pattern on Line Segments
Reduced Sample Estimator using Histogram Data
Alternating Gibbs Sampler for Multitype Point Processes
Prediction from a Fitted Determinantal Point Process Model
Plot a Studentised Permutation Test
Plot Profile Likelihood
Simulate Matern Model I
Extract Design Matrix of Point Process Model for Several Point Patterns
Methods for Influence Objects
Spatial Cumulative Distribution Function
Spatial Logistic Regression
Distance Between Linear Spaces
Signed or Vector-Valued Measure
Check Whether Point Process Model is Valid
Simulate a Fitted Gibbs Point Process Model
Pool Several Functions
Plot Leverage Function
Multitype pair correlation function (cross-type)
Prediction from a Fitted Point Process Model
Fit Point Process Model to Data
Perfect Simulation of the Strauss-Hardcore Process
Polynomial in One or Two Variables
Fit the Thomas Point Process by Minimum Contrast
Name for Unit of Length
Triplet Interaction Family
Estimate Variance of Summary Statistic by Subdivision
Simulate a Fitted Cluster Point Process Model
Extract Quadrature Scheme Used to Fit a Point Process Model
Range of Function Values
Dispersion Test of CSR for Split Point Pattern Based on
Quadrat Counts
Simulate Poisson Cluster Process
Evaluate an Expression in a Function Table
Predicted Variance of the Number of Points
Pool Data from Several Ratio Objects
Data Sharpening of Point Pattern
Random Shift
Leverage and Influence Measures for Spatial Point Process Model
Plot Result of Scan Test
Compute Integral of Function Against Cumulative Distribution
Random Thinning of Clumps
Simulate point patterns using the Metropolis-Hastings algorithm.
Plot Result of Berman Test
Pseudoscore Diagnostic For Fitted Model against Area-Interaction Alternative
Make Predictions From a Recursively Partitioned Point Process Model
Extract Design Matrix from Point Process Model
Simulate Neyman-Scott Point Process with Cauchy cluster kernel
Ord Interaction Process Family
Smoothed Relative Density of Pairs of Covariate Values
Inhomogeneous Multitype Pair Correlation Function (Cross-Type)
Contact Distribution Function using Rectangular Structuring Element
Sibling Probability of Cluster Point Process
Nonparametric Estimate of Spatially-Varying Relative Risk
Pseudoscore Diagnostic For Fitted Model against Saturation Alternative
Simulate Gauss-Poisson Process
Perfect Simulation of the Diggle-Gratton Process
Ratio object
Evaluate Expression Involving Components of a Measure
Extract Random Effects from Point Process Model
Perfect Simulation of the Strauss Process
Q-Q Plot of Residuals from Fitted Point Process Model
Dispersion Test for Spatial Point Pattern Based on
Quadrat Counts
Simulate a Point Process Model Fitted to Several Point Patterns
Simulate Matern Cluster Process
Perfect Simulation of the Hardcore Process
Random Pixel Noise
Generate Random Numbers of Points for Cell Process
Simulate Baddeley-Silverman Cell Process
Perfect Simulation of the Diggle-Gates-Stibbard Process
Perfect Simulation of the Penttinen Process
Recursively Partitioned Point Process Model
Richardson Extrapolation
Nonparametric Estimate of Intensity as Function of a Covariate
Fit the Thomas Point Process by Minimum Contrast
Plot a Spatially Sampled Function
Simulate Point Process Models using the Metropolis-Hastings Algorithm.
Interpret Fitted Model for Metropolis-Hastings Simulation.
Repulsiveness Index of a Determinantal Point Process Model
Update an Interpoint Interaction
Residuals for Point Process Model Fitted to Multiple Point Patterns
Spatially Sampled Function
Range of Interaction for a Determinantal Point Process Model
Alternating Gibbs Sampler for Area-Interaction Process
Generate Poisson Point Pattern in Three Dimensions
Compute Predictors from Sufficient Dimension Reduction
Receiver Operating Characteristic
Simulate a Fitted Spatial Logistic Regression Model
Rose Diagram
Test of Spatial Segregation of Types
Check Validity of a Determinantal Point Process Model
Generate N Uniform Random Points in Three Dimensions
Summarizing a Fitted Point Process Model
Evaluate Expression in a Spatially Sampled Function
Residuals for Fitted Cox or Cluster Point Process Model
Determine Initial State for Metropolis-Hastings Simulation.
Random Re-Labelling of Point Pattern
Range of Interaction for a Cox or Cluster Point Process Model
Residuals for Fitted Determinantal Point Process Model
Generate Poisson Point Pattern
Alternating Gibbs Sampler for Multitype Hard Core Process
Generate N Uniform Random Points On Line Segments
Theoretical Distribution of Nearest Neighbour Distance
Sufficient Dimension Reduction
Generate Multitype Poisson Point Pattern
Extract the Values of the Response from a Fitted Model
Summarizing a Fitted Determinantal Point Process Model
Define Point Process Model for Metropolis-Hastings Simulation.
Generate Poisson Point Pattern in Any Dimensions
Simulate Stratified Random Point Pattern
Cluster Point Process Model
Build Point Process Model for Metropolis-Hastings Simulation.
The spatstat.core Package
Summarizing a Fitted Cox or Cluster Point Process Model
Likelihood Ratio Test Statistic for Scan Test
Internal spatstat.core functions
Pixel Values Along a Transect
Randomly Shift a List of Point Patterns
Simulation of Determinantal Point Process Model
Variance-Covariance Matrix for a Fitted Cluster Point Process Model
Variance-Covariance Matrix for a Fitted Point Process Model
Randomly Shift a Line Segment Pattern
Deprecated spatstat.core functions
Set Control Parameters for Metropolis-Hastings Algorithm.
Update Control Parameters of Metropolis-Hastings Algorithm
Update a Fitted Point Process Model
Variance-Covariance Matrix for a Fitted Spatial Logistic Regression
Calculate Variance-Covariance Matrix for Fitted Multiple Point
Process Model
Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel
Random Thinning
Poisson Line Tessellation
Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel
Update a Fitted Cluster Point Process Model
Rotational Average of a Pixel Image
Stienen Diagram
Generate N Uniform Random Points in Any Dimensions
Studentised Permutation Test
Simulated Annealing or Simulated Tempering for Gibbs Point Processes
Check Whether Point Process Model is Valid
Spatial Scan Test
Divide a Measure into Parts
Separate a Vector Measure into its Scalar Components
Extract List of Individual Point Process Models
Check Whether Spatial Logistic Regression Model is Valid
update.detpointprocfamily
Set Parameter Values in a Determinantal Point Process Model