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