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