Multitype Nearest Neighbour Distance Function (i-to-j)
Multitype Nearest Neighbour Distance Function (i-to-any)
Marked Nearest Neighbour Distance Function
The Multitype Strauss Point Process Model
The Multitype/Hard Core Strauss Point Process Model
The Piecewise Constant Pairwise Interaction Point Process Model
The Strauss / Hard Core Point Process Model
Apply Affine Transformation To Point Pattern
Apply Affine Transformation To Line Segment Pattern
Calculate four standard summary functions of a point pattern.
Calculate Statistic for All Types in a Multitype Point Pattern
Apply Function to Every Neighbourhood in a Point Pattern
Bounding Box of a Window or Point Pattern
Coefficients of Fitted Point Process Model
Test Whether Two Function Objects Are Compatible
Test Whether Two Pixel Images Are Compatible
Pairwise distances between two different sets of points
Pairwise distances between two different point patterns
Pairwise distances between two different line segment patterns
Crossing Points of Two Line Segment Patterns
Convert Pixel Image from Numeric to Factor
Convert Point Pattern Marks from Numeric to Factor
Extract Original Data from a Fitted Point Process Model
Generate a Default Pattern of Dummy Points
Kernel Smoothed Intensity of Point Pattern
Kernel Smoothing of Line Segment Pattern
Kernel Smoothed Intensity of Split Point Pattern
Diagnostic Plots for Fitted Point Process Model
Compute Quadrature Weights Based on Dirichlet Tessellation
Extract Dummy Points Used to Fit a Point Process Model
Determine Duplicated Points in a Spatial Point Pattern
Simulation envelopes of summary function
Evaluate Expression Involving Pixel Images
Weighted Empirical Cumulative Distribution Function
Fitted Conditional Intensity for Point Process Model
Beta Ganglion Cells in Cat Retina, Old Version
Compute Quadrature Weights Based on Grid Counts
Humberside Data on Childhood Leukaemia and Lymphoma
Test Whether A Point Process Model is Marked
Test Whether A Point Process Model is Multitype
Test Whether A Point Pattern is Multitype
Test Whether An Object Is A Fitted Point Process Model
Test Whether An Object Is A Point Pattern
Determine Whether One Window is Contained In Another
Kaplan-Meier Estimator using Histogram Data
Kaplan-Meier and Reduced Sample Estimator using Histograms
Kolmogorov-Smirnov Test for Point Process Model
Fit a Log-Gaussian Cox Point Process by Minimum Contrast
Summarise Marks in Every Neighbourhood in a Point Pattern
Fit the Matern Cluster Point Process by Minimum Contrast
Point Patterns of New Brunswick Forest Fires
Nearest-Neighbour Correlation of Marked Point Pattern
Nearest Neighbour in Another Point Pattern
Pairwise distances between line segments
Saturated Pairwise Interaction Point Process Family
Pair Correlation Function obtained from array of K functions
Pair Correlation Function obtained from K Function
Pair Correlation Function of Point Pattern
Plot a plotppm Object Created by plot.ppm
Optimal Match Between Two Point Patterns
Prediction from a Fitted Point Process Model
Print Brief Details of a Point Pattern Dataset
Print Brief Details of a Line Segment Pattern Dataset
Q-Q Plot of Residuals from Fitted Point Process Model
Extract Quadrature Scheme Used to Fit a Point Process Model
Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts
Generate a Quadrature Scheme from a Point Pattern
Perfect Simulation of the Strauss Process
Cartesian Coordinates for a Pixel Raster
Reduced Sample Estimator using Histogram Data
California Redwoods Point Pattern (Ripley's Subset)
California Redwoods Point Pattern (Entire Dataset)
Convert dataset to another unit of length
Convert Window to Another Unit of Length
Convert Point Pattern to Another Unit of Length
Convert Line Segment Pattern to Another Unit of Length
Residuals for Fitted Point Process Model
Data and Code From JRSS Discussion Paper on Residuals
Simulate point patterns using the Metropolis-Hastings algorithm.
Simulate Point Process Models using the Metropolis-Hastings Algorithm.
Simulate from a Fitted Point Process Model
Set Control Parameters for Metropolis-Hastings Algorithm.
Define Point Process Model for Metropolis-Hastings Simulation.
Build Point Process Model for Metropolis-Hastings Simulation.
Interpret Fitted Model for Metropolis-Hastings Simulation.
Determine Initial State for Metropolis-Hastings Simulation.
Generate Multitype Poisson Point Pattern
Simulate Stratified Random Point Pattern
Simulate systematic random point pattern
Generate N Uniform Random Points in a Disc
Crossing Points in a Line Segment Pattern
Set or Reset the Marks in a Point Pattern
Apply Vector Translation To Point Pattern
Apply Vector Translation To Line Segment Pattern
Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True
Extract or Replace Subset of a List of Things
Extract or Replace Subset of Point Pattern
Sufficient Statistic of Point Process Model
Summarizing a Fitted Point Process Model
Summary of a Line Segment Pattern Dataset
Fit the Thomas Point Process by Minimum Contrast
Extract Unique Points from a Spatial Point Pattern
Remove Marks from a Marked Point Pattern
Variance-Covariance Matrix for a Fitted Point Process Model