# spatstat v1.32-0

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

A package for analysing spatial data, mainly Spatial Point Patterns, including multitype/marked points and spatial covariates, in any two-dimensional spatial region. Also supports three-dimensional point patterns, and space-time point patterns in any number of dimensions.
Contains over 1000 functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference.
Data types include point patterns, line segment patterns, spatial windows, pixel images and tessellations.
Exploratory methods include K-functions, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics etc.
Point process models can be fitted to point pattern data using functions ppm, kppm, slrm similar to glm. Models may include dependence on covariates, interpoint interaction, cluster formation 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).

## Functions in spatstat

Name | Description | |

Ginhom | Inhomogeneous Nearest Neighbour Function | |

Kcross.inhom | Inhomogeneous Cross K Function | |

Extract.fasp | Extract Subset of Function Array | |

areaGain | Difference of Disc Areas | |

Linhom | L-function | |

as.psp | Convert Data To Class psp | |

boxx | Multi-Dimensional Box | |

areaLoss | Difference of Disc Areas | |

Strauss | The Strauss Point Process Model | |

applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |

centroid.owin | Centroid of a window | |

dilation | Morphological Dilation | |

Pairwise | Generic Pairwise Interaction model | |

eval.im | Evaluate Expression Involving Pixel Images | |

Gmulti | Marked Nearest Neighbour Distance Function | |

clip.infline | Intersect Infinite Straight Lines with a Window | |

Extract.layered | Extract Subset of a Layered Object | |

PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |

DiggleGratton | Diggle-Gratton model | |

murchison | Murchison gold deposits | |

Hybrid | Hybrid Interaction Point Process Model | |

ants | Harkness-Isham ants' nests data | |

Fiksel | The Fiksel Interaction | |

as.box3 | Convert Data to Three-Dimensional Box | |

affine.lpp | Apply Geometrical Transformations to Point Pattern on a Linear Network | |

Finhom | Inhomogeneous Empty Space Function | |

Jcross | Multitype J Function (i-to-j) | |

licence.polygons | Restricted Licence Conditions for Polygon Calculations | |

marks.psp | Marks of a Line Segment Pattern | |

Replace.im | Reset Values in Subset of Image | |

Concom | The Connected Component Process Model | |

bramblecanes | Hutchings' Bramble Canes data | |

BadGey | Hybrid Geyer Point Process Model | |

delaunay.distance | Distance on Delaunay Triangulation | |

is.ppm | Test Whether An Object Is A Fitted Point Process Model | |

OrdThresh | Ord's Interaction model | |

Jdot | Multitype J Function (i-to-any) | |

beachcolours | Create Colour Scheme for a Range of Numbers | |

Extract.linnet | Extract Subset of Linear Network | |

border | Border Region of a Window | |

G3est | Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern | |

Softcore | The Soft Core Point Process Model | |

Iest | Estimate the I-function | |

logLik.slrm | Loglikelihood of Spatial Logistic Regression | |

complement.owin | Take Complement of a Window | |

bei | Tropical rain forest trees | |

compatible.fasp | Test Whether Function Arrays Are Compatible | |

gorillas | Gorilla Nesting Sites | |

formula.fv | Extract or Change the Plot Formula for a Function Value Table | |

anemones | Beadlet Anemones Data | |

plot.splitppp | Plot a List of Point Patterns | |

Fest | Estimate the empty space function F | |

commonGrid | Determine A Common Spatial Domain And Pixel Resolution | |

Gcom | Model Compensator of Nearest Neighbour Function | |

as.function.fv | Convert Function Value Table to Function | |

alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern | |

distmap | Distance Map | |

Extract.msr | Extract Subset of Signed or Vector Measure | |

methods.fii | Methods for Fitted Interactions | |

Extract.psp | Extract Subset of Line Segment Pattern | |

contour.listof | Plot a List of Things | |

distfun | Distance Map as a Function | |

clarkevans.test | Clark and Evans Test | |

Emark | Diagnostics for random marking | |

MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |

compareFit | Residual Diagnostics for Multiple Fitted Models | |

dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |

localKinhom | Inhomogeneous Neighbourhood Density Function | |

cut.im | Convert Pixel Image from Numeric to Factor | |

AreaInter | The Area Interaction Point Process Model | |

exactMPLEstrauss | Exact Maximum Pseudolikelihood Estimate for Stationary Strauss Process | |

affine.owin | Apply Affine Transformation To Window | |

by.im | Apply Function to Image Broken Down by Factor | |

runifpointOnLines | Generate N Uniform Random Points On Line Segments | |

plot.colourmap | Plot a Colour Map | |

clusterset | Allard-Fraley Estimator of Cluster Feature | |

deriv.fv | Calculate Derivative of Function Values | |

Ord | Generic Ord Interaction model | |

connected.ppp | Connected components of a point pattern | |

anova.ppm | ANOVA for Fitted Point Process Models | |

MultiHard | The Multitype Hard Core Point Process Model | |

im.object | Class of Images | |

cauchy.estK | Fit the Neyman-Scott cluster process with Cauchy kernel | |

is.multitype.ppm | Test Whether A Point Process Model is Multitype | |

affine.psp | Apply Affine Transformation To Line Segment Pattern | |

interp.im | Interpolate a Pixel Image | |

demopat | Artificial Data Point Pattern | |

Kinhom | Inhomogeneous K-function | |

is.owin | Test Whether An Object Is A Window | |

Extract.ppp | Extract or Replace Subset of Point Pattern | |

as.matrix.im | Convert Pixel Image to Matrix or Array | |

DiggleGatesStibbard | Diggle-Gates-Stibbard Point Process Model | |

convexhull | Convex Hull | |

LennardJones | The Lennard-Jones Potential | |

diameter.boxx | Geometrical Calculations for Multi-Dimensional Box | |

colourtools | Convert and Compare Colours in Different Formats | |

Tstat | Third order summary statistic | |

bdist.points | Distance to Boundary of Window | |

as.interact | Extract Interaction Structure | |

plot.hyperframe | Plot Entries in a Hyperframe | |

compatible.fv | Test Whether Function Objects Are Compatible | |

eroded.areas | Areas of Morphological Erosions | |

pcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-Type) | |

lineardisc | Compute Disc of Given Radius in Linear Network | |

allstats | Calculate four standard summary functions of a point pattern. | |

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

nnwhich | Nearest neighbour | |

cut.ppp | Classify Points in a Point Pattern | |

pairdist | Pairwise distances | |

convolve.im | Convolution of Pixel Images | |

intersect.owin | Intersection, Union or Set Subtraction of Two Windows | |

identify.psp | Identify Segments in a Line Segment Pattern | |

predict.kppm | Prediction from a Fitted Cluster Point Process Model | |

rLGCP | Simulate Log-Gaussian Cox Process | |

gridweights | Compute Quadrature Weights Based on Grid Counts | |

finpines | Pine saplings in Finland. | |

clickjoin | Interactively join vertices on a plot | |

crossdist.ppx | Pairwise Distances Between Two Different Multi-Dimensional Point Patterns | |

harmonise.im | Make Pixel Images Compatible | |

is.marked.ppm | Test Whether A Point Process Model is Marked | |

vargamma.estpcf | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |

ppx | Multidimensional Space-Time Point Pattern | |

default.rmhcontrol | Set Default Control Parameters for Metropolis-Hastings Algorithm. | |

affine | Apply Affine Transformation | |

default.expand | Default Expansion Rule for Simulation of Model | |

plot.plotppm | Plot a plotppm Object Created by plot.ppm | |

is.marked | Test Whether Marks Are Present | |

Poisson | Poisson Point Process Model | |

infline | Infinite Straight Lines | |

fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |

nearestsegment | Find Line Segment Nearest to Each Point | |

endpoints.psp | Endpoints of Line Segment Pattern | |

clickppp | Interactively Add Points | |

methods.kppm | Methods for Cluster Point Process Models | |

lut | Lookup Tables | |

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

letterR | Window in Shape of Letter R | |

circumradius | Circumradius and Diameter of a Linear Network | |

Lest | L-function | |

envelope.envelope | Recompute Envelopes | |

dclf.progress | Progress Plot of Test of Spatial Pattern | |

erosion | Morphological Erosion | |

ewcdf | Weighted Empirical Cumulative Distribution Function | |

is.convex | Test Whether a Window is Convex | |

model.matrix.slrm | Extract Design Matrix from Spatial Logistic Regression Model | |

dfbetas.ppm | Parameter influence measure | |

markconnect | Mark Connection Function | |

plot.envelope | Plot a Simulation Envelope | |

SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model | |

eval.fv | Evaluate Expression Involving Functions | |

affine.im | Apply Affine Transformation To Pixel Image | |

colourmap | Colour Lookup Tables | |

by.ppp | Apply a Function to a Point Pattern Broken Down by Factor | |

ippm | Optimise Irregular Trend Parameters in Point Process Model | |

influence.ppm | Influence Measure for Spatial Point Process Model | |

Ldot.inhom | Inhomogeneous Multitype L Dot Function | |

Lcross.inhom | Inhomogeneous Cross Type L Function | |

psstG | Pseudoscore Diagnostic For Fitted Model against Saturation Alternative | |

fv | Create a Function Value Table | |

flu | Influenza Virus Proteins | |

as.mask.psp | Convert Line Segment Pattern to Binary Pixel Mask | |

convexhull.xy | Convex Hull of Points | |

concatxy | Concatenate x,y Coordinate Vectors | |

methods.funxy | Methods for Spatial Functions | |

methods.pp3 | Methods for three-dimensional point patterns | |

redwood | California Redwoods Point Pattern (Ripley's Subset) | |

distmap.owin | Distance Map of Window | |

marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern | |

reduced.sample | Reduced Sample Estimator using Histogram Data | |

msr | Signed or Vector-Valued Measure | |

ppp.object | Class of Point Patterns | |

dilated.areas | Areas of Morphological Dilations | |

closing | Morphological Closing | |

simulate.kppm | Simulate a Fitted Cluster Point Process Model | |

envelope | Simulation Envelopes of Summary Function | |

nnfun | Nearest Neighbour Map as a Function | |

diameter | Diameter of an Object | |

gordon | People in Gordon Square | |

crossdist.pp3 | Pairwise distances between two different three-dimensional point patterns | |

rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |

simulate.slrm | Simulate a Fitted Spatial Logistic Regression Model | |

pcfcross | Multitype pair correlation function (cross-type) | |

linnet | Create a Linear Network | |

pcf.fv | Pair Correlation Function obtained from K Function | |

smooth.fv | Apply Smoothing to Function Values | |

angles.psp | Orientation Angles of Line Segments | |

Hardcore | The Hard Core Point Process Model | |

nbfires | Point Patterns of New Brunswick Forest Fires | |

raster.x | Cartesian Coordinates for a Pixel Raster | |

parres | Partial Residuals for Point Process Model | |

nnmark | Mark of Nearest Neighbour | |

cells | Biological Cells Point Pattern | |

rknn | Theoretical Distribution of Nearest Neighbour Distance | |

rGaussPoisson | Simulate Gauss-Poisson Process | |

pp3 | Three Dimensional Point Pattern | |

print.ppm | Print a Fitted Point Process Model | |

methods.rhohat | Methods for Intensity Functions of Spatial Covariate | |

methods.lpp | Methods for Point Patterns on a Linear Network | |

hyperframe | Hyper Data Frame | |

pairdist.pp3 | Pairwise distances in Three Dimensions | |

rhohat | Smoothing Estimate of Covariate Transformation | |

methods.units | Methods for Units | |

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

runifpointx | Generate N Uniform Random Points in Any Dimensions | |

plot.psp | plot a Spatial Line Segment Pattern | |

rpoint | Generate N Random Points | |

model.images | Compute Images of Constructed Covariates | |

rlabel | Random Re-Labelling of Point Pattern | |

print.ppp | Print Brief Details of a Point Pattern Dataset | |

lppm | Fit Point Process Model to Point Pattern on Linear Network | |

gridcentres | Rectangular grid of points | |

periodify | Make Periodic Copies of a Spatial Pattern | |

as.ppm | Extract Fitted Point Process Model | |

persp.im | Perspective Plot of Pixel Image | |

duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |

dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |

distcdf | Distribution Function of Interpoint Distance | |

coords | Extract or Change Coordinates of a Spatial or Spatiotemporal Point Pattern | |

rmpoispp | Generate Multitype Poisson Point Pattern | |

simdat | Simulated Point Pattern | |

betacells | Beta Ganglion Cells in Cat Retina | |

density.ppp | Kernel Smoothed Intensity of Point Pattern | |

rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |

simplify.owin | Approximate a Polygon by a Simpler Polygon | |

linim | Create Pixel Image on Linear Network | |

nsegments | Number of Line Segments in a Line Segment Pattern | |

Extract.fv | Extract Subset of Function Values | |

envelope.pp3 | Simulation Envelopes of Summary Function for 3D Point Pattern | |

is.hybrid | Test Whether Object is a Hybrid | |

npfun | Dummy Function Returns Number of Points | |

pool | Pool Data | |

Extract.tess | Extract or Replace Subset of Tessellation | |

swedishpines | Swedish Pines Point Pattern | |

print.im | Print Brief Details of an Image | |

discpartarea | Area of Part of Disc | |

Gres | Residual G Function | |

plot.pp3 | Plot a three-dimensional point pattern | |

diameter.box3 | Geometrical Calculations for Three-Dimensional Box | |

rMosaicField | Mosaic Random Field | |

bronzefilter | Bronze gradient filter data | |

Jest | Estimate the J-function | |

ponderosa | Ponderosa Pine Tree Point Pattern | |

reach | Interaction Distance of a Point Process | |

valid.ppm | Check Whether Point Process Model is Valid | |

pppdist | Distance Between Two Point Patterns | |

rgbim | Create Colour-Valued Pixel Image | |

with.hyperframe | Evaluate an Expression in Each Row of a Hyperframe | |

pairdist.ppp | Pairwise distances | |

is.lpp | Test Whether An Object Is A Point Pattern on a Linear Network | |

with.fv | Evaluate an Expression in a Function Table | |

as.rectangle | Window Frame | |

pcf.ppp | Pair Correlation Function of Point Pattern | |

fitted.ppm | Fitted Conditional Intensity for Point Process Model | |

fasp.object | Function Arrays for Spatial Patterns | |

selfcrossing.psp | Crossing Points in a Line Segment Pattern | |

quadscheme | Generate a Quadrature Scheme from a Point Pattern | |

Jinhom | Inhomogeneous J-function | |

update.rmhcontrol | Update Control Parameters of Metropolis-Hastings Algorithm | |

pcf3est | Pair Correlation Function of a Three-Dimensional Point Pattern | |

psp | Create a Line Segment Pattern | |

rho2hat | Smoothed Relative Density of Pairs of Covariate Values | |

methods.ppx | Methods for Multidimensional Space-Time Point Patterns | |

nndist | Nearest neighbour distances | |

beginner | Print Introduction For Beginners | |

rescale | Convert dataset to another unit of length | |

Extract.splitppp | Extract or Replace Sub-Patterns | |

envelope.lpp | Envelope for Point Patterns on Linear Network | |

Extract.owin | Extract Subset of Window | |

Kest.fft | K-function using FFT | |

as.matrix.owin | Convert Pixel Image to Matrix | |

rcell | Simulate Baddeley-Silverman Cell Process | |

matchingdist | Distance for a Point Pattern Matching | |

japanesepines | Japanese Pines Point Pattern | |

print.psp | Print Brief Details of a Line Segment Pattern Dataset | |

progressreport | Print Progress Reports | |

rpoisline | Generate Poisson Random Line Process | |

plot.linnet | Plot a linear network | |

rpoislpp | Poisson Point Process on a Linear Network | |

rotate.psp | Rotate a Line Segment Pattern | |

idw | Inverse-distance weighted smoothing of observations at irregular points | |

bw.scott | Scott's Rule for Bandwidth Selection for Kernel Density | |

rescale.owin | Convert Window to Another Unit of Length | |

shift.im | Apply Vector Translation To Pixel Image | |

tiles | Extract List of Tiles in a Tessellation | |

compatible | Test Whether Objects Are Compatible | |

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

methods.rho2hat | Methods for Intensity Functions of Two Spatial Covariates | |

plot.tess | Plot a tessellation | |

rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |

pool.envelope | Pool Data from Several Envelopes | |

layered | Create List of Plotting Layers | |

affine.ppp | Apply Affine Transformation To Point Pattern | |

pointsOnLines | Place Points Evenly Along Specified Lines | |

integral.im | Integral of a Pixel Image | |

will.expand | Test Expansion Rule | |

stieltjes | Compute Integral of Function Against Cumulative Distribution | |

F3est | Empty Space Function of a Three-Dimensional Point Pattern | |

rsyst | Simulate systematic random point pattern | |

sumouter | Compute Quadratic Forms | |

pcfinhom | Inhomogeneous Pair Correlation Function | |

is.ppp | Test Whether An Object Is A Point Pattern | |

amacrine | Hughes' Amacrine Cell Data | |

chop.tess | Subdivide a Window or Tessellation using a Set of Lines | |

append.psp | Combine Two Line Segment Patterns | |

model.depends | Identify Covariates Involved in each Model Term | |

Extract.listof | Extract or Replace Subset of a List of Things | |

lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |

thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |

split.ppp | Divide Point Pattern into Sub-patterns | |

spatstat-deprecated | Deprecated spatstat functions | |

as.mask | Pixel Image Approximation of a Window | |

area.owin | Area of a Window | |

bounding.box.xy | Convex Hull of Points | |

kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |

pool.fasp | Pool Data from Several Function Arrays | |

spruces | Spruces Point Pattern | |

crossdist.lpp | Pairwise distances between two point patterns on a linear network | |

matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |

bermantest | Berman's Tests for Point Process Model | |

plot.listof | Plot a List of Things | |

cauchy.estpcf | Fit the Neyman-Scott cluster process with Cauchy kernel | |

runifpoint3 | Generate N Uniform Random Points in Three Dimensions | |

rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |

Kmeasure | Reduced Second Moment Measure | |

round.ppp | Apply Numerical Rounding to Spatial Coordinates | |

as.hyperframe | Convert Data to Hyperframe | |

Kmodel | K function of a model | |

quadrats | Divide Region into Quadrats | |

blur | Apply Gaussian Blur to a Pixel Image | |

setcov | Set Covariance of a Window | |

project.ppm | Force Point Process Model to be Valid | |

discretise | Safely Convert Point Pattern Window to Binary Mask | |

markcorrint | Mark Correlation Integral | |

bdist.tiles | Distance to Boundary of Window | |

Kcross | Multitype K Function (Cross-type) | |

rounding | Detect Numerical Rounding | |

rthin | Random Thinning | |

unnormdensity | Weighted kernel smoother | |

Ldot | Multitype L-function (i-to-any) | |

smooth.msr | Smooth a Signed or Vector-Valued Measure | |

rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |

sessionLibs | Print Names and Version Numbers of Libraries Loaded | |

Hest | Spherical Contact Distribution Function | |

eem | Exponential Energy Marks | |

as.owin | Convert Data To Class owin | |

adaptive.density | Intensity Estimate of Point Pattern Using Tessellation | |

transect.im | Pixel Values Along a Transect | |

rpoispp | Generate Poisson Point Pattern | |

bw.relrisk | Cross Validated Bandwidth Selection for Relative Risk Estimation | |

unique.ppp | Extract Unique Points from a Spatial Point Pattern | |

Extract.ppx | Extract Subset of Multidimensional Point Pattern | |

Saturated | Saturated Pairwise Interaction model | |

rThomas | Simulate Thomas Process | |

StraussHard | The Strauss / Hard Core Point Process Model | |

methods.slrm | Methods for Spatial Logistic Regression Models | |

collapse.fv | Collapse Several Function Tables into One | |

quadrat.test | Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |

rSSI | Simulate Simple Sequential Inhibition | |

summary.ppp | Summary of a Point Pattern Dataset | |

MultiStrauss | The Multitype Strauss Point Process Model | |

scanpp | Read Point Pattern From Data File | |

bind.fv | Combine Function Value Tables | |

midpoints.psp | Midpoints of Line Segment Pattern | |

inforder.family | Infinite Order Interaction Family | |

print.quad | Print a Quadrature Scheme | |

smooth.ppp | Spatial smoothing of observations at irregular points | |

hist.im | Histogram of Pixel Values in an Image | |

fv.object | Function Value Table | |

Jmulti | Marked J Function | |

gpc2owin | Convert Polygonal Region into Different Format | |

Kmulti | Marked K-Function | |

vertices | Vertices of a Window | |

opening | Morphological Opening | |

iplot | Point and Click Interface for Displaying Spatial Data | |

pixellate.psp | Convert Line Segment Pattern to Pixel Image | |

plot.fv | Plot Function Values | |

ppm.object | Class of Fitted Point Process Models | |

perimeter | Perimeter Length of Window | |

as.linim | Convert to Pixel Image on Linear Network | |

shapley | Galaxies in the Shapley Supercluster | |

as.data.frame.psp | Coerce Line Segment Pattern to a Data Frame | |

marks | Marks of a Point Pattern | |

scalardilate | Apply Scalar Dilation | |

rcellnumber | Generate Random Numbers of Points for Cell Process | |

simplenet | Simple Example of Linear Network | |

plot.kppm | Plot a fitted cluster point process | |

cbind.hyperframe | Combine Hyperframes by Rows or by Columns | |

logLik.ppm | Log Likelihood and AIC for Point Process Model | |

linearKinhom | Inhomogeneous Linear K Function | |

pixelquad | Quadrature Scheme Based on Pixel Grid | |

hybrid.family | Hybrid Interaction Family | |

localK | Neighbourhood density function | |

as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |

whist | Weighted Histogram | |

npoints | Number of Points in a Point Pattern | |

chorley | Chorley-Ribble Cancer Data | |

rotate.ppp | Rotate a Point Pattern | |

pool.rat | Pool Data from Several Ratio Objects | |

leverage.ppm | Leverage Measure for Spatial Point Process Model | |

rshift.splitppp | Randomly Shift a List of Point Patterns | |

LambertW | Lambert's W Function | |

contour.im | Contour plot of pixel image | |

rstrat | Simulate Stratified Random Point Pattern | |

bw.frac | Bandwidth Selection Based on Window Geometry | |

distmap.psp | Distance Map of Line Segment Pattern | |

crossdist | Pairwise distances | |

crossdist.default | Pairwise distances between two different sets of points | |

predict.lppm | Predict Point Process Model on Linear Network | |

anova.lppm | ANOVA for Fitted Point Process Models on Linear Network | |

psst | Pseudoscore Diagnostic For Fitted Model against General Alternative | |

rCauchy | Simulate Neyman-Scott Point Process with Cauchy cluster kernel | |

delaunay | Delaunay Triangulation of Point Pattern | |

rotate.owin | Rotate a Window | |

nncorr | Nearest-Neighbour Correlation Indices of Marked Point Pattern | |

trim.rectangle | Cut margins from rectangle | |

summary.listof | Summary of a List of Things | |

density.psp | Kernel Smoothing of Line Segment Pattern | |

Kscaled | Locally Scaled K-function | |

hamster | Aherne's hamster tumour data | |

methods.boxx | Methods for Multi-Dimensional Box | |

intensity.lpp | Empirical Intensity of Point Pattern on Linear Network | |

localpcf | Local pair correlation function | |

as.hyperframe.ppx | Extract coordinates and marks of multidimensional point pattern | |

linearK | Linear K Function | |

volume | Volume of an Object | |

edges2vees | List Dihedral Triples in a Graph | |

Kdot | Multitype K Function (i-to-any) | |

unmark | Remove Marks | |

chicago | Chicago Street Crime Data | |

methods.linnet | Methods for Linear Networks | |

Kcom | Model Compensator of K Function | |

clickpoly | Interactively Define a Polygon | |

owin | Create a Window | |

lpp | Create Point Pattern on Linear Network | |

lengths.psp | Lengths of Line Segments | |

model.matrix.ppm | Extract Design Matrix from Point Process Model | |

levelset | Level Set of a Pixel Image | |

plot.fasp | Plot a Function Array | |

crossdist.psp | Pairwise distances between two different line segment patterns | |

linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |

slrm | Spatial Logistic Regression | |

Extract.quad | Subset of Quadrature Scheme | |

eval.fasp | Evaluate Expression Involving Function Arrays | |

kppm | Fit Cluster or Cox Point Process Model | |

rPoissonCluster | Simulate Poisson Cluster Process | |

shift.psp | Apply Vector Translation To Line Segment Pattern | |

as.data.frame.im | Convert Pixel Image to Data Frame | |

box3 | Three-Dimensional Box | |

pcf.fasp | Pair Correlation Function obtained from array of K functions | |

simulate.ppm | Simulate a Fitted Gibbs Point Process Model | |

mincontrast | Method of Minimum Contrast | |

intensity | Intensity of a Dataset or a Model | |

diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |

as.tess | Convert Data To Tessellation | |

longleaf | Longleaf Pines Point Pattern | |

plot.influence.ppm | Plot Influence Measure | |

crossing.psp | Crossing Points of Two Line Segment Patterns | |

shift | Apply Vector Translation | |

copper | Berman-Huntington points and lines data | |

sidelengths.owin | Side Lengths of Enclosing Rectangle of a Window | |

spatstat-package | The Spatstat Package | |

methods.lppm | Methods for Fitted Point Process Models on a Linear Network | |

intensity.ppm | Intensity of Fitted Point Process Model | |

update.kppm | Update a Fitted Cluster Point Process Model | |

rHardcore | Perfect Simulation of the Hardcore Process | |

mean.im | Maximum, Minimum, Mean, Median, Range or Sum of Pixel Values in an Image | |

timed | Record the Computation Time | |

Lcross | Multitype L-function (cross-type) | |

lurking | Lurking variable plot | |

runifpoint | Generate N Uniform Random Points | |

Gest | Nearest Neighbour Distance Function G | |

plot.slrm | Plot a Fitted Spatial Logistic Regression | |

crossdist.ppp | Pairwise distances between two different point patterns | |

flipxy | Exchange X and Y Coordinates | |

pairwise.family | Pairwise Interaction Process Family | |

km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |

paracou | Kimboto trees at Paracou, French Guiana | |

nnwhich.ppx | Nearest Neighbours in Any Dimensions | |

anova.slrm | Analysis of Deviance for Spatial Logistic Regression Models | |

harmonic | Basis for Harmonic Functions | |

triplet.family | Triplet Interaction Family | |

mucosa | Cells in Gastric Mucosa | |

profilepl | Profile Maximum Pseudolikelihood | |

which.max.im | Identify Pixelwise Maximum of Several Pixel Images | |

Triplets | The Triplet Point Process Model | |

plot.msr | Plot a Signed or Vector-Valued Measure | |

vcov.slrm | Variance-Covariance Matrix for a Fitted Spatial Logistic Regression | |

tess | Create a Tessellation | |

osteo | Osteocyte Lacunae Data: Replicated Three-Dimensional Point Patterns | |

rStraussHard | Perfect Simulation of the Strauss-Hardcore Process | |

is.multitype | Test whether Object is Multitype | |

matclust.estpcf | Fit the Matern Cluster Point Process by Minimum Contrast Using Pair Correlation | |

split.im | Divide Image Into Sub-images | |

latest.news | Print News About Latest Version of Package | |

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |

owin.object | Class owin | |

methods.layered | Methods for Layered Objects | |

is.stationary | Recognise Stationary and Poisson Point Process Models | |

clmfires | Castilla-La Mancha Forest Fires | |

markvario | Mark Variogram | |

is.subset.owin | Determine Whether One Window is Contained In Another | |

pairs.im | Scatterplot Matrix for Pixel Images | |

nearest.raster.point | Find Pixel Nearest to a Given Point | |

rmhexpand | Specify Simulation Window or Expansion Rule | |

nnwhich.pp3 | Nearest neighbours in three dimensions | |

identify.ppp | Identify Points in a Point Pattern | |

lgcp.estpcf | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |

pairdist.psp | Pairwise distances between line segments | |

pixellate.owin | Convert Window to Pixel Image | |

as.fv | Convert Data To Class fv | |

quad.object | Class of Quadrature Schemes | |

Kest | K-function | |

data.ppm | Extract Original Data from a Fitted Point Process Model | |

quadscheme.logi | Generate a Logistic Regression Quadrature Scheme from a Point Pattern | |

rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |

markcorr | Mark Correlation Function | |

vargamma.estK | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |

pixellate | Convert Spatial Object to Pixel Image | |

imcov | Spatial Covariance of a Pixel Image | |

nndist.ppx | Nearest Neighbour Distances in Any Dimensions | |

pcf | Pair Correlation Function | |

diameter.owin | Diameter of a Window | |

plot.im | Plot a Pixel Image | |

coef.ppm | Coefficients of Fitted Point Process Model | |

Geyer | Geyer's Saturation Point Process Model | |

split.ppx | Divide Multidimensional Point Pattern into Sub-patterns | |

rescue.rectangle | Convert Window Back To Rectangle | |

dirichlet | Dirichlet Tessellation of Point Pattern | |

plot.quad | plot a Spatial Quadrature Scheme | |

rmpoint | Generate N Random Multitype Points | |

bw.smoothppp | Cross Validated Bandwidth Selection for Spatial Smoothing | |

ppm | Fit Point Process Model to Data | |

pppmatching | Create a Point Matching | |

rjitter | Random Perturbation of a Point Pattern | |

rNeymanScott | Simulate Neyman-Scott Process | |

pcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Type-i-To-Any-Type) | |

markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |

hyytiala | Scots pines and other trees at Hyytiala | |

residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |

lansing | Lansing Woods Point Pattern | |

bw.diggle | Cross Validated Bandwidth Selection for Kernel Density | |

model.frame.ppm | Extract the Variables in a Point Process Model | |

ripras | Estimate window from points alone | |

summary.splitppp | Summary of a Split Point Pattern | |

quadrat.test.splitppp | Dispersion Test of CSR for Split Point Pattern Based on Quadrat Counts | |

quantile.im | Sample Quantiles of Pixel Image | |

connected | Connected components | |

clarkevans | Clark and Evans Aggregation Index | |

deltametric | Delta Metric | |

plot.ppp | plot a Spatial Point Pattern | |

runiflpp | Uniform Random Points on a Linear Network | |

plot.owin | Plot a Spatial Window | |

project2segment | Move Point To Nearest Line | |

square | Square Window | |

dummify | Convert Data to Numeric Values by Constructing Dummy Variables | |

nncross.pp3 | Nearest Neighbours Between Two Patterns in 3D | |

as.ppp | Convert Data To Class ppp | |

rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |

ppp | Create a Point Pattern | |

nndist.pp3 | Nearest neighbour distances in three dimensions | |

scan.test | Spatial Scan Test | |

qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |

spatstat-internal | Internal spatstat functions | |

pairdist.lpp | Pairwise shortest-path distances between points on a linear network | |

disc | Circular Window | |

relrisk | Nonparametric Estimate of Spatially-Varying Relative Risk | |

methods.box3 | Methods for Three-Dimensional Box | |

nnmap | K-th Nearest Point Map | |

Extract.lpp | Extract Subset of Point Pattern on Linear Network | |

is.marked.ppp | Test Whether A Point Pattern is Marked | |

rStrauss | Perfect Simulation of the Strauss Process | |

rat | Ratio object | |

vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |

Gfox | Foxall's Distance Functions | |

summary.im | Summarizing a Pixel Image | |

psp.object | Class of Line Segment Patterns | |

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

tweak.colourmap | Change Colour Values in a Colour Map | |

bw.stoyan | Stoyan's Rule of Thumb for Bandwidth Selection | |

density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |

compatible.im | Test Whether Pixel Images Are Compatible | |

pairsat.family | Saturated Pairwise Interaction Point Process Family | |

is.im | Test Whether An Object Is A Pixel Image | |

update.ppm | Update a Fitted Point Process Model | |

rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |

rDGS | Perfect Simulation of the Diggle-Gates-Stibbard Process | |

Kres | Residual K Function | |

distmap.ppp | Distance Map of Point Pattern | |

kstest.ppm | Kolmogorov-Smirnov Test for Point Pattern or Point Process Model | |

plot.layered | Layered Plot | |

formula.ppm | Model Formulae for Gibbs Point Process Models | |

heather | Diggle's Heather Data | |

Extract.im | Extract Subset of Image | |

spokes | Spokes pattern of dummy points | |

ord.family | Ord Interaction Process Family | |

intersect.tess | Intersection of Two Tessellations | |

dclf.test | Diggle-Cressie-Loosmore-Ford and Maximum Absolute Deviation Tests | |

runifdisc | Generate N Uniform Random Points in a Disc | |

nnclean | Nearest Neighbour Clutter Removal | |

summary.ppm | Summarizing a Fitted Point Process Model | |

shift.ppp | Apply Vector Translation To Point Pattern | |

zapsmall.im | Rounding of Pixel Values | |

addvar | Added Variable Plot for Point Process Model | |

rDiggleGratton | Perfect Simulation of the Diggle-Gratton Process | |

nndist.psp | Nearest neighbour distances between line segments | |

rshift.ppp | Randomly Shift a Point Pattern | |

linearpcf | Linear Pair Correlation Function | |

affine.linnet | Apply Geometrical Transformations to a Linear Network | |

as.data.frame.hyperframe | Coerce Hyperframe to Data Frame | |

nncross | Nearest Neighbours Between Two Patterns | |

im | Create a Pixel Image Object | |

is.rectangle | Determine Type of Window | |

fitted.slrm | Fitted Probabilities for Spatial Logistic Regression | |

pcfdot | Multitype pair correlation function (i-to-any) | |

waka | Trees in Waka national park | |

Kmulti.inhom | Inhomogeneous Marked K-Function | |

bounding.box | Bounding Box of a Window or Point Pattern | |

fryplot | Fry Plot of Point Pattern | |

pppmatching.object | Class of Point Matchings | |

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

as.im | Convert to Pixel Image | |

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

predict.ppm | Prediction from a Fitted Point Process Model | |

tile.areas | Compute Areas of Tiles in a Tessellation | |

thomas.estpcf | Fit the Thomas Point Process by Minimum Contrast | |

K3est | K-function of a Three-Dimensional Point Pattern | |

miplot | Morishita Index Plot | |

pixellate.ppp | Convert Point Pattern to Pixel Image | |

print.owin | Print Brief Details of a Spatial Window | |

rMaternI | Simulate Matern Model I | |

varblock | Estimate Variance of Summary Statistic by Subdivision | |

bdist.pixels | Distance to Boundary of Window | |

corners | Corners of a rectangle | |

as.polygonal | Convert a Window to a Polygonal Window | |

funxy | Spatial Function Class | |

rescale.ppp | Convert Point Pattern to Another Unit of Length | |

plot.linim | Plot Pixel Image on Linear Network | |

coef.slrm | Coefficients of Fitted Spatial Logistic Regression Model | |

vcov.kppm | Variance-Covariance Matrix for a Fitted Cluster Point Process Model | |

plot.leverage.ppm | Plot Leverage Function | |

quadratcount | Quadrat counting for a point pattern | |

scaletointerval | Rescale Data to Lie Between Specified Limits | |

rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |

shift.owin | Apply Vector Translation To Window | |

default.dummy | Generate a Default Pattern of Dummy Points | |

edges2triangles | List Triangles in a Graph | |

rotate | Rotate | |

summary.owin | Summary of a Spatial Window | |

rescale.im | Convert Pixel Image to Another Unit of Length | |

rmh.ppm | Simulate from a Fitted Point Process Model | |

suffstat | Sufficient Statistic of Point Process Model | |

predict.slrm | Predicted or Fitted Values from Spatial Logistic Regression | |

summary.psp | Summary of a Line Segment Pattern Dataset | |

effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model | |

inside.owin | Test Whether Points Are Inside A Window | |

superimpose | Superimpose Several Geometric Patterns | |

rMosaicSet | Mosaic Random Set | |

summary.quad | Summarizing a Quadrature Scheme | |

layerplotargs | Extract or Replace the Plot Arguments of a Layered Object | |

interp.colourmap | Interpolate smoothly between specified colours | |

pairdist.default | Pairwise distances | |

rpoislinetess | Poisson Line Tessellation | |

lohboot | Bootstrap Confidence Bands for Summary Function | |

expand.owin | Apply Expansion Rule | |

rMatClust | Simulate Matern Cluster Process | |

incircle | Find Largest Circle Inside Window | |

rotate.im | Rotate a Pixel Image | |

ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |

is.multitype.ppp | Test Whether A Point Pattern is Multitype | |

spatstat.options | Internal Options in Spatstat Package | |

plot.ppm | plot a Fitted Point Process Model | |

plot.kstest | Plot a Spatial Kolmogorov-Smirnov Test | |

rVarGamma | Simulate Neyman-Scott Point Process with Variance Gamma cluster kernel | |

rlinegrid | Generate grid of parallel lines with random displacement | |

residuals.ppm | Residuals for Fitted Point Process Model | |

psstA | Pseudoscore Diagnostic For Fitted Model against Area-Interaction Alternative | |

quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |

rshift.psp | Randomly Shift a Line Segment Pattern | |

urkiola | Urkiola Woods Point Pattern | |

sharpen | Data Sharpening of Point Pattern | |

rshift | Random Shift | |

pool.quadrattest | Pool Several Quadrat Tests | |

redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |

plot.bermantest | Plot Result of Berman Test | |

rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |

is.empty | Test Whether An Object Is Empty | |

nztrees | New Zealand Trees Point Pattern | |

pairdist.ppx | Pairwise Distances in Any Dimensions | |

unitname | Name for Unit of Length | |

union.quad | Union of Data and Dummy Points | |

rMaternII | Simulate Matern Model II | |

intensity.ppp | Empirical Intensity of Point Pattern | |

istat | Point and Click Interface for Exploratory Analysis of Point Pattern | |

reflect | Reflect In Origin | |

No Results! |

## Last month downloads

## Details

Date | 2013-08-13 |

License | GPL (>= 2) |

URL | http://www.spatstat.org |

LazyData | true |

LazyLoad | true |

ByteCompile | true |

Packaged | 2013-08-13 08:23:55 UTC; adrian |

NeedsCompilation | yes |

Repository | CRAN |

Date/Publication | 2013-08-13 12:42:15 |

depends | base (>= 3.0.0) , deldir (>= 0.0-21) , graphics , grDevices , mgcv , R (>= 3.0.0) , stats , utils |

suggests | gpclib , gsl , locfit , maptools , RandomFields (>= 2.0.60) , rpanel , scatterplot3d , sm , spatial , tensor , tkrplot |

Contributors | Rolf Turner, Adrian Baddeley |

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