# spatstat v1.25-4

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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 | |

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

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

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

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

discpartarea | Area of Part of Disc | |

harmonic | Basis for Harmonic Functions | |

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

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

eval.fasp | Evaluate Expression Involving Function Arrays | |

distmap.owin | Distance Map of Window | |

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

Poisson | Poisson Point Process Model | |

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

areaGain | Difference of Disc Areas | |

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

hyperframe | Hyper Data Frame | |

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

as.ppp | Convert Data To Class ppp | |

bind.fv | Combine Function Value Tables | |

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

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

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

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

infline | Infinite Straight Lines | |

Iest | Estimate the I-function | |

as.interact | Extract Interaction Structure | |

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

plot.leverage.ppm | Plot Leverage Function | |

Kmodel | K function of a model | |

bdist.points | Distance to Boundary of Window | |

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

as.psp | Convert Data To Class psp | |

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

colourtools | Convert and Compare Colours in Different Formats | |

ants | Harkness-Isham ants' nests data | |

as.hyperframe | Convert Data to Hyperframe | |

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

compareFit | Residual Diagnostics for Multiple Fitted Models | |

gpc2owin | Convert Polygonal Region into Different Format | |

erosion | Morphological Erosion | |

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

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

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

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

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

nndist | Nearest neighbour distances | |

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

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

owin.object | Class owin | |

AreaInter | The Area Interaction Point Process Model | |

gridcentres | Rectangular grid of points | |

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

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

distmap | Distance Map | |

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

dfbetas.ppm | Parameter influence measure | |

Hest | Spherical Contact Distribution Function | |

as.rectangle | Window Frame | |

boxx | Multi-Dimensional Box | |

midpoints.psp | Midpoints of Line Segment Pattern | |

circumradius | Circumradius and Diameter of a Linear Network | |

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

dirichlet | Dirichlet Tessellation of Point Pattern | |

bdist.pixels | Distance to Boundary of Window | |

crossdist | Pairwise distances | |

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

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

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

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

Kmulti | Marked K-Function | |

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

linearKinhom | Inhomogeneous Linear K Function | |

perimeter | Perimeter Length of Window | |

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

Gest | Nearest Neighbour Distance Function G | |

eval.fv | Evaluate Expression Involving Functions | |

Lcross.inhom | Inhomogeneous Cross Type L Function | |

ppp | Create a Point Pattern | |

ewcdf | Weighted Empirical Cumulative Distribution Function | |

eval.im | Evaluate Expression Involving Pixel Images | |

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

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

anemones | Beadlet Anemones Data | |

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

Extract.im | Extract Subset of Image | |

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

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

affine.owin | Apply Affine Transformation To Window | |

nncross | Nearest Neighbours Between Two Patterns | |

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

progressreport | Print Progress Reports | |

Extract.fasp | Extract Subset of Function Array | |

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

endpoints.psp | Endpoints of Line Segment Pattern | |

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

fv | Create a Function Value Table | |

quad.object | Class of Quadrature Schemes | |

Kinhom | Inhomogeneous K-function | |

project2segment | Move Point To Nearest Line | |

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

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

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

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

clickpoly | Interactively Define a Polygon | |

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

colourmap | Colour Lookup Tables | |

as.owin | Convert Data To Class owin | |

box3 | Three-Dimensional Box | |

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

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

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

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

bronzefilter | Bronze gradient filter data | |

quadratcount | Quadrat counting for a point pattern | |

finpines | Pine saplings in Finland. | |

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

concatxy | Concatenate x,y Coordinate Vectors | |

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

MultiHard | The Multitype Hard Core Point Process Model | |

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

rPoissonCluster | Simulate Poisson Cluster Process | |

integral.im | Integral of a Pixel Image | |

rMaternI | Simulate Matern Model I | |

lut | Lookup Tables | |

area.owin | Area of a Window | |

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

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

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

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

distfun | Distance Map as a Function | |

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

append.psp | Combine Two Line Segment Patterns | |

layered | Create List of Plotting Layers | |

rNeymanScott | Simulate Neyman-Scott Process | |

fv.object | Function Value Table | |

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

plot.colourmap | Plot a Colour Map | |

logLik.slrm | Loglikelihood of Spatial Logistic Regression | |

chorley | Chorley-Ribble Cancer Data | |

as.tess | Convert Data To Tessellation | |

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

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

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

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

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

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

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

linim | Create Pixel Image on Linear Network | |

envelope.envelope | Recompute Envelopes | |

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

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

persp.im | Perspective Plot of Pixel Image | |

linearK | Linear K Function | |

rpoisline | Generate Poisson Random Line Process | |

nnclean | Nearest Neighbour Clutter Removal | |

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

pairs.im | Scatterplot Matrix for Pixel Images | |

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

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

methods.linnet | Methods for Linear Networks | |

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

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

lurking | Lurking variable plot | |

model.frame.ppm | Extract the Environment of a Point Process Model | |

marks | Marks of a Point Pattern | |

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

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

rpoispp | Generate Poisson Point Pattern | |

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

bei | Tropical rain forest trees | |

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

diameter | Diameter of an Object | |

fasp.object | Function Arrays for Spatial Patterns | |

nearestsegment | Find Line Segment Nearest to Each Point | |

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

rotate.ppp | Rotate a Point Pattern | |

is.marked | Test Whether Marks Are Present | |

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

localKinhom | Inhomogeneous Neighbourhood Density Function | |

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

corners | Corners of a rectangle | |

nnwhich.ppx | Nearest Neighbours in Any Dimensions | |

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

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

rMosaicField | Mosaic Random Field | |

npfun | Dummy Function Returns Number of Points | |

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

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

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

rSSI | Simulate Simple Sequential Inhibition | |

pairdist.pp3 | Pairwise distances in Three Dimensions | |

shift.owin | Apply Vector Translation To Window | |

localK | Neighbourhood density function | |

clickjoin | Interactively join vertices on a plot | |

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

lpp | Create Point Pattern on Linear Network | |

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

shapley | Galaxies in the Shapley Supercluster | |

nnwhich.pp3 | Nearest neighbours in three dimensions | |

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

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

methods.units | Methods for Units | |

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

affine | Apply Affine Transformation | |

pairdist.ppp | Pairwise distances | |

plot.layered | Layered Plot | |

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

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

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

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

rat | Ratio object | |

spatstat-deprecated | Deprecated spatstat functions | |

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

quantile.im | Sample Quantiles of Pixel Image | |

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

flipxy | Exchange X and Y Coordinates | |

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

triplet.family | Triplet Interaction Family | |

matchingdist | Distance for a Point Pattern Matching | |

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

plot.fv | Plot Function Values | |

delaunay | Delaunay Triangulation of Point Pattern | |

profilepl | Profile Maximum Pseudolikelihood | |

quadrat.test.splitppp | Chi-Squared Test of CSR for Split Point Pattern | |

im.object | Class of Images | |

summary.owin | Summary of a Spatial Window | |

rmpoispp | Generate Multitype Poisson Point Pattern | |

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

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

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

pool.envelope | Pool Data from Several Envelopes | |

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

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

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

eem | Exponential Energy Marks | |

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

linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |

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

rStrauss | Perfect Simulation of the Strauss Process | |

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

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

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

plot.owin | Plot a Spatial Window | |

reach | Interaction Distance of a Point Process | |

spatstat-internal | Internal spatstat functions | |

as.im | Convert to Pixel Image | |

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

LennardJones | The Lennard-Jones Potential | |

square | Square Window | |

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

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

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

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

nnwhich | Nearest neighbour | |

Kest.fft | K-function using FFT | |

opening | Morphological Opening | |

Linhom | L-function | |

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

ord.family | Ord Interaction Process Family | |

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

gorillas | Gorilla Nesting Sites | |

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

plot.influence.ppm | Plot Influence Measure | |

rpoislpp | Poisson Point Process on a Linear Network | |

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

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

rpoint | Generate N Random Points | |

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

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

incircle | Find Largest Circle Inside Window | |

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

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

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

lengths.psp | Lengths of Line Segments | |

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

rMatClust | Simulate Matern Cluster Process | |

rhohat | Smoothing Estimate of Covariate Transformation | |

plot.envelope | Plot a Simulation Envelope | |

pcf | Pair Correlation Function | |

markvario | Mark Variogram | |

plot.bermantest | Plot Result of Berman Test | |

bramblecanes | Hutchings' Bramble Canes data | |

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

rescue.rectangle | Convert Window Back To Rectangle | |

pppmatching.object | Class of Point Matchings | |

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

spatstat.options | Internal Options in Spatstat Package | |

scanpp | Read Point Pattern From Data File | |

unnormdensity | Weighted kernel smoother | |

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

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

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

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

simplenet | Simple Example of Linear Network | |

fryplot | Fry Plot of Point Pattern | |

DiggleGratton | Diggle-Gratton model | |

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

volume | Volume of an Object | |

pool | Pool Data | |

gridweights | Compute Quadrature Weights Based on Grid Counts | |

Strauss | The Strauss Point Process Model | |

pppmatching | Create a Point Matching | |

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

Extract.fv | Extract Subset of Function Values | |

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

betacells | Beta Ganglion Cells in Cat Retina | |

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

rjitter | Random Perturbation of a Point Pattern | |

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

MultiStrauss | The Multitype Strauss Point Process Model | |

convexhull.xy | Convex Hull of Points | |

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

tess | Create a Tessellation | |

Gres | Residual G Function | |

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

ripras | Estimate window from points alone | |

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

rknn | Theoretical Distribution of Nearest Neighbour Distance | |

plot.ppp | plot a Spatial Point Pattern | |

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

suffstat | Sufficient Statistic of Point Process Model | |

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

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

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

setcov | Set Covariance of a Window | |

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

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

rlabel | Random Re-Labelling of Point Pattern | |

japanesepines | Japanese Pines Point Pattern | |

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

levelset | Level Set of a Pixel Image | |

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

iplot | Point and Click Interface for Displaying a Point Pattern | |

markcorrint | Mark Correlation Integral | |

miplot | Morishita Index Plot | |

areaLoss | Difference of Disc Areas | |

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

contour.listof | Plot a List of Things | |

bdist.tiles | Distance to Boundary of Window | |

interp.im | Interpolate a Pixel Image | |

rstrat | Simulate Stratified Random Point Pattern | |

plot.linnet | Plot a linear network | |

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

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

im | Create a Pixel Image Object | |

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

Ldot.inhom | Inhomogeneous Multitype L Dot Function | |

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

Lest | L-function | |

smooth.fv | Apply Smoothing to Function Values | |

disc | Circular Window | |

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

envelope | Simulation Envelopes of Summary Function | |

summary.quad | Summarizing a Quadrature Scheme | |

Saturated | Saturated Pairwise Interaction model | |

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

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

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

pairdist | Pairwise distances | |

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

distmap.ppp | Distance Map of Point Pattern | |

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

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

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

clickppp | Interactively Add Points | |

spatstat-package | The Spatstat Package | |

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

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

rmpoint | Generate N Random Multitype Points | |

pairdist.ppx | Pairwise Distances in Any Dimensions | |

diameter.owin | Diameter of a Window | |

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

vertices | Vertices of a Window | |

summary.im | Summarizing a Pixel Image | |

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

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

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

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

dilated.areas | Areas of Morphological Dilations | |

quadrats | Divide Region into Quadrats | |

expand.owin | Expand Window By Factor | |

Ord | Generic Ord Interaction model | |

complement.owin | Take Complement of a Window | |

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

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

BadGey | Hybrid Geyer Point Process Model | |

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

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

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

longleaf | Longleaf Pines Point Pattern | |

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

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

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

Kest | K-function | |

Kcom | Model Compensator of K Function | |

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

Tstat | Third order summary statistic | |

markcorr | Mark Correlation Function | |

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

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

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

murchison | Murchison gold deposits | |

kppm | Fit Cluster or Cox Point Process Model | |

owin | Create a Window | |

psp | Create a Line Segment Pattern | |

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

pairwise.family | Pairwise Interaction Process Family | |

trim.rectangle | Cut margins from rectangle | |

is.multitype | Test whether Object is Multitype | |

Softcore | The Soft Core Point Process Model | |

ppp.object | Class of Point Patterns | |

connected | Connected components of an image or window | |

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

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

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

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

pairdist.psp | Pairwise distances between line segments | |

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

deltametric | Delta Metric | |

copper | Berman-Huntington points and lines data | |

rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |

hamster | Aherne's hamster tumour data | |

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

Gfox | Foxall's Distance Functions | |

plot.fasp | Plot a Function Array | |

dilation | Morphological Dilation | |

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

cells | Biological Cells Point Pattern | |

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

harmonise.im | Make Pixel Images Compatible | |

runiflpp | Uniform Random Points on a Linear Network | |

unmark | Remove Marks | |

pixellate.owin | Convert Window to Pixel Image | |

heather | Diggle's Heather Data | |

rshift | Random Shift | |

flu | Influenza Virus Proteins | |

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

periodify | Make Periodic Copies of a Spatial Pattern | |

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

rotate | Rotate | |

psp.object | Class of Line Segment Patterns | |

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

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

spokes | Spokes pattern of dummy points | |

mincontrast | Method of Minimum Contrast | |

rLGCP | Simulate Log-Gaussian Cox Process | |

rescale | Convert dataset to another unit of length | |

simdat | Simulated Point Pattern | |

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

pixelquad | Quadrature Scheme Based on Pixel Grid | |

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

linearpcf | Linear Pair Correlation Function | |

Extract.quad | Subset of Quadrature Scheme | |

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

Hardcore | The Hard Core Point Process Model | |

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

runifpoint | Generate N Uniform Random Points | |

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

Triplets | The Triplet Point Process Model | |

Pairwise | Generic Pairwise Interaction model | |

Gcom | Model Compensator of Nearest Neighbour Function | |

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

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

rpoislinetess | Poisson Line Tessellation | |

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

slrm | Spatial Logistic Regression | |

rshift.ppp | Randomly Shift a Point Pattern | |

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

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

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

pairdist.default | Pairwise distances | |

stieltjes | Compute Integral of Function Against Cumulative Distribution | |

clarkevans.test | Clark and Evans Test | |

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

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

plot.tess | Plot a tessellation | |

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

convexhull | Convex Hull | |

superimpose | Superimpose Several Geometric Patterns | |

Geyer | Geyer's Saturation Point Process Model | |

ponderosa | Ponderosa Pine Tree Point Pattern | |

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

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

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

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

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

sharpen | Data Sharpening of Point Pattern | |

methods.distfun | Methods for Distance Functions | |

imcov | Spatial Covariance of a Pixel Image | |

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

pixellate | Convert Spatial Object to Pixel Image | |

npoints | Number of Points in a Point Pattern | |

sumouter | Compute Quadratic Forms | |

rsyst | Simulate systematic random point pattern | |

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

varblock | Estimate Variance of Summary Statistic by Subdivision | |

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

model.images | Compute Images of Constructed Covariates | |

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

Kres | Residual K Function | |

linnet | Create a Linear Network | |

markconnect | Mark Connection Function | |

lansing | Lansing Woods Point Pattern | |

eroded.areas | Areas of Morphological Erosions | |

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

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

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

rotate.owin | Rotate a Window | |

Kscaled | Locally Scaled K-function | |

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

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

OrdThresh | Ord's Interaction model | |

angles.psp | Orientation Angles of Line Segments | |

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

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

amacrine | Hughes' Amacrine Cell Data | |

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

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

pp3 | Three Dimensional Point Pattern | |

nbfires | Point Patterns of New Brunswick Forest Fires | |

rThomas | Simulate Thomas Process | |

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

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

pppdist | Distance Between Two Point Patterns | |

Kmeasure | Reduced Second Moment Measure | |

rcell | Simulate Baddeley-Silverman Cell Process | |

Emark | Diagnostics for random marking | |

rHardcore | Perfect Simulation of the Hardcore Process | |

clarkevans | Clark and Evans Aggregation Index | |

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

plot.quad | plot a Spatial Quadrature Scheme | |

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

chicago | Chicago Street Crime Data | |

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

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

tiles | Extract List of Tiles in a Tessellation | |

rthin | Random Thinning | |

Fiksel | The Fiksel Interaction | |

Gmulti | Marked Nearest Neighbour Distance Function | |

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

Kcross.inhom | Inhomogeneous Cross K Function | |

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

contour.im | Contour plot of pixel image | |

demopat | Artificial Data Point Pattern | |

intersect.tess | Intersection of Two Tessellations | |

localpcf | Local pair correlation function | |

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

inforder.family | Infinite Order Interaction Family | |

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

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

compatible | Test Whether Objects Are Compatible | |

nztrees | New Zealand Trees Point Pattern | |

ppx | Multidimensional Space-Time Point Pattern | |

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

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

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

rMaternII | Simulate Matern Model II | |

msr | Signed or Vector-Valued Measure | |

scaletointerval | Rescale Data to Lie Between Specified Limits | |

shift | Apply Vector Translation | |

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

spruces | Spruces Point Pattern | |

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

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

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

ppm | Fit Point Process Model to Data | |

pcfinhom | Inhomogeneous Pair Correlation Function | |

rgbim | Create Colour-Valued Pixel Image | |

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

print.quad | Print a Quadrature Scheme | |

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

scan.test | Spatial Scan Test | |

urkiola | Urkiola Woods Point Pattern | |

pointsOnLines | Place Points Evenly Along Specified Lines | |

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

rMosaicSet | Mosaic Random Set | |

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

zapsmall.im | Rounding of Pixel Values | |

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

whist | Weighted Histogram | |

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

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

plot.im | Plot a Pixel Image | |

rGaussPoisson | Simulate Gauss-Poisson Process | |

plot.listof | Plot a List of Things | |

rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |

plot.hyperframe | Plot Entries in a Hyperframe | |

border | Border Region of a Window | |

swedishpines | Swedish Pines Point Pattern | |

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

Jmulti | Marked J Function | |

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

blur | Apply Gaussian Blur to a Pixel Image | |

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

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

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

rotate.psp | Rotate a Line Segment Pattern | |

Fest | Estimate the empty space function F | |

closing | Morphological Closing | |

edges2triangles | List Triangles in a Graph | |

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

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

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

default.expand | Compute Expansion Window for Simulation | |

Jest | Estimate the J-function | |

centroid.owin | Centroid of a window | |

letterR | Window in Shape of Letter R | |

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

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

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

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

unitname | Name for Unit of Length | |

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

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

No Results! |

## Last month downloads

## Details

Date | 2012-02-29 |

License | GPL (>= 2) |

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

LazyData | true |

LazyLoad | true |

ByteCompile | true |

Packaged | 2012-02-29 10:38:58 UTC; adrian |

Repository | CRAN |

Date/Publication | 2012-02-29 13:06:31 |

depends | base (>= 2.14.0) , deldir (>= 0.0-10) , graphics , mgcv , R (>= 2.14.0) , stats , utils |

suggests | gpclib , maptools , RandomFields (>= 2.0) , rpanel , scatterplot3d , sm , spatial , tkrplot |

Contributors | Rolf Turner, Adrian Baddeley |

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