# spatstat v1.31-3

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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 | |

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

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

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

lohboot | Bootstrap Confidence Bands for Summary Function | |

murchison | Murchison gold deposits | |

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

nnwhich.pp3 | Nearest neighbours in three dimensions | |

pairs.im | Scatterplot Matrix for Pixel Images | |

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

pcfinhom | Inhomogeneous Pair Correlation Function | |

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

plot.colourmap | Plot a Colour Map | |

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

plot.tess | Plot a tessellation | |

ponderosa | Ponderosa Pine Tree Point Pattern | |

rGaussPoisson | Simulate Gauss-Poisson Process | |

ppx | Multidimensional Space-Time Point Pattern | |

linnet | Create a Linear Network | |

rat | Ratio object | |

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

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

miplot | Morishita Index Plot | |

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

print.quad | Print a Quadrature Scheme | |

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

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

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

rThomas | Simulate Thomas Process | |

setcov | Set Covariance of a Window | |

varblock | Estimate Variance of Summary Statistic by Subdivision | |

rhohat | Smoothing Estimate of Covariate Transformation | |

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

pairdist.psp | Pairwise distances between line segments | |

msr | Signed or Vector-Valued Measure | |

pixellate | Convert Spatial Object to Pixel Image | |

persp.im | Perspective Plot of Pixel Image | |

npoints | Number of Points in a Point Pattern | |

urkiola | Urkiola Woods Point Pattern | |

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

transect.im | Pixel Values Along a Transect | |

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

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

plot.hyperframe | Plot Entries in a Hyperframe | |

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

plot.ppp | plot a Spatial Point Pattern | |

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

pp3 | Three Dimensional Point Pattern | |

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

vertices | Vertices of a Window | |

ppp.object | Class of Point Patterns | |

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

quadratcount | Quadrat counting for a point pattern | |

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

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

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

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

square | Square Window | |

swedishpines | Swedish Pines Point Pattern | |

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

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

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

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

rpoisline | Generate Poisson Random Line Process | |

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

levelset | Level Set of a Pixel Image | |

ord.family | Ord Interaction Process Family | |

plot.bermantest | Plot Result of Berman Test | |

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

scalardilate | Apply Scalar Dilation | |

scanpp | Read Point Pattern From Data File | |

suffstat | Sufficient Statistic of Point Process Model | |

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

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

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

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

rMaternII | Simulate Matern Model II | |

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

rMosaicSet | Mosaic Random Set | |

rpoislinetess | Poisson Line Tessellation | |

longleaf | Longleaf Pines Point Pattern | |

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

linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |

tess | Create a Tessellation | |

markcorr | Mark Correlation Function | |

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

matchingdist | Distance for a Point Pattern Matching | |

summary.quad | Summarizing a Quadrature Scheme | |

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

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

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

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

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

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

lengths.psp | Lengths of Line Segments | |

nearestsegment | Find Line Segment Nearest to Each Point | |

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

owin.object | Class owin | |

pairdist.ppx | Pairwise Distances in Any Dimensions | |

methods.funxy | Methods for Spatial Functions | |

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

lansing | Lansing Woods Point Pattern | |

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

letterR | Window in Shape of Letter R | |

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

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

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

linim | Create Pixel Image on Linear Network | |

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

reach | Interaction Distance of a Point Process | |

japanesepines | Japanese Pines Point Pattern | |

lurking | Lurking variable plot | |

lpp | Create Point Pattern on Linear Network | |

nnmap | K-th Nearest Point Map | |

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

plot.owin | Plot a Spatial Window | |

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

periodify | Make Periodic Copies of a Spatial Pattern | |

rMosaicField | Mosaic Random Field | |

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

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

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

owin | Create a Window | |

psp | Create a Line Segment Pattern | |

perimeter | Perimeter Length of Window | |

rjitter | Random Perturbation of a Point Pattern | |

pool | Pool Data | |

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

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

nnclean | Nearest Neighbour Clutter Removal | |

quantile.im | Sample Quantiles of Pixel Image | |

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

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

plot.influence.ppm | Plot Influence Measure | |

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

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

pppdist | Distance Between Two Point Patterns | |

triplet.family | Triplet Interaction Family | |

nndist | Nearest neighbour distances | |

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

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

rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |

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

quad.object | Class of Quadrature Schemes | |

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

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

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

rpoislpp | Poisson Point Process on a Linear Network | |

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

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

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

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

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

rmhexpand | Specify Simulation Window or Expansion Rule | |

rmpoint | Generate N Random Multitype Points | |

rotate.psp | Rotate a Line Segment Pattern | |

rpoint | Generate N Random Points | |

slrm | Spatial Logistic Regression | |

runiflpp | Uniform Random Points on a Linear Network | |

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

rounding | Detect Numerical Rounding | |

simdat | Simulated Point Pattern | |

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

rshift.ppp | Randomly Shift a Point Pattern | |

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

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

timed | Record the Computation Time | |

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

is.rectangle | Determine Type of Window | |

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

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

sharpen | Data Sharpening of Point Pattern | |

unitname | Name for Unit of Length | |

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

layered | Create List of Plotting Layers | |

is.multitype | Test whether Object is Multitype | |

localKinhom | Inhomogeneous Neighbourhood Density Function | |

methods.layered | Methods for Layered Objects | |

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

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

marks | Marks of a Point Pattern | |

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

paracou | Kimboto trees at Paracou, French Guiana | |

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

nnwhich.ppx | Nearest Neighbours in Any Dimensions | |

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

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

profilepl | Profile Maximum Pseudolikelihood | |

rPoissonCluster | Simulate Poisson Cluster Process | |

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

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

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

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

reflect | Reflect In Origin | |

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

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

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

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

DiggleGratton | Diggle-Gratton model | |

rthin | Random Thinning | |

Extract.linnet | Extract Subset of Linear Network | |

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

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

shapley | Galaxies in the Shapley Supercluster | |

shift | Apply Vector Translation | |

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

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

spatstat-package | The Spatstat Package | |

linearK | Linear K Function | |

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

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

trim.rectangle | Cut margins from rectangle | |

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

Hybrid | Hybrid Interaction Point Process Model | |

markvario | Mark Variogram | |

Triplets | The Triplet Point Process Model | |

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

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

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

amacrine | Hughes' Amacrine Cell Data | |

mincontrast | Method of Minimum Contrast | |

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

nnfun | Nearest Neighbour Map as a Function | |

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

Fest | Estimate the empty space function F | |

pairdist | Pairwise distances | |

bdist.tiles | Distance to Boundary of Window | |

convexhull | Convex Hull | |

MultiHard | The Multitype Hard Core Point Process Model | |

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

pairwise.family | Pairwise Interaction Process Family | |

distcdf | Distribution Function of Interpoint Distance | |

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

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

expand.owin | Apply Expansion Rule | |

Lcross.inhom | Inhomogeneous Cross Type L Function | |

box3 | Three-Dimensional Box | |

bdist.pixels | Distance to Boundary of Window | |

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

opening | Morphological Opening | |

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

Kres | Residual K Function | |

areaLoss | Difference of Disc Areas | |

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

clarkevans.test | Clark and Evans Test | |

plot.quad | plot a Spatial Quadrature Scheme | |

as.owin | Convert Data To Class owin | |

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

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

discpartarea | Area of Part of Disc | |

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

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

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

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

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

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

rHardcore | Perfect Simulation of the Hardcore Process | |

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

rMatClust | Simulate Matern Cluster Process | |

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

harmonic | Basis for Harmonic Functions | |

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

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

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

spokes | Spokes pattern of dummy points | |

colourtools | Convert and Compare Colours in Different Formats | |

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

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

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

incircle | Find Largest Circle Inside Window | |

stieltjes | Compute Integral of Function Against Cumulative Distribution | |

inforder.family | Infinite Order Interaction Family | |

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

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

markcorrint | Mark Correlation Integral | |

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

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

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

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

ants | Harkness-Isham ants' nests data | |

gridweights | Compute Quadrature Weights Based on Grid Counts | |

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

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

plot.fasp | Plot a Function Array | |

interp.im | Interpolate a Pixel Image | |

clickjoin | Interactively join vertices on a plot | |

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

integral.im | Integral of a Pixel Image | |

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

psp.object | Class of Line Segment Patterns | |

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

rcell | Simulate Baddeley-Silverman Cell Process | |

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

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

sumouter | Compute Quadratic Forms | |

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

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

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

spruces | Spruces Point Pattern | |

rotate | Rotate | |

rshift | Random Shift | |

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

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

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

Emark | Diagnostics for random marking | |

waka | Trees in Waka national park | |

bdist.points | Distance to Boundary of Window | |

kppm | Fit Cluster or Cox Point Process Model | |

Kmodel | K function of a model | |

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

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

Extract.fasp | Extract Subset of Function Array | |

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

parres | Partial Residuals for Point Process Model | |

LennardJones | The Lennard-Jones Potential | |

Extract.quad | Subset of Quadrature Scheme | |

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

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

append.psp | Combine Two Line Segment Patterns | |

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

convexhull.xy | Convex Hull of Points | |

OrdThresh | Ord's Interaction model | |

Kmulti | Marked K-Function | |

delaunay | Delaunay Triangulation of Point Pattern | |

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

angles.psp | Orientation Angles of Line Segments | |

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

Extract.im | Extract Subset of Image | |

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

crossdist | Pairwise distances | |

rotate.ppp | Rotate a Point Pattern | |

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

rsyst | Simulate systematic random point pattern | |

rstrat | Simulate Stratified Random Point Pattern | |

fasp.object | Function Arrays for Spatial Patterns | |

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

distmap | Distance Map | |

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

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

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

compatible | Test Whether Objects Are Compatible | |

Gres | Residual G Function | |

contour.listof | Plot a List of Things | |

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

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

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

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

blur | Apply Gaussian Blur to a Pixel Image | |

connected | Connected components | |

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

Tstat | Third order summary statistic | |

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

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

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

eval.im | Evaluate Expression Involving Pixel Images | |

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

fryplot | Fry Plot of Point Pattern | |

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

dirichlet | Dirichlet Tessellation of Point Pattern | |

flu | Influenza Virus Proteins | |

concatxy | Concatenate x,y Coordinate Vectors | |

infline | Infinite Straight Lines | |

edges2triangles | List Triangles in a Graph | |

pixellate.owin | Convert Window to Pixel Image | |

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

hybrid.family | Hybrid Interaction Family | |

demopat | Artificial Data Point Pattern | |

Kinhom | Inhomogeneous K-function | |

as.ppm | Extract Fitted Point Process Model | |

anemones | Beadlet Anemones Data | |

diameter.owin | Diameter of a Window | |

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

is.marked | Test Whether Marks Are Present | |

gordon | People in Gordon Square | |

border | Border Region of a Window | |

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

methods.units | Methods for Units | |

chicago | Chicago Street Crime Data | |

linearpcf | Linear Pair Correlation Function | |

compareFit | Residual Diagnostics for Multiple Fitted Models | |

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

bronzefilter | Bronze gradient filter data | |

BadGey | Hybrid Geyer Point Process Model | |

methods.fii | Methods for Fitted Interactions | |

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

pppmatching | Create a Point Matching | |

clmfires | Castilla-La Mancha Forest Fires | |

Lest | L-function | |

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

affine | Apply Affine Transformation | |

Gcom | Model Compensator of Nearest Neighbour Function | |

zapsmall.im | Rounding of Pixel Values | |

model.images | Compute Images of Constructed Covariates | |

diameter | Diameter of an Object | |

mucosa | Cells in Gastric Mucosa | |

as.interact | Extract Interaction Structure | |

as.im | Convert to Pixel Image | |

volume | Volume of an Object | |

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

clarkevans | Clark and Evans Aggregation Index | |

dilated.areas | Areas of Morphological Dilations | |

area.owin | Area of a Window | |

nnwhich | Nearest neighbour | |

eval.fv | Evaluate Expression Involving Functions | |

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

ppp | Create a Point Pattern | |

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

pppmatching.object | Class of Point Matchings | |

Gest | Nearest Neighbour Distance Function G | |

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

Poisson | Poisson Point Process Model | |

localpcf | Local pair correlation function | |

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

rMaternI | Simulate Matern Model I | |

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

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

Softcore | The Soft Core Point Process Model | |

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

eroded.areas | Areas of Morphological Erosions | |

bramblecanes | Hutchings' Bramble Canes data | |

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

Hardcore | The Hard Core Point Process Model | |

Pairwise | Generic Pairwise Interaction model | |

rgbim | Create Colour-Valued Pixel Image | |

nztrees | New Zealand Trees Point Pattern | |

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

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

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

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

gpc2owin | Convert Polygonal Region into Different Format | |

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

Extract.fv | Extract Subset of Function Values | |

spatstat-deprecated | Deprecated spatstat functions | |

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

rmpoispp | Generate Multitype Poisson Point Pattern | |

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

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

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

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

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

unmark | Remove Marks | |

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

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

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

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

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

Ord | Generic Ord Interaction model | |

boxx | Multi-Dimensional Box | |

markconnect | Mark Connection Function | |

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

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

Ginhom | Inhomogeneous Nearest Neighbour Function | |

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

ripras | Estimate window from points alone | |

scan.test | Spatial Scan Test | |

midpoints.psp | Midpoints of Line Segment Pattern | |

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

LambertW | Lambert's W Function | |

Kcom | Model Compensator of K Function | |

nncross | Nearest Neighbours Between Two Patterns | |

erosion | Morphological Erosion | |

Hest | Spherical Contact Distribution Function | |

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

bei | Tropical rain forest trees | |

pairdist.pp3 | Pairwise distances in Three Dimensions | |

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

distmap.owin | Distance Map of Window | |

as.ppp | Convert Data To Class ppp | |

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

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

pixelquad | Quadrature Scheme Based on Pixel Grid | |

plot.envelope | Plot a Simulation Envelope | |

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

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

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

complement.owin | Take Complement of a Window | |

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

cells | Biological Cells Point Pattern | |

hyperframe | Hyper Data Frame | |

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

plot.fv | Plot Function Values | |

plot.layered | Layered Plot | |

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

im | Create a Pixel Image Object | |

plot.listof | Plot a List of Things | |

rLGCP | Simulate Log-Gaussian Cox Process | |

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

rStrauss | Perfect Simulation of the Strauss Process | |

convolve.im | Convolution of Pixel Images | |

Kmulti.inhom | Inhomogeneous Marked K-Function | |

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

envelope.envelope | Recompute Envelopes | |

closing | Morphological Closing | |

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

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

rpoispp | Generate Poisson Point Pattern | |

rlabel | Random Re-Labelling of Point Pattern | |

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

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

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

as.tess | Convert Data To Tessellation | |

corners | Corners of a rectangle | |

copper | Berman-Huntington points and lines data | |

finpines | Pine saplings in Finland. | |

colourmap | Colour Lookup Tables | |

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

Extract.owin | Extract Subset of Window | |

endpoints.psp | Endpoints of Line Segment Pattern | |

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

as.rectangle | Window Frame | |

Strauss | The Strauss Point Process Model | |

distfun | Distance Map as a Function | |

fv.object | Function Value Table | |

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

as.psp | Convert Data To Class psp | |

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

clusterset | Allard-Fraley Estimator of Cluster Feature | |

Kest | K-function | |

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

Gmulti | Marked Nearest Neighbour Distance Function | |

Jest | Estimate the J-function | |

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

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

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

ewcdf | Weighted Empirical Cumulative Distribution Function | |

imcov | Spatial Covariance of a Pixel Image | |

Kscaled | Locally Scaled K-function | |

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

centroid.owin | Centroid of a window | |

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

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

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

edges2vees | List Dihedral Triples in a Graph | |

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

harmonise.im | Make Pixel Images Compatible | |

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

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

rknn | Theoretical Distribution of Nearest Neighbour Distance | |

localK | Neighbourhood density function | |

nbfires | Point Patterns of New Brunswick Forest Fires | |

plot.linnet | Plot a linear network | |

plot.im | Plot a Pixel Image | |

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

pool.envelope | Pool Data from Several Envelopes | |

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

rSSI | Simulate Simple Sequential Inhibition | |

rotate.im | Rotate a Pixel Image | |

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

scaletointerval | Rescale Data to Lie Between Specified Limits | |

shift.owin | Apply Vector Translation To Window | |

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

summary.owin | Summary of a Spatial Window | |

Kcross.inhom | Inhomogeneous Cross K Function | |

Kest.fft | K-function using FFT | |

unnormdensity | Weighted kernel smoother | |

chorley | Chorley-Ribble Cancer Data | |

clickppp | Interactively Add Points | |

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

eval.fasp | Evaluate Expression Involving Function Arrays | |

gorillas | Gorilla Nesting Sites | |

hyytiala | Scots pines and other trees at Hyytiala | |

intersect.tess | Intersection of Two Tessellations | |

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

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

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

Finhom | Inhomogeneous Empty Space Function | |

linearKinhom | Inhomogeneous Linear K Function | |

intensity.ppp | Empirical Intensity of Point Pattern | |

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

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

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

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

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

npfun | Dummy Function Returns Number of Points | |

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

plot.leverage.ppm | Plot Leverage Function | |

dilation | Morphological Dilation | |

pairdist.ppp | Pairwise distances | |

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

AreaInter | The Area Interaction Point Process Model | |

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

pointsOnLines | Place Points Evenly Along Specified Lines | |

quadrats | Divide Region into Quadrats | |

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

betacells | Beta Ganglion Cells in Cat Retina | |

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

rNeymanScott | Simulate Neyman-Scott Process | |

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

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

Jmulti | Marked J Function | |

pool.quadrattest | Pool Several Quadrat Tests | |

smooth.fv | Apply Smoothing to Function Values | |

hamster | Aherne's hamster tumour data | |

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

spatstat-internal | Internal spatstat functions | |

will.expand | Test Expansion Rule | |

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

logLik.slrm | Loglikelihood of Spatial Logistic Regression | |

lut | Lookup Tables | |

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

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

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

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

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

Fiksel | The Fiksel Interaction | |

Jinhom | Inhomogeneous J-function | |

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

areaGain | Difference of Disc Areas | |

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

Ldot.inhom | Inhomogeneous Multitype L Dot Function | |

clickpoly | Interactively Define a Polygon | |

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

affine.owin | Apply Affine Transformation To Window | |

addvar | Added Variable Plot for Point Process Model | |

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

dfbetas.ppm | Parameter influence measure | |

delaunay.distance | Distance on Delaunay Triangulation | |

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

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

heather | Diggle's Heather Data | |

gridcentres | Rectangular grid of points | |

fv | Create a Function Value Table | |

eem | Exponential Energy Marks | |

simplenet | Simple Example of Linear Network | |

pairdist.default | Pairwise distances | |

ppm | Fit Point Process Model to Data | |

project2segment | Move Point To Nearest Line | |

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

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

rescue.rectangle | Convert Window Back To Rectangle | |

runifpoint | Generate N Uniform Random Points | |

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

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

spatstat.options | Internal Options in Spatstat Package | |

superimpose | Superimpose Several Geometric Patterns | |

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

Saturated | Saturated Pairwise Interaction model | |

Iest | Estimate the I-function | |

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

Geyer | Geyer's Saturation Point Process Model | |

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

bind.fv | Combine Function Value Tables | |

Concom | The Connected Component Process Model | |

Gfox | Foxall's Distance Functions | |

Linhom | L-function | |

flipxy | Exchange X and Y Coordinates | |

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

intensity | Intensity of a Dataset or a Model | |

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

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

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

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

methods.linnet | Methods for Linear Networks | |

pcf | Pair Correlation Function | |

whist | Weighted Histogram | |

progressreport | Print Progress Reports | |

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

rescale | Convert dataset to another unit of length | |

rotate.owin | Rotate a Window | |

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

tiles | Extract List of Tiles in a Tessellation | |

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

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

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

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

deltametric | Delta Metric | |

envelope | Simulation Envelopes of Summary Function | |

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

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

funxy | Spatial Function Class | |

contour.im | Contour plot of pixel image | |

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

rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |

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

MultiStrauss | The Multitype Strauss Point Process Model | |

Kmeasure | Reduced Second Moment Measure | |

circumradius | Circumradius and Diameter of a Linear Network | |

distmap.ppp | Distance Map of Point Pattern | |

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

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

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

im.object | Class of Images | |

disc | Circular Window | |

as.hyperframe | Convert Data to Hyperframe | |

summary.im | Summarizing a Pixel Image | |

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

No Results! |

## Last month downloads

## Details

Date | 2013-05-27 |

License | GPL (>= 2) |

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

LazyData | true |

LazyLoad | true |

ByteCompile | true |

Packaged | 2013-05-27 04:08:21 UTC; adrian |

NeedsCompilation | yes |

Repository | CRAN |

Date/Publication | 2013-05-27 07:54:27 |

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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