# spatstat v1.31-1.1

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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 | |

Kscaled | Locally Scaled K-function | |

MultiStrauss | The Multitype Strauss Point Process Model | |

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

Strauss | The Strauss Point Process Model | |

as.psp | Convert Data To Class psp | |

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

as.ppp | Convert Data To Class ppp | |

as.tess | Convert Data To Tessellation | |

Gres | Residual G Function | |

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

as.rectangle | Window Frame | |

contour.im | Contour plot of pixel image | |

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

distmap.ppp | Distance Map of Point Pattern | |

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

im | Create a Pixel Image Object | |

as.interact | Extract Interaction Structure | |

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

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

convexhull.xy | Convex Hull of Points | |

clarkevans.test | Clark and Evans Test | |

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

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

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

funxy | Spatial Function Class | |

hyperframe | Hyper Data Frame | |

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

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

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

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

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

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

ord.family | Ord Interaction Process Family | |

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

plot.listof | Plot a List of Things | |

murchison | Murchison gold deposits | |

Fest | Estimate the empty space function F | |

parres | Partial Residuals for Point Process Model | |

periodify | Make Periodic Copies of a Spatial Pattern | |

Jinhom | Inhomogeneous J-function | |

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

rThomas | Simulate Thomas Process | |

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

psp.object | Class of Line Segment Patterns | |

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

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

rMaternI | Simulate Matern Model I | |

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

rounding | Detect Numerical Rounding | |

distcdf | Distribution Function of Interpoint Distance | |

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

rsyst | Simulate systematic random point pattern | |

heather | Diggle's Heather Data | |

paracou | Kimboto trees at Paracou, French Guiana | |

nnwhich.pp3 | Nearest neighbours in three dimensions | |

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

rstrat | Simulate Stratified Random Point Pattern | |

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

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

square | Square Window | |

plot.tess | Plot a tessellation | |

ripras | Estimate window from points alone | |

rlabel | Random Re-Labelling of Point Pattern | |

Extract.im | Extract Subset of Image | |

Kmeasure | Reduced Second Moment Measure | |

Extract.quad | Subset of Quadrature Scheme | |

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

anemones | Beadlet Anemones Data | |

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

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

dilated.areas | Areas of Morphological Dilations | |

discpartarea | Area of Part of Disc | |

progressreport | Print Progress Reports | |

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

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

centroid.owin | Centroid of a window | |

methods.linnet | Methods for Linear Networks | |

nnwhich | Nearest neighbour | |

diameter.owin | Diameter of a Window | |

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

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

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

pairdist.psp | Pairwise distances between line segments | |

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

quad.object | Class of Quadrature Schemes | |

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

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

distmap | Distance Map | |

tiles | Extract List of Tiles in a Tessellation | |

quadratcount | Quadrat counting for a point pattern | |

eval.im | Evaluate Expression Involving Pixel Images | |

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

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

corners | Corners of a rectangle | |

opening | Morphological Opening | |

pixellate | Convert Spatial Object to Pixel Image | |

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

rLGCP | Simulate Log-Gaussian Cox Process | |

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

Extract.owin | Extract Subset of Window | |

rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |

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

pairs.im | Scatterplot Matrix for Pixel Images | |

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

simplenet | Simple Example of Linear Network | |

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

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

rMosaicSet | Mosaic Random Set | |

pp3 | Three Dimensional Point Pattern | |

Saturated | Saturated Pairwise Interaction model | |

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

psp | Create a Line Segment Pattern | |

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

AreaInter | The Area Interaction Point Process Model | |

spatstat-deprecated | Deprecated spatstat functions | |

circumradius | Circumradius and Diameter of a Linear Network | |

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

Gmulti | Marked Nearest Neighbour Distance Function | |

Kest | K-function | |

Gfox | Foxall's Distance Functions | |

rgbim | Create Colour-Valued Pixel Image | |

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

Linhom | L-function | |

closing | Morphological Closing | |

Finhom | Inhomogeneous Empty Space Function | |

Lest | L-function | |

shift.owin | Apply Vector Translation To Window | |

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

Pairwise | Generic Pairwise Interaction model | |

bronzefilter | Bronze gradient filter data | |

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

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

box3 | Three-Dimensional Box | |

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

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

compatible | Test Whether Objects Are Compatible | |

rhohat | Smoothing Estimate of Covariate Transformation | |

plot.fasp | Plot a Function Array | |

scaletointerval | Rescale Data to Lie Between Specified Limits | |

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

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

marks | Marks of a Point Pattern | |

Kest.fft | K-function using FFT | |

Ginhom | Inhomogeneous Nearest Neighbour Function | |

Softcore | The Soft Core Point Process Model | |

Kmulti | Marked K-Function | |

Tstat | Third order summary statistic | |

nztrees | New Zealand Trees Point Pattern | |

clickpoly | Interactively Define a Polygon | |

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

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

chorley | Chorley-Ribble Cancer Data | |

colourmap | Colour Lookup Tables | |

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

compareFit | Residual Diagnostics for Multiple Fitted Models | |

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

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

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

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

LambertW | Lambert's W Function | |

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

diameter | Diameter of an Object | |

fv.object | Function Value Table | |

ewcdf | Weighted Empirical Cumulative Distribution Function | |

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

MultiHard | The Multitype Hard Core Point Process Model | |

methods.units | Methods for Units | |

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

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

rotate.ppp | Rotate a Point Pattern | |

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

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

waka | Trees in Waka national park | |

affine.owin | Apply Affine Transformation To Window | |

shift | Apply Vector Translation | |

flu | Influenza Virus Proteins | |

as.owin | Convert Data To Class owin | |

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

owin | Create a Window | |

plot.colourmap | Plot a Colour Map | |

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

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

rGaussPoisson | Simulate Gauss-Poisson Process | |

plot.fv | Plot Function Values | |

rshift.ppp | Randomly Shift a Point Pattern | |

plot.linnet | Plot a linear network | |

Kmodel | K function of a model | |

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

mucosa | Cells in Gastric Mucosa | |

shapley | Galaxies in the Shapley Supercluster | |

unmark | Remove Marks | |

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

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

rjitter | Random Perturbation of a Point Pattern | |

nnfun | Nearest Neighbour Map as a Function | |

nearestsegment | Find Line Segment Nearest to Each Point | |

summary.owin | Summary of a Spatial Window | |

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

clusterset | Allard-Fraley Estimator of Cluster Feature | |

rat | Ratio object | |

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

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

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

plot.influence.ppm | Plot Influence Measure | |

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

rshift | Random Shift | |

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

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

markcorr | Mark Correlation Function | |

rmpoispp | Generate Multitype Poisson Point Pattern | |

rHardcore | Perfect Simulation of the Hardcore Process | |

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

summary.im | Summarizing a Pixel Image | |

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

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

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

pcf | Pair Correlation Function | |

smooth.fv | Apply Smoothing to Function Values | |

rMatClust | Simulate Matern Cluster Process | |

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

Emark | Diagnostics for random marking | |

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

quantile.im | Sample Quantiles of Pixel Image | |

pairdist.pp3 | Pairwise distances in Three Dimensions | |

rNeymanScott | Simulate Neyman-Scott Process | |

rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |

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

Gcom | Model Compensator of Nearest Neighbour Function | |

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

scan.test | Spatial Scan Test | |

append.psp | Combine Two Line Segment Patterns | |

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

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

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

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

unnormdensity | Weighted kernel smoother | |

Extract.fasp | Extract Subset of Function Array | |

blur | Apply Gaussian Blur to a Pixel Image | |

Geyer | Geyer's Saturation Point Process Model | |

Kcom | Model Compensator of K Function | |

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

vertices | Vertices of a Window | |

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

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

Kcross.inhom | Inhomogeneous Cross K Function | |

bramblecanes | Hutchings' Bramble Canes data | |

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

whist | Weighted Histogram | |

superimpose | Superimpose Several Geometric Patterns | |

markcorrint | Mark Correlation Integral | |

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

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

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

reach | Interaction Distance of a Point Process | |

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

as.hyperframe | Convert Data to Hyperframe | |

pointsOnLines | Place Points Evenly Along Specified Lines | |

rMosaicField | Mosaic Random Field | |

border | Border Region of a Window | |

setcov | Set Covariance of a Window | |

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

rcell | Simulate Baddeley-Silverman Cell Process | |

japanesepines | Japanese Pines Point Pattern | |

model.images | Compute Images of Constructed Covariates | |

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

complement.owin | Take Complement of a Window | |

rotate.im | Rotate a Pixel Image | |

nbfires | Point Patterns of New Brunswick Forest Fires | |

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

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

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

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

transect.im | Pixel Values Along a Transect | |

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

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

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

spokes | Spokes pattern of dummy points | |

bdist.tiles | Distance to Boundary of Window | |

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

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

rescue.rectangle | Convert Window Back To Rectangle | |

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

spatstat-package | The Spatstat Package | |

gridweights | Compute Quadrature Weights Based on Grid Counts | |

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

chicago | Chicago Street Crime Data | |

flipxy | Exchange X and Y Coordinates | |

dfbetas.ppm | Parameter influence measure | |

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

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

linearpcf | Linear Pair Correlation Function | |

dirichlet | Dirichlet Tessellation of Point Pattern | |

triplet.family | Triplet Interaction Family | |

runiflpp | Uniform Random Points on a Linear Network | |

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

linearK | Linear K Function | |

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

envelope.envelope | Recompute Envelopes | |

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

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

hyytiala | Scots pines and other trees at Hyytiala | |

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

volume | Volume of an Object | |

rpoint | Generate N Random Points | |

localK | Neighbourhood density function | |

harmonise.im | Make Pixel Images Compatible | |

rotate | Rotate | |

is.marked | Test Whether Marks Are Present | |

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

contour.listof | Plot a List of Things | |

mincontrast | Method of Minimum Contrast | |

markvario | Mark Variogram | |

runifpoint | Generate N Uniform Random Points | |

will.expand | Test Expansion Rule | |

connected | Connected components | |

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

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

rpoislinetess | Poisson Line Tessellation | |

areaLoss | Difference of Disc Areas | |

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

delaunay.distance | Distance on Delaunay Triangulation | |

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

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

deltametric | Delta Metric | |

urkiola | Urkiola Woods Point Pattern | |

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

clickjoin | Interactively join vertices on a plot | |

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

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

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

pairdist.ppp | Pairwise distances | |

edges2triangles | List Triangles in a Graph | |

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

nnclean | Nearest Neighbour Clutter Removal | |

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

methods.layered | Methods for Layered Objects | |

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

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

miplot | Morishita Index Plot | |

nnwhich.ppx | Nearest Neighbours in Any Dimensions | |

plot.im | Plot a Pixel Image | |

pixelquad | Quadrature Scheme Based on Pixel Grid | |

owin.object | Class owin | |

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

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

pppmatching.object | Class of Point Matchings | |

zapsmall.im | Rounding of Pixel Values | |

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

scalardilate | Apply Scalar Dilation | |

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

simdat | Simulated Point Pattern | |

rMaternII | Simulate Matern Model II | |

pppmatching | Create a Point Matching | |

rStrauss | Perfect Simulation of the Strauss Process | |

Concom | The Connected Component Process Model | |

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

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

distmap.owin | Distance Map of Window | |

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

Fiksel | The Fiksel Interaction | |

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

Hybrid | Hybrid Interaction Point Process Model | |

rescale | Convert dataset to another unit of length | |

lengths.psp | Lengths of Line Segments | |

Triplets | The Triplet Point Process Model | |

rpoispp | Generate Poisson Point Pattern | |

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

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

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

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

rthin | Random Thinning | |

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

cells | Biological Cells Point Pattern | |

convexhull | Convex Hull | |

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

boxx | Multi-Dimensional Box | |

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

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

distfun | Distance Map as a Function | |

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

interp.im | Interpolate a Pixel Image | |

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

gridcentres | Rectangular grid of points | |

varblock | Estimate Variance of Summary Statistic by Subdivision | |

clmfires | Castilla-La Mancha Forest Fires | |

endpoints.psp | Endpoints of Line Segment Pattern | |

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

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

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

incircle | Find Largest Circle Inside Window | |

fryplot | Fry Plot of Point Pattern | |

intensity.ppp | Empirical Intensity of Point Pattern | |

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

bdist.points | Distance to Boundary of Window | |

inforder.family | Infinite Order Interaction Family | |

pixellate.owin | Convert Window to Pixel Image | |

perimeter | Perimeter Length of Window | |

lansing | Lansing Woods Point Pattern | |

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

rpoisline | Generate Poisson Random Line Process | |

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

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

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

pairdist | Pairwise distances | |

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

layered | Create List of Plotting Layers | |

linim | Create Pixel Image on Linear Network | |

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

ppm | Fit Point Process Model to Data | |

ppp.object | Class of Point Patterns | |

levelset | Level Set of a Pixel Image | |

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

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

pairdist.ppx | Pairwise Distances in Any Dimensions | |

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

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

longleaf | Longleaf Pines Point Pattern | |

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

Kinhom | Inhomogeneous K-function | |

crossdist | Pairwise distances | |

quadrats | Divide Region into Quadrats | |

plot.owin | Plot a Spatial Window | |

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

summary.quad | Summarizing a Quadrature Scheme | |

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

letterR | Window in Shape of Letter R | |

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

intersect.tess | Intersection of Two Tessellations | |

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

BadGey | Hybrid Geyer Point Process Model | |

sumouter | Compute Quadratic Forms | |

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

Ldot.inhom | Inhomogeneous Multitype L Dot Function | |

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

fasp.object | Function Arrays for Spatial Patterns | |

OrdThresh | Ord's Interaction model | |

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

amacrine | Hughes' Amacrine Cell Data | |

bei | Tropical rain forest trees | |

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

tess | Create a Tessellation | |

Ord | Generic Ord Interaction model | |

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

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

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

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

delaunay | Delaunay Triangulation of Point Pattern | |

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

eroded.areas | Areas of Morphological Erosions | |

gpc2owin | Convert Polygonal Region into Different Format | |

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

eval.fasp | Evaluate Expression Involving Function Arrays | |

msr | Signed or Vector-Valued Measure | |

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

reflect | Reflect In Origin | |

matchingdist | Distance for a Point Pattern Matching | |

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

plot.hyperframe | Plot Entries in a Hyperframe | |

midpoints.psp | Midpoints of Line Segment Pattern | |

rSSI | Simulate Simple Sequential Inhibition | |

persp.im | Perspective Plot of Pixel Image | |

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

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

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

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

pcfinhom | Inhomogeneous Pair Correlation Function | |

rmhexpand | Specify Simulation Window or Expansion Rule | |

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

area.owin | Area of a Window | |

scanpp | Read Point Pattern From Data File | |

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

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

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

gorillas | Gorilla Nesting Sites | |

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

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

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

rpoislpp | Poisson Point Process on a Linear Network | |

nncross | Nearest Neighbours Between Two Patterns | |

plot.layered | Layered Plot | |

expand.owin | Apply Expansion Rule | |

localKinhom | Inhomogeneous Neighbourhood Density Function | |

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

pool.envelope | Pool Data from Several Envelopes | |

infline | Infinite Straight Lines | |

Kmulti.inhom | Inhomogeneous Marked K-Function | |

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

trim.rectangle | Cut margins from rectangle | |

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

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

ponderosa | Ponderosa Pine Tree Point Pattern | |

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

slrm | Spatial Logistic Regression | |

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

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

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

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

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

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

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

concatxy | Concatenate x,y Coordinate Vectors | |

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

linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |

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

eval.fv | Evaluate Expression Involving Functions | |

gordon | People in Gordon Square | |

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

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

as.ppm | Extract Fitted Point Process Model | |

nndist | Nearest neighbour distances | |

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

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

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

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

kppm | Fit Cluster or Cox Point Process Model | |

intensity | Intensity of a Dataset or a Model | |

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

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

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

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

clarkevans | Clark and Evans Aggregation Index | |

ppp | Create a Point Pattern | |

sharpen | Data Sharpening of Point Pattern | |

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

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

disc | Circular Window | |

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

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

linnet | Create a Linear Network | |

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

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

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

lurking | Lurking variable plot | |

spatstat-internal | Internal spatstat functions | |

Hardcore | The Hard Core Point Process Model | |

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

Lcross.inhom | Inhomogeneous Cross Type L Function | |

Jmulti | Marked J Function | |

addvar | Added Variable Plot for Point Process Model | |

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

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

dilation | Morphological Dilation | |

integral.im | Integral of a Pixel Image | |

methods.funxy | Methods for Spatial Functions | |

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

is.multitype | Test whether Object is Multitype | |

as.im | Convert to Pixel Image | |

plot.leverage.ppm | Plot Leverage Function | |

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

pppdist | Distance Between Two Point Patterns | |

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

profilepl | Profile Maximum Pseudolikelihood | |

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

im.object | Class of Images | |

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

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

rknn | Theoretical Distribution of Nearest Neighbour Distance | |

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

plot.bermantest | Plot Result of Berman Test | |

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

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

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

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

Gest | Nearest Neighbour Distance Function G | |

Hest | Spherical Contact Distribution Function | |

Iest | Estimate the I-function | |

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

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

Kres | Residual K Function | |

envelope | Simulation Envelopes of Summary Function | |

angles.psp | Orientation Angles of Line Segments | |

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

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

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

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

finpines | Pine saplings in Finland. | |

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

plot.ppp | plot a Spatial Point Pattern | |

ppx | Multidimensional Space-Time Point Pattern | |

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

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

rPoissonCluster | Simulate Poisson Cluster Process | |

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

swedishpines | Swedish Pines Point Pattern | |

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

pairwise.family | Pairwise Interaction Process Family | |

rotate.owin | Rotate a Window | |

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

eem | Exponential Energy Marks | |

spruces | Spruces Point Pattern | |

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

linearKinhom | Inhomogeneous Linear K Function | |

stieltjes | Compute Integral of Function Against Cumulative Distribution | |

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

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

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

npfun | Dummy Function Returns Number of Points | |

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

localpcf | Local pair correlation function | |

markconnect | Mark Connection Function | |

logLik.slrm | Loglikelihood of Spatial Logistic Regression | |

Extract.fv | Extract Subset of Function Values | |

harmonic | Basis for Harmonic Functions | |

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

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

Jest | Estimate the J-function | |

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

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

bdist.pixels | Distance to Boundary of Window | |

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

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

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

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

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

copper | Berman-Huntington points and lines data | |

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

pairdist.default | Pairwise distances | |

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

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

project2segment | Move Point To Nearest Line | |

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

plot.envelope | Plot a Simulation Envelope | |

rmpoint | Generate N Random Multitype Points | |

pool | Pool Data | |

print.quad | Print a Quadrature Scheme | |

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

pool.quadrattest | Pool Several Quadrat Tests | |

unitname | Name for Unit of Length | |

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

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

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

Poisson | Poisson Point Process Model | |

fv | Create a Function Value Table | |

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

DiggleGratton | Diggle-Gratton model | |

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

betacells | Beta Ganglion Cells in Cat Retina | |

bind.fv | Combine Function Value Tables | |

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

demopat | Artificial Data Point Pattern | |

hamster | Aherne's hamster tumour data | |

hybrid.family | Hybrid Interaction Family | |

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

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

plot.quad | plot a Spatial Quadrature Scheme | |

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

npoints | Number of Points in a Point Pattern | |

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

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

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

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

rotate.psp | Rotate a Line Segment Pattern | |

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

spatstat.options | Internal Options in Spatstat Package | |

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

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

suffstat | Sufficient Statistic of Point Process Model | |

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

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

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

is.rectangle | Determine Type of Window | |

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

lohboot | Bootstrap Confidence Bands for Summary Function | |

ants | Harkness-Isham ants' nests data | |

areaGain | Difference of Disc Areas | |

erosion | Morphological Erosion | |

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

affine | Apply Affine Transformation | |

convolve.im | Convolution of Pixel Images | |

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

lut | Lookup Tables | |

lpp | Create Point Pattern on Linear Network | |

clickppp | Interactively Add Points | |

imcov | Spatial Covariance of a Pixel Image | |

colourtools | Convert and Compare Colours in Different Formats | |

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

LennardJones | The Lennard-Jones Potential | |

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

No Results! |

## Last month downloads

## Details

Date | 2013-03-01 |

License | GPL (>= 2) |

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

LazyData | true |

LazyLoad | true |

ByteCompile | true |

Packaged | 2013-04-25 16:54:41 UTC; ripley |

NeedsCompilation | yes |

Repository | CRAN |

Date/Publication | 2013-04-25 18:55:21 |

depends | base (>= 2.14.0) , deldir (>= 0.0-21) , graphics , grDevices , mgcv , R (>= 2.14.0) , stats , utils |

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

Contributors | Rolf Turner, Adrian Baddeley |

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