# spatstat v1.33-0

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

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

## Functions in spatstat

Name | Description | |

Kmodel | K function of a model | |

Iest | Estimate the I-function | |

Fest | Estimate the empty space function F | |

AreaInter | The Area Interaction Point Process Model | |

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

Jmulti | Marked J Function | |

connected | Connected components | |

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

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

Finhom | Inhomogeneous Empty Space Function | |

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

bdist.points | Distance to Boundary of Window | |

cells | Biological Cells Point Pattern | |

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

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

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

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

betacells | Beta Ganglion Cells in Cat Retina | |

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

Linhom | L-function | |

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

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

as.ppp | Convert Data To Class ppp | |

clickjoin | Interactively join vertices on a plot | |

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

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

colourmap | Colour Lookup Tables | |

edges2triangles | List Triangles in a Graph | |

intersect.tess | Intersection of Two Tessellations | |

deriv.fv | Calculate Derivative of Function Values | |

clmfires | Castilla-La Mancha Forest Fires | |

gridcentres | Rectangular grid of points | |

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

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

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

areaLoss | Difference of Disc Areas | |

dirichlet | Dirichlet Tessellation of Point Pattern | |

compareFit | Residual Diagnostics for Multiple Fitted Models | |

distmap | Distance Map | |

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

fasp.object | Function Arrays for Spatial Patterns | |

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

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

letterR | Window in Shape of Letter R | |

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

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

Fiksel | The Fiksel Interaction | |

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

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

Smooth | Spatial smoothing of data | |

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

as.rectangle | Window Frame | |

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

Tstat | Third order summary statistic | |

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

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

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

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

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

border | Border Region of a Window | |

colourtools | Convert and Compare Colours in Different Formats | |

blur | Apply Gaussian Blur to a Pixel Image | |

dilation | Morphological Dilation | |

plot.leverage.ppm | Plot Leverage Function | |

hyytiala | Scots pines and other trees at Hyytiala | |

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

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

harmonise.im | Make Pixel Images Compatible | |

Geyer | Geyer's Saturation Point Process Model | |

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

gridweights | Compute Quadrature Weights Based on Grid Counts | |

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

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

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

infline | Infinite Straight Lines | |

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

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

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

Kres | Residual K Function | |

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

Extract.fasp | Extract Subset of Function Array | |

plot.envelope | Plot a Simulation Envelope | |

diameter.owin | Diameter of a Window | |

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

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

bw.ppl | Likelihood Cross Validation Bandwidth Selection for Kernel Density | |

Kmulti.inhom | Inhomogeneous Marked K-Function | |

Gres | Residual G Function | |

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

demopat | Artificial Data Point Pattern | |

clickpoly | Interactively Define a Polygon | |

linearKinhom | Inhomogeneous Linear K Function | |

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

area.owin | Area of a Window | |

Lcross.inhom | Inhomogeneous Cross Type L Function | |

Kmeasure | Reduced Second Moment Measure | |

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

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

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

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

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

pppmatching | Create a Point Matching | |

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

areaGain | Difference of Disc Areas | |

flu | Influenza Virus Proteins | |

eval.fasp | Evaluate Expression Involving Function Arrays | |

Pairwise | Generic Pairwise Interaction model | |

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

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

localpcf | Local pair correlation function | |

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

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

compatible | Test Whether Objects Are Compatible | |

distmap.ppp | Distance Map of Point Pattern | |

BadGey | Hybrid Geyer Point Process Model | |

heather | Diggle's Heather Data | |

Kcross.inhom | Inhomogeneous Cross K Function | |

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

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

kppm | Fit Cluster or Cox Point Process Model | |

Emark | Diagnostics for random marking | |

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

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

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

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

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

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

pcfinhom | Inhomogeneous Pair Correlation Function | |

plot.influence.ppm | Plot Influence Measure | |

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

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

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

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

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

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

centroid.owin | Centroid of a window | |

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

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

edges2vees | List Dihedral Triples in a Graph | |

logLik.slrm | Loglikelihood of Spatial Logistic Regression | |

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

rjitter | Random Perturbation of a Point Pattern | |

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

lut | Lookup Tables | |

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

Ldot.inhom | Inhomogeneous Multitype L Dot Function | |

longleaf | Longleaf Pines Point Pattern | |

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

as.fv | Convert Data To Class fv | |

disc | Circular Window | |

Jest | Estimate the J-function | |

addvar | Added Variable Plot for Point Process Model | |

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

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

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

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

plot.colourmap | Plot a Colour Map | |

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

bdist.tiles | Distance to Boundary of Window | |

localKinhom | Inhomogeneous Neighbourhood Density Function | |

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

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

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

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

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

complement.owin | Take Complement of a Window | |

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

rPoissonCluster | Simulate Poisson Cluster Process | |

envelope | Simulation Envelopes of Summary Function | |

Poisson | Poisson Point Process Model | |

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

localK | Neighbourhood density function | |

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

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

summary.quad | Summarizing a Quadrature Scheme | |

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

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

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

fv.object | Function Value Table | |

delaunay.distance | Distance on Delaunay Triangulation | |

clarkevans | Clark and Evans Aggregation Index | |

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

is.marked | Test Whether Marks Are Present | |

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

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

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

parres | Partial Residuals for Point Process Model | |

methods.layered | Methods for Layered Objects | |

spatstat-internal | Internal spatstat functions | |

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

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

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

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

crossdist | Pairwise distances | |

envelope.envelope | Recompute Envelopes | |

chicago | Chicago Street Crime Data | |

rHardcore | Perfect Simulation of the Hardcore Process | |

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

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

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

as.interact | Extract Interaction Structure | |

Saturated | Saturated Pairwise Interaction model | |

pairs.im | Scatterplot Matrix for Pixel Images | |

rMaternI | Simulate Matern Model I | |

tess | Create a Tessellation | |

midpoints.psp | Midpoints of Line Segment Pattern | |

nnfun | Nearest Neighbour Map as a Function | |

shift.owin | Apply Vector Translation To Window | |

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

lurking | Lurking variable plot | |

Concom | The Connected Component Process Model | |

superimpose | Superimpose Several Geometric Patterns | |

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

dfbetas.ppm | Parameter influence measure | |

pixellate.owin | Convert Window to Pixel Image | |

gorillas | Gorilla Nesting Sites | |

hybrid.family | Hybrid Interaction Family | |

quantile.im | Sample Quantiles of Pixel Image | |

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

nearestsegment | Find Line Segment Nearest to Each Point | |

hamster | Aherne's hamster tumour data | |

plot.fasp | Plot a Function Array | |

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

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

edge.Trans | Translation Edge Correction | |

plot.im | Plot a Pixel Image | |

Kest.fft | K-function using FFT | |

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

as.psp | Convert Data To Class psp | |

convolve.im | Convolution of Pixel Images | |

convexhull.xy | Convex Hull of Points | |

as.ppm | Extract Fitted Point Process Model | |

pointsOnLines | Place Points Evenly Along Specified Lines | |

inforder.family | Infinite Order Interaction Family | |

volume | Volume of an Object | |

spatstat.options | Internal Options in Spatstat Package | |

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

Triplets | The Triplet Point Process Model | |

eem | Exponential Energy Marks | |

plot.owin | Plot a Spatial Window | |

suffstat | Sufficient Statistic of Point Process Model | |

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

npoints | Number of Points in a Point Pattern | |

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

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

rsyst | Simulate systematic random point pattern | |

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

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

concatxy | Concatenate x,y Coordinate Vectors | |

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

urkiola | Urkiola Woods Point Pattern | |

discpartarea | Area of Part of Disc | |

chorley | Chorley-Ribble Cancer Data | |

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

Extract.owin | Extract Subset of Window | |

rotate.im | Rotate a Pixel Image | |

pairdist.ppx | Pairwise Distances in Any Dimensions | |

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

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

rpoispp | Generate Poisson Point Pattern | |

Strauss | The Strauss Point Process Model | |

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

plot.ppp | plot a Spatial Point Pattern | |

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

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

expand.owin | Apply Expansion Rule | |

plot.bermantest | Plot Result of Berman Test | |

sharpen | Data Sharpening of Point Pattern | |

plot.linnet | Plot a linear network | |

ppp.object | Class of Point Patterns | |

rhohat | Smoothing Estimate of Covariate Transformation | |

rgbim | Create Colour-Valued Pixel Image | |

rNeymanScott | Simulate Neyman-Scott Process | |

bei | Tropical rain forest trees | |

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

affine | Apply Affine Transformation | |

diameter | Diameter of an Object | |

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

markcorr | Mark Correlation Function | |

rescale | Convert dataset to another unit of length | |

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

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

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

ewcdf | Weighted Empirical Cumulative Distribution Function | |

zapsmall.im | Rounding of Pixel Values | |

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

MultiHard | The Multitype Hard Core Point Process Model | |

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

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

timed | Record the Computation Time | |

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

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

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

fv | Create a Function Value Table | |

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

trim.rectangle | Cut margins from rectangle | |

plot.fv | Plot Function Values | |

model.images | Compute Images of Constructed Covariates | |

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

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

methods.fii | Methods for Fitted Interactions | |

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

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

Ginhom | Inhomogeneous Nearest Neighbour Function | |

Kest | K-function | |

scan.test | Spatial Scan Test | |

scaletointerval | Rescale Data to Lie Between Specified Limits | |

circumradius | Circumradius and Diameter of a Linear Network | |

persp.im | Perspective Plot of Pixel Image | |

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

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

rLGCP | Simulate Log-Gaussian Cox Process | |

scanpp | Read Point Pattern From Data File | |

closing | Morphological Closing | |

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

OrdThresh | Ord's Interaction model | |

intensity | Intensity of a Dataset or a Model | |

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

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

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

methods.linnet | Methods for Linear Networks | |

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

intensity.ppp | Empirical Intensity of Point Pattern | |

nnwhich.pp3 | Nearest neighbours in three dimensions | |

lansing | Lansing Woods Point Pattern | |

runiflpp | Uniform Random Points on a Linear Network | |

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

dilated.areas | Areas of Morphological Dilations | |

MultiStrauss | The Multitype Strauss Point Process Model | |

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

miplot | Morishita Index Plot | |

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

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

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

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

gpc2owin | Convert Polygonal Region into Different Format | |

corners | Corners of a rectangle | |

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

rpoint | Generate N Random Points | |

linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |

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

nbfires | Point Patterns of New Brunswick Forest Fires | |

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

rpoislinetess | Poisson Line Tessellation | |

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

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

linearpcf | Linear Pair Correlation Function | |

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

clarkevans.test | Clark and Evans Test | |

Extract.quad | Subset of Quadrature Scheme | |

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

print.quad | Print a Quadrature Scheme | |

rat | Ratio object | |

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

rshift | Random Shift | |

as.tess | Convert Data To Tessellation | |

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

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

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

nnwhich.ppx | Nearest Neighbours in Any Dimensions | |

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

rmpoispp | Generate Multitype Poisson Point Pattern | |

ponderosa | Ponderosa Pine Tree Point Pattern | |

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

npfun | Dummy Function Returns Number of Points | |

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

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

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

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

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

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

transect.im | Pixel Values Along a Transect | |

opening | Morphological Opening | |

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

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

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

vertices | Vertices of a Window | |

bronzefilter | Bronze gradient filter data | |

append.psp | Combine Two Line Segment Patterns | |

distcdf | Distribution Function of Interpoint Distance | |

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

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

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

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

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

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

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

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

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

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

mucosa | Cells in Gastric Mucosa | |

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

spruces | Spruces Point Pattern | |

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

Jinhom | Inhomogeneous J-function | |

delaunay | Delaunay Triangulation of Point Pattern | |

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

bdist.pixels | Distance to Boundary of Window | |

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

eroded.areas | Areas of Morphological Erosions | |

finpines | Pine saplings in Finland. | |

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

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

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

owin | Create a Window | |

mincontrast | Method of Minimum Contrast | |

ppm | Fit Point Process Model to Data | |

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

setcov | Set Covariance of a Window | |

matchingdist | Distance for a Point Pattern Matching | |

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

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

spatstat-deprecated | Deprecated spatstat functions | |

psp.object | Class of Line Segment Patterns | |

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

nztrees | New Zealand Trees Point Pattern | |

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

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

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

edge.Ripley | Ripley's Isotropic Edge Correction | |

pixelquad | Quadrature Scheme Based on Pixel Grid | |

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

unitname | Name for Unit of Length | |

lpp | Create Point Pattern on Linear Network | |

Extract.fv | Extract Subset of Function Values | |

paracou | Kimboto trees at Paracou, French Guiana | |

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

as.hyperframe | Convert Data to Hyperframe | |

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

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

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

rpoislpp | Poisson Point Process on a Linear Network | |

rmpoint | Generate N Random Multitype Points | |

Hybrid | Hybrid Interaction Point Process Model | |

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

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

sumouter | Compute Quadratic Forms | |

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

funxy | Spatial Function Class | |

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

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

pcf | Pair Correlation Function | |

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

periodify | Make Periodic Copies of a Spatial Pattern | |

markconnect | Mark Connection Function | |

ppx | Multidimensional Space-Time Point Pattern | |

nnwhich | Nearest neighbour | |

nncross | Nearest Neighbours Between Two Patterns | |

is.rectangle | Determine Type of Window | |

rMaternII | Simulate Matern Model II | |

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

Lest | L-function | |

distfun | Distance Map as a Function | |

pool | Pool Data | |

pppdist | Distance Between Two Point Patterns | |

runifpoint | Generate N Uniform Random Points | |

waka | Trees in Waka national park | |

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

layered | Create List of Plotting Layers | |

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

ord.family | Ord Interaction Process Family | |

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

imcov | Spatial Covariance of a Pixel Image | |

deltametric | Delta Metric | |

incircle | Find Largest Circle Inside Window | |

bind.fv | Combine Function Value Tables | |

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

simdat | Simulated Point Pattern | |

shift | Apply Vector Translation | |

simplenet | Simple Example of Linear Network | |

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

nndist | Nearest neighbour distances | |

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

rlabel | Random Re-Labelling of Point Pattern | |

im.object | Class of Images | |

contour.im | Contour plot of pixel image | |

progressreport | Print Progress Reports | |

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

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

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

lengths.psp | Lengths of Line Segments | |

lohboot | Bootstrap Confidence Bands for Summary Function | |

integral.im | Integral of a Pixel Image | |

Gest | Nearest Neighbour Distance Function G | |

quadratcount | Quadrat counting for a point pattern | |

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

eval.im | Evaluate Expression Involving Pixel Images | |

rThomas | Simulate Thomas Process | |

psp | Create a Line Segment Pattern | |

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

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

nnclean | Nearest Neighbour Clutter Removal | |

gordon | People in Gordon Square | |

beginner | Print Introduction For Beginners | |

box3 | Three-Dimensional Box | |

unmark | Remove Marks | |

summary.owin | Summary of a Spatial Window | |

is.multitype | Test whether Object is Multitype | |

varblock | Estimate Variance of Summary Statistic by Subdivision | |

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

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

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

linearK | Linear K Function | |

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

rMatClust | Simulate Matern Cluster Process | |

rGaussPoisson | Simulate Gauss-Poisson Process | |

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

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

LennardJones | The Lennard-Jones Potential | |

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

plot.layered | Layered Plot | |

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

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

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

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

ripras | Estimate window from points alone | |

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

pool.envelope | Pool Data from Several Envelopes | |

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

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

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

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

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

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

rSSI | Simulate Simple Sequential Inhibition | |

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

rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |

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

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

Softcore | The Soft Core Point Process Model | |

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

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

quadrats | Divide Region into Quadrats | |

bramblecanes | Hutchings' Bramble Canes data | |

rotate.psp | Rotate a Line Segment Pattern | |

distmap.owin | Distance Map of Window | |

pairwise.family | Pairwise Interaction Process Family | |

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

rpoisline | Generate Poisson Random Line Process | |

rescue.rectangle | Convert Window Back To Rectangle | |

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

Gfox | Foxall's Distance Functions | |

marks | Marks of a Point Pattern | |

levelset | Level Set of a Pixel Image | |

pairdist.ppp | Pairwise distances | |

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

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

tiles | Extract List of Tiles in a Tessellation | |

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

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

owin.object | Class owin | |

angles.psp | Orientation Angles of Line Segments | |

reflect | Reflect In Origin | |

plot.quad | plot a Spatial Quadrature Scheme | |

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

pairdist.default | Pairwise distances | |

linnet | Create a Linear Network | |

unnormdensity | Weighted kernel smoother | |

markcorrint | Mark Correlation Integral | |

Gcom | Model Compensator of Nearest Neighbour Function | |

profilepl | Profile Maximum Pseudolikelihood | |

swedishpines | Swedish Pines Point Pattern | |

methods.units | Methods for Units | |

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

fryplot | Fry Plot of Point Pattern | |

convexhull | Convex Hull | |

rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |

rknn | Theoretical Distribution of Nearest Neighbour Distance | |

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

msr | Signed or Vector-Valued Measure | |

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

rcell | Simulate Baddeley-Silverman Cell Process | |

pairdist.pp3 | Pairwise distances in Three Dimensions | |

copper | Berman-Huntington points and lines data | |

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

Kinhom | Inhomogeneous K-function | |

as.im | Convert to Pixel Image | |

rmhexpand | Specify Simulation Window or Expansion Rule | |

rStrauss | Perfect Simulation of the Strauss Process | |

boxx | Multi-Dimensional Box | |

clusterset | Allard-Fraley Estimator of Cluster Feature | |

amacrine | Hughes' Amacrine Cell Data | |

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

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

ppp | Create a Point Pattern | |

endpoints.psp | Endpoints of Line Segment Pattern | |

im | Create a Pixel Image Object | |

rthin | Random Thinning | |

spokes | Spokes pattern of dummy points | |

LambertW | Lambert's W Function | |

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

ants | Harkness-Isham ants' nests data | |

slrm | Spatial Logistic Regression | |

rotate | Rotate | |

Hest | Spherical Contact Distribution Function | |

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

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

markvario | Mark Variogram | |

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

as.owin | Convert Data To Class owin | |

rstrat | Simulate Stratified Random Point Pattern | |

contour.listof | Plot a List of Things | |

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

pp3 | Three Dimensional Point Pattern | |

shapley | Galaxies in the Shapley Supercluster | |

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

DiggleGratton | Diggle-Gratton model | |

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

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

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

pairdist.psp | Pairwise distances between line segments | |

rotate.owin | Rotate a Window | |

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

anemones | Beadlet Anemones Data | |

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

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

perimeter | Perimeter Length of Window | |

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

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

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

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

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

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

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

Extract.im | Extract Subset of Image | |

triplet.family | Triplet Interaction Family | |

Extract.linnet | Extract Subset of Linear Network | |

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

stieltjes | Compute Integral of Function Against Cumulative Distribution | |

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

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

flipxy | Exchange X and Y Coordinates | |

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

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

clickppp | Interactively Add Points | |

plot.hyperframe | Plot Entries in a Hyperframe | |

whist | Weighted Histogram | |

pool.quadrattest | Pool Several Quadrat Tests | |

rounding | Detect Numerical Rounding | |

japanesepines | Japanese Pines Point Pattern | |

pairdist | Pairwise distances | |

Hardcore | The Hard Core Point Process Model | |

stratrand | Stratified random point pattern | |

Kmulti | Marked K-Function | |

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

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

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

plot.tess | Plot a tessellation | |

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

rMosaicField | Mosaic Random Field | |

summary.im | Summarizing a Pixel Image | |

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

hyperframe | Hyper Data Frame | |

harmonic | Basis for Harmonic Functions | |

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

quad.object | Class of Quadrature Schemes | |

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

Ord | Generic Ord Interaction model | |

plot.listof | Plot a List of Things | |

interp.colourmap | Interpolate smoothly between specified colours | |

eval.fv | Evaluate Expression Involving Functions | |

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

nnmark | Mark of Nearest Neighbour | |

smooth.fv | Apply Smoothing to Function Values | |

interp.im | Interpolate a Pixel Image | |

square | Square Window | |

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

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

rotate.ppp | Rotate a Point Pattern | |

overlap.owin | Compute Area of Overlap | |

rMosaicSet | Mosaic Random Set | |

Kscaled | Locally Scaled K-function | |

murchison | Murchison gold deposits | |

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

linim | Create Pixel Image on Linear Network | |

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

pppmatching.object | Class of Point Matchings | |

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

methods.funxy | Methods for Spatial Functions | |

will.expand | Test Expansion Rule | |

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

pixellate | Convert Spatial Object to Pixel Image | |

affine.owin | Apply Affine Transformation To Window | |

Gmulti | Marked Nearest Neighbour Distance Function | |

project2segment | Move Point To Nearest Line | |

Kcom | Model Compensator of K Function | |

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

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

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

reach | Interaction Distance of a Point Process | |

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

scalardilate | Apply Scalar Dilation | |

spatstat-package | The Spatstat Package | |

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

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

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

rshift.ppp | Randomly Shift a Point Pattern | |

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

erosion | Morphological Erosion | |

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

nnmap | K-th Nearest Point Map | |

No Results! |

## Last month downloads

## Details

Date | 2013-09-05 |

License | GPL (>= 2) |

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

LazyData | true |

LazyLoad | true |

ByteCompile | true |

Packaged | 2013-09-05 07:48:07 UTC; adrian |

NeedsCompilation | yes |

Repository | CRAN |

Date/Publication | 2013-09-05 11:40:52 |

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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