# spatstat v1.26-1

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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 | |

Geyer | Geyer's Saturation Point Process Model | |

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

ants | Harkness-Isham ants' nests data | |

spatstat-deprecated | Deprecated spatstat functions | |

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

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

Gmulti | Marked Nearest Neighbour Distance Function | |

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

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

discpartarea | Area of Part of Disc | |

Kmeasure | Reduced Second Moment Measure | |

contour.im | Contour plot of pixel image | |

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

gorillas | Gorilla Nesting Sites | |

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

Iest | Estimate the I-function | |

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

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

fryplot | Fry Plot of Point Pattern | |

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

expand.owin | Expand Window By Factor | |

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

OrdThresh | Ord's Interaction model | |

linnet | Create a Linear Network | |

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

amacrine | Hughes' Amacrine Cell Data | |

intersect.tess | Intersection of Two Tessellations | |

model.images | Compute Images of Constructed Covariates | |

Extract.fasp | Extract Subset of Function Array | |

pppmatching | Create a Point Matching | |

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

plot.listof | Plot a List of Things | |

anemones | Beadlet Anemones Data | |

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

Kcom | Model Compensator of K Function | |

as.tess | Convert Data To Tessellation | |

area.owin | Area of a Window | |

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

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

clickppp | Interactively Add Points | |

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

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

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

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

nnclean | Nearest Neighbour Clutter Removal | |

chicago | Chicago Street Crime Data | |

Gres | Residual G Function | |

imcov | Spatial Covariance of a Pixel Image | |

heather | Diggle's Heather Data | |

matchingdist | Distance for a Point Pattern Matching | |

incircle | Find Largest Circle Inside Window | |

ripras | Estimate window from points alone | |

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

Tstat | Third order summary statistic | |

Pairwise | Generic Pairwise Interaction model | |

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

pairdist.psp | Pairwise distances between line segments | |

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

demopat | Artificial Data Point Pattern | |

flu | Influenza Virus Proteins | |

MultiHard | The Multitype Hard Core Point Process Model | |

im.object | Class of Images | |

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

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

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

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

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

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

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

bind.fv | Combine Function Value Tables | |

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

msr | Signed or Vector-Valued Measure | |

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

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

methods.linnet | Methods for Linear Networks | |

mincontrast | Method of Minimum Contrast | |

is.marked | Test Whether Marks Are Present | |

nnwhich.ppx | Nearest Neighbours in Any Dimensions | |

blur | Apply Gaussian Blur to a Pixel Image | |

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

as.psp | Convert Data To Class psp | |

ppp.object | Class of Point Patterns | |

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

linearpcf | Linear Pair Correlation Function | |

pcfinhom | Inhomogeneous Pair Correlation Function | |

eval.fasp | Evaluate Expression Involving Function Arrays | |

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

as.im | Convert to Pixel Image | |

pool.envelope | Pool Data from Several Envelopes | |

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

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

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

kppm | Fit Cluster or Cox Point Process Model | |

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

LennardJones | The Lennard-Jones Potential | |

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

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

connected | Connected components of an image or window | |

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

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

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

nncross | Nearest Neighbours Between Two Patterns | |

rMosaicSet | Mosaic Random Set | |

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

finpines | Pine saplings in Finland. | |

plot.ppp | plot a Spatial Point Pattern | |

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

lpp | Create Point Pattern on Linear Network | |

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

pointsOnLines | Place Points Evenly Along Specified Lines | |

japanesepines | Japanese Pines Point Pattern | |

lengths.psp | Lengths of Line Segments | |

rgbim | Create Colour-Valued Pixel Image | |

pairdist.ppx | Pairwise Distances in Any Dimensions | |

pppmatching.object | Class of Point Matchings | |

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

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

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

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

quadrats | Divide Region into Quadrats | |

pairdist.default | Pairwise distances | |

rpoislinetess | Poisson Line Tessellation | |

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

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

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

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

murchison | Murchison gold deposits | |

closing | Morphological Closing | |

disc | Circular Window | |

lut | Lookup Tables | |

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

chorley | Chorley-Ribble Cancer Data | |

erosion | Morphological Erosion | |

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

box3 | Three-Dimensional Box | |

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

rotate.psp | Rotate a Line Segment Pattern | |

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

complement.owin | Take Complement of a Window | |

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

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

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

border | Border Region of a Window | |

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

rescue.rectangle | Convert Window Back To Rectangle | |

perimeter | Perimeter Length of Window | |

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

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

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

plot.layered | Layered Plot | |

opening | Morphological Opening | |

slrm | Spatial Logistic Regression | |

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

spatstat-package | The Spatstat Package | |

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

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

ewcdf | Weighted Empirical Cumulative Distribution Function | |

rPoissonCluster | Simulate Poisson Cluster Process | |

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

pairwise.family | Pairwise Interaction Process Family | |

rshift | Random Shift | |

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

affine | Apply Affine Transformation | |

lurking | Lurking variable plot | |

rmpoint | Generate N Random Multitype Points | |

convexhull | Convex Hull | |

spruces | Spruces Point Pattern | |

square | Square Window | |

nnwhich.pp3 | Nearest neighbours in three dimensions | |

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

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

rSSI | Simulate Simple Sequential Inhibition | |

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

rescale | Convert dataset to another unit of length | |

angles.psp | Orientation Angles of Line Segments | |

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

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

ponderosa | Ponderosa Pine Tree Point Pattern | |

as.rectangle | Window Frame | |

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

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

Linhom | L-function | |

rmpoispp | Generate Multitype Poisson Point Pattern | |

volume | Volume of an Object | |

boxx | Multi-Dimensional Box | |

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

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

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

Fiksel | The Fiksel Interaction | |

rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |

pixelquad | Quadrature Scheme Based on Pixel Grid | |

rthin | Random Thinning | |

Kscaled | Locally Scaled K-function | |

quadratcount | Quadrat counting for a point pattern | |

runifpoint | Generate N Uniform Random Points | |

tiles | Extract List of Tiles in a Tessellation | |

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

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

Triplets | The Triplet Point Process Model | |

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

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

dirichlet | Dirichlet Tessellation of Point Pattern | |

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

markcorrint | Mark Correlation Integral | |

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

Kcross.inhom | Inhomogeneous Cross K Function | |

pairdist.ppp | Pairwise distances | |

AreaInter | The Area Interaction Point Process Model | |

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

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

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

Lcross.inhom | Inhomogeneous Cross Type L Function | |

Strauss | The Strauss Point Process Model | |

betacells | Beta Ganglion Cells in Cat Retina | |

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

areaGain | Difference of Disc Areas | |

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

copper | Berman-Huntington points and lines data | |

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

gridcentres | Rectangular grid of points | |

BadGey | Hybrid Geyer Point Process Model | |

npfun | Dummy Function Returns Number of Points | |

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

Gfox | Foxall's Distance Functions | |

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

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

colourmap | Colour Lookup Tables | |

distmap.owin | Distance Map of Window | |

harmonic | Basis for Harmonic Functions | |

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

pairs.im | Scatterplot Matrix for Pixel Images | |

Hardcore | The Hard Core Point Process Model | |

harmonise.im | Make Pixel Images Compatible | |

hamster | Aherne's hamster tumour data | |

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

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

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

plot.hyperframe | Plot Entries in a Hyperframe | |

edges2triangles | List Triangles in a Graph | |

pairdist.pp3 | Pairwise distances in Three Dimensions | |

bdist.points | Distance to Boundary of Window | |

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

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

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

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

rpoispp | Generate Poisson Point Pattern | |

plot.influence.ppm | Plot Influence Measure | |

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

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

compatible | Test Whether Objects Are Compatible | |

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

rMatClust | Simulate Matern Cluster Process | |

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

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

ppm | Fit Point Process Model to Data | |

sharpen | Data Sharpening of Point Pattern | |

plot.colourmap | Plot a Colour Map | |

tess | Create a Tessellation | |

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

plot.envelope | Plot a Simulation Envelope | |

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

ppx | Multidimensional Space-Time Point Pattern | |

quantile.im | Sample Quantiles of Pixel Image | |

triplet.family | Triplet Interaction Family | |

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

print.quad | Print a Quadrature Scheme | |

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

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

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

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

rNeymanScott | Simulate Neyman-Scott Process | |

swedishpines | Swedish Pines Point Pattern | |

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

scan.test | Spatial Scan Test | |

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

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

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

rMaternII | Simulate Matern Model II | |

rlabel | Random Re-Labelling of Point Pattern | |

rMaternI | Simulate Matern Model I | |

shift.owin | Apply Vector Translation To Window | |

ppp | Create a Point Pattern | |

Jest | Estimate the J-function | |

rhohat | Smoothing Estimate of Covariate Transformation | |

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

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

cells | Biological Cells Point Pattern | |

plot.bermantest | Plot Result of Berman Test | |

suffstat | Sufficient Statistic of Point Process Model | |

psp.object | Class of Line Segment Patterns | |

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

colourtools | Convert and Compare Colours in Different Formats | |

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

Kest.fft | K-function using FFT | |

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

Extract.fv | Extract Subset of Function Values | |

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

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

Ldot.inhom | Inhomogeneous Multitype L Dot Function | |

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

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

affine.owin | Apply Affine Transformation To Window | |

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

Lest | L-function | |

crossdist | Pairwise distances | |

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

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

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

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

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

persp.im | Perspective Plot of Pixel Image | |

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

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

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

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

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

clickpoly | Interactively Define a Polygon | |

Fest | Estimate the empty space function F | |

pp3 | Three Dimensional Point Pattern | |

rLGCP | Simulate Log-Gaussian Cox Process | |

endpoints.psp | Endpoints of Line Segment Pattern | |

concatxy | Concatenate x,y Coordinate Vectors | |

envelope | Simulation Envelopes of Summary Function | |

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

rcell | Simulate Baddeley-Silverman Cell Process | |

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

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

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

eroded.areas | Areas of Morphological Erosions | |

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

linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |

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

linearKinhom | Inhomogeneous Linear K Function | |

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

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

linearK | Linear K Function | |

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

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

profilepl | Profile Maximum Pseudolikelihood | |

urkiola | Urkiola Woods Point Pattern | |

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

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

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

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

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

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

whist | Weighted Histogram | |

is.multitype | Test whether Object is Multitype | |

Kinhom | Inhomogeneous K-function | |

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

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

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

eval.fv | Evaluate Expression Involving Functions | |

convexhull.xy | Convex Hull of Points | |

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

plot.tess | Plot a tessellation | |

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

rpoisline | Generate Poisson Random Line Process | |

as.hyperframe | Convert Data to Hyperframe | |

Hest | Spherical Contact Distribution Function | |

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

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

nnwhich | Nearest neighbour | |

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

rknn | Theoretical Distribution of Nearest Neighbour Distance | |

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

Extract.im | Extract Subset of Image | |

Ord | Generic Ord Interaction model | |

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

plot.quad | plot a Spatial Quadrature Scheme | |

pixellate.owin | Convert Window to Pixel Image | |

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

bdist.tiles | Distance to Boundary of Window | |

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

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

localK | Neighbourhood density function | |

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

project2segment | Move Point To Nearest Line | |

plot.leverage.ppm | Plot Leverage Function | |

lohboot | Bootstrap Confidence Bands for Summary Function | |

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

rGaussPoisson | Simulate Gauss-Poisson Process | |

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

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

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

hyperframe | Hyper Data Frame | |

smooth.fv | Apply Smoothing to Function Values | |

Gest | Nearest Neighbour Distance Function G | |

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

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

Softcore | The Soft Core Point Process Model | |

rStrauss | Perfect Simulation of the Strauss Process | |

dfbetas.ppm | Parameter influence measure | |

rThomas | Simulate Thomas Process | |

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

dilated.areas | Areas of Morphological Dilations | |

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

rotate.owin | Rotate a Window | |

scanpp | Read Point Pattern From Data File | |

setcov | Set Covariance of a Window | |

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

miplot | Morishita Index Plot | |

spatstat.options | Internal Options in Spatstat Package | |

owin.object | Class owin | |

nndist | Nearest neighbour distances | |

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

corners | Corners of a rectangle | |

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

rotate | Rotate | |

rjitter | Random Perturbation of a Point Pattern | |

dilation | Morphological Dilation | |

plot.im | Plot a Pixel Image | |

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

ord.family | Ord Interaction Process Family | |

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

periodify | Make Periodic Copies of a Spatial Pattern | |

nztrees | New Zealand Trees Point Pattern | |

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

rsyst | Simulate systematic random point pattern | |

fv | Create a Function Value Table | |

vertices | Vertices of a Window | |

progressreport | Print Progress Reports | |

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

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

localpcf | Local pair correlation function | |

envelope.envelope | Recompute Envelopes | |

pool | Pool Data | |

marks | Marks of a Point Pattern | |

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

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

stieltjes | Compute Integral of Function Against Cumulative Distribution | |

Extract.quad | Subset of Quadrature Scheme | |

Jmulti | Marked J Function | |

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

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

Kres | Residual K Function | |

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

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

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

areaLoss | Difference of Disc Areas | |

Kmulti | Marked K-Function | |

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

unitname | Name for Unit of Length | |

zapsmall.im | Rounding of Pixel Values | |

clickjoin | Interactively join vertices on a plot | |

integral.im | Integral of a Pixel Image | |

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

Kest | K-function | |

MultiStrauss | The Multitype Strauss Point Process Model | |

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

logLik.slrm | Loglikelihood of Spatial Logistic Regression | |

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

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

interp.im | Interpolate a Pixel Image | |

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

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

rstrat | Simulate Stratified Random Point Pattern | |

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

eval.im | Evaluate Expression Involving Pixel Images | |

fasp.object | Function Arrays for Spatial Patterns | |

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

longleaf | Longleaf Pines Point Pattern | |

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

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

layered | Create List of Plotting Layers | |

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

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

plot.fv | Plot Function Values | |

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

plot.owin | Plot a Spatial Window | |

rMosaicField | Mosaic Random Field | |

nearestsegment | Find Line Segment Nearest to Each Point | |

runiflpp | Uniform Random Points on a Linear Network | |

markcorr | Mark Correlation Function | |

Saturated | Saturated Pairwise Interaction model | |

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

summary.owin | Summary of a Spatial Window | |

rshift.ppp | Randomly Shift a Point Pattern | |

rpoislpp | Poisson Point Process on a Linear Network | |

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

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

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

spatstat-internal | Internal spatstat functions | |

eem | Exponential Energy Marks | |

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

rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |

shift | Apply Vector Translation | |

npoints | Number of Points in a Point Pattern | |

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

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

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

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

clarkevans.test | Clark and Evans Test | |

bramblecanes | Hutchings' Bramble Canes data | |

bdist.pixels | Distance to Boundary of Window | |

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

Emark | Diagnostics for random marking | |

gridweights | Compute Quadrature Weights Based on Grid Counts | |

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

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

as.owin | Convert Data To Class owin | |

inforder.family | Infinite Order Interaction Family | |

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

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

markconnect | Mark Connection Function | |

nbfires | Point Patterns of New Brunswick Forest Fires | |

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

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

plot.linnet | Plot a linear network | |

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

trim.rectangle | Cut margins from rectangle | |

DiggleGratton | Diggle-Gratton model | |

as.ppp | Convert Data To Class ppp | |

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

contour.listof | Plot a List of Things | |

spokes | Spokes pattern of dummy points | |

sumouter | Compute Quadratic Forms | |

bronzefilter | Bronze gradient filter data | |

summary.im | Summarizing a Pixel Image | |

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

Gcom | Model Compensator of Nearest Neighbour Function | |

distmap | Distance Map | |

rpoint | Generate N Random Points | |

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

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

diameter | Diameter of an Object | |

fv.object | Function Value Table | |

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

midpoints.psp | Midpoints of Line Segment Pattern | |

gpc2owin | Convert Polygonal Region into Different Format | |

flipxy | Exchange X and Y Coordinates | |

distmap.ppp | Distance Map of Point Pattern | |

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

distfun | Distance Map as a Function | |

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

methods.distfun | Methods for Distance Functions | |

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

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

pppdist | Distance Between Two Point Patterns | |

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

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

rotate.ppp | Rotate a Point Pattern | |

shapley | Galaxies in the Shapley Supercluster | |

reach | Interaction Distance of a Point Process | |

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

unnormdensity | Weighted kernel smoother | |

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

localKinhom | Inhomogeneous Neighbourhood Density Function | |

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

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

compareFit | Residual Diagnostics for Multiple Fitted Models | |

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

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

as.interact | Extract Interaction Structure | |

diameter.owin | Diameter of a Window | |

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

delaunay | Delaunay Triangulation of Point Pattern | |

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

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

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

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

letterR | Window in Shape of Letter R | |

simdat | Simulated Point Pattern | |

rHardcore | Perfect Simulation of the Hardcore Process | |

scaletointerval | Rescale Data to Lie Between Specified Limits | |

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

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

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

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

Poisson | Poisson Point Process Model | |

rat | Ratio object | |

infline | Infinite Straight Lines | |

simplenet | Simple Example of Linear Network | |

Kmodel | K function of a model | |

clarkevans | Clark and Evans Aggregation Index | |

deltametric | Delta Metric | |

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

im | Create a Pixel Image Object | |

pcf | Pair Correlation Function | |

levelset | Level Set of a Pixel Image | |

markvario | Mark Variogram | |

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

methods.units | Methods for Units | |

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

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

psp | Create a Line Segment Pattern | |

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

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

linim | Create Pixel Image on Linear Network | |

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

superimpose | Superimpose Several Geometric Patterns | |

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

quad.object | Class of Quadrature Schemes | |

summary.quad | Summarizing a Quadrature Scheme | |

varblock | Estimate Variance of Summary Statistic by Subdivision | |

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

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

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

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

default.expand | Compute Expansion Window for Simulation | |

bei | Tropical rain forest trees | |

pairdist | Pairwise distances | |

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

lansing | Lansing Woods Point Pattern | |

owin | Create a Window | |

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

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

centroid.owin | Centroid of a window | |

circumradius | Circumradius and Diameter of a Linear Network | |

pixellate | Convert Spatial Object to Pixel Image | |

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

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

unmark | Remove Marks | |

append.psp | Combine Two Line Segment Patterns | |

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

plot.fasp | Plot a Function Array | |

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

No Results! |

## Last month downloads

## Details

Date | 2012-04-19 |

License | GPL (>= 2) |

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

LazyData | true |

LazyLoad | true |

ByteCompile | true |

Packaged | 2012-04-19 02:59:30 UTC; adrian |

Repository | CRAN |

Date/Publication | 2012-04-19 08:14:28 |

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

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

Contributors | Rolf Turner, Adrian Baddeley |

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