# spatstat v1.22-1

Monthly downloads

## 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 | |

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

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

Softcore | The Soft Core Point Process Model | |

deltametric | Delta Metric | |

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

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

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

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

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

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

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

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

copper | Berman-Huntington points and lines data | |

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

Kcross.inhom | Inhomogeneous Cross K Function | |

gpc2owin | Convert Polygonal Region into Different Format | |

is.marked | Test Whether Marks Are Present | |

bronzefilter | Bronze gradient filter data | |

Ldot.inhom | Inhomogeneous Multitype L Dot Function | |

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

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

as.owin | Convert Data To Class owin | |

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

murchison | Murchison gold deposits | |

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

unmark | Remove Marks | |

rMatClust | Simulate Matern Cluster Process | |

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

Extract.fv | Extract Subset of Function Values | |

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

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

Geyer | Geyer's Saturation Point Process Model | |

Extract.fasp | Extract Subset of Function Array | |

affine.owin | Apply Affine Transformation To Window | |

AreaInter | The Area Interaction Point Process Model | |

Kest | K-function | |

Poisson | Poisson Point Process Model | |

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

anemones | Beadlet Anemones Data | |

append.psp | Combine Two Line Segment Patterns | |

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

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

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

Ord | Generic Ord Interaction model | |

cells | Biological Cells Point Pattern | |

as.psp | Convert Data To Class psp | |

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

eval.fasp | Evaluate Expression Involving Function Arrays | |

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

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

amacrine | Hughes' Amacrine Cell Data | |

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

default.expand | Compute Expansion Window for Simulation | |

expand.owin | Expand Window By Factor | |

heather | Diggle's Heather Data | |

as.hyperframe | Convert Data to Hyperframe | |

midpoints.psp | Midpoints of Line Segment Pattern | |

DiggleGratton | Diggle-Gratton model | |

hamster | Aherne's hamster tumour data | |

Hest | Spherical Contact Distribution Function | |

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

distmap | Distance Map | |

Kmeasure | Reduced Second Moment Measure | |

dilated.areas | Areas of Morphological Dilations | |

boxx | Multi-Dimensional Box | |

Linhom | L-function | |

bdist.points | Distance to Boundary of Window | |

Kest.fft | K-function using FFT | |

intersect.tess | Intersection of Two Tessellations | |

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

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

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

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

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

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

methods.linnet | Methods for Linear Networks | |

rStrauss | Perfect Simulation of the Strauss Process | |

Jest | Estimate the J-function | |

spatstat-deprecated | Deprecated spatstat functions | |

levelset | Level Set of a Pixel Image | |

plot.linnet | Plot a linear network | |

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

nnwhich.pp3 | Nearest neighbours in three dimensions | |

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

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

Extract.quad | Subset of Quadrature Scheme | |

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

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

im | Create a Pixel Image Object | |

nnclean | Nearest Neighbour Clutter Removal | |

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

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

Strauss | The Strauss Point Process Model | |

Lcross.inhom | Inhomogeneous Cross Type L Function | |

demopat | Artificial Data Point Pattern | |

area.owin | Area of a Window | |

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

npoints | Number of Points in a Point Pattern | |

pointsOnLines | Place Points Evenly Along Specified Lines | |

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

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

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

as.im | Convert to Pixel Image | |

pairwise.family | Pairwise Interaction Process Family | |

bdist.pixels | Distance to Boundary of Window | |

owin | Create a Window | |

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

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

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

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

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

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

fryplot | Fry Plot of Point Pattern | |

ppm | Fit Point Process Model to Data | |

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

LennardJones | The Lennard-Jones Potential | |

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

contour.im | Contour plot of pixel image | |

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

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

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

clickjoin | Interactively join vertices on a plot | |

plot.hyperframe | Plot Entries in a Hyperframe | |

Pairwise | Generic Pairwise Interaction model | |

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

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

Iest | Estimate the I-function | |

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

finpines | Pine saplings in Finland. | |

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

rshift.ppp | Randomly Shift a Point Pattern | |

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

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

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

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

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

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

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

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

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

shift | Apply Vector Translation | |

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

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

gridcentres | Rectangular grid of points | |

diameter | Diameter of an Object | |

ponderosa | Ponderosa Pine Tree Point Pattern | |

distfun | Distance Map as a Function | |

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

ord.family | Ord Interaction Process Family | |

rGaussPoisson | Simulate Gauss-Poisson Process | |

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

rgbim | Create Colour-Valued Pixel Image | |

clickppp | Interactively Add Points | |

Jmulti | Marked J Function | |

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

pcfinhom | Inhomogeneous Pair Correlation Function | |

angles.psp | Orientation Angles of Line Segments | |

rMosaicField | Mosaic Random Field | |

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

rthin | Random Thinning | |

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

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

plot.ppp | plot a Spatial Point Pattern | |

dilation | Morphological Dilation | |

pairdist.ppp | Pairwise distances | |

harmonic | Basis for Harmonic Functions | |

gridweights | Compute Quadrature Weights Based on Grid Counts | |

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

eval.im | Evaluate Expression Involving Pixel Images | |

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

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

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

as.tess | Convert Data To Tessellation | |

erosion | Morphological Erosion | |

Fiksel | The Fiksel Interaction | |

OrdThresh | Ord's Interaction model | |

clarkevans.test | Clark and Evans Test | |

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

nbfires | Point Patterns of New Brunswick Forest Fires | |

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

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

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

ewcdf | Weighted Empirical Cumulative Distribution Function | |

shapley | Galaxies in the Shapley Supercluster | |

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

ppx | Multidimensional Space-Time Point Pattern | |

pixellate | Convert Spatial Object to Pixel Image | |

betacells | Beta Ganglion Cells in Cat Retina | |

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

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

localpcf | Local pair correlation function | |

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

disc | Circular Window | |

rpoisline | Generate Poisson Random Line Process | |

BadGey | Hybrid Geyer Point Process Model | |

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

pairdist | Pairwise distances | |

affine | Apply Affine Transformation | |

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

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

plot.listof | Plot a List of Things | |

eem | Exponential Energy Marks | |

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

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

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

Gest | Nearest Neighbour Distance Function G | |

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

connected | Connected components of an image or window | |

rotate | Rotate | |

infline | Infinite Straight Lines | |

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

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

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

spatstat-internal | Internal spatstat functions | |

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

Kinhom | Inhomogeneous K-function | |

runifpoint | Generate N Uniform Random Points | |

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

rpoispp | Generate Poisson Point Pattern | |

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

simdat | Simulated Point Pattern | |

Gmulti | Marked Nearest Neighbour Distance Function | |

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

mincontrast | Method of Minimum Contrast | |

ants | Harkness-Isham ants' nests data | |

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

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

rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |

blur | Apply Gaussian Blur to a Pixel Image | |

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

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

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

letterR | Window in Shape of Letter R | |

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

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

border | Border Region of a Window | |

rMaternII | Simulate Matern Model II | |

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

areaGain | Difference of Disc Areas | |

box3 | Three-Dimensional Box | |

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

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

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

fasp.object | Function Arrays for Spatial Patterns | |

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

pairdist.ppx | Pairwise Distances in Any Dimensions | |

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

persp.im | Perspective Plot of Pixel Image | |

lpp | Create Point Pattern on Linear Network | |

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

as.rectangle | Window Frame | |

pairs.im | Scatterplot Matrix for Pixel Images | |

pairdist.psp | Pairwise distances between line segments | |

rpoint | Generate N Random Points | |

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

MultiHard | The Multitype Hard Core Point Process Model | |

psp.object | Class of Line Segment Patterns | |

Extract.im | Extract Subset of Image | |

chorley | Chorley-Ribble Cancer Data | |

concatxy | Concatenate x,y Coordinate Vectors | |

colourtools | Convert and Compare Colours in Different Formats | |

square | Square Window | |

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

fv | Create a Function Value Table | |

superimpose | Superimpose Several Geometric Patterns | |

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

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

complement.owin | Take Complement of a Window | |

rotate.psp | Rotate a Line Segment Pattern | |

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

Kscaled | Locally Scaled K-function | |

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

endpoints.psp | Endpoints of Line Segment Pattern | |

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

hyperframe | Hyper Data Frame | |

profilepl | Profile Maximum Pseudolikelihood | |

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

owin.object | Class owin | |

diameter.owin | Diameter of a Window | |

rshift | Random Shift | |

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

quantile.im | Sample Quantiles of Pixel Image | |

Gfox | Foxall's Distance Functions | |

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

scaletointerval | Rescale Data to Lie Between Specified Limits | |

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

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

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

perimeter | Perimeter Length of Window | |

sharpen | Data Sharpening of Point Pattern | |

distmap.owin | Distance Map of Window | |

logLik.slrm | Loglikelihood of Spatial Logistic Regression | |

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

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

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

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

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

colourmap | Colour Lookup Tables | |

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

Saturated | Saturated Pairwise Interaction model | |

dirichlet | Dirichlet Tessellation of Point Pattern | |

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

nnwhich.ppx | Nearest Neighbours in Any Dimensions | |

quadratcount | Quadrat counting for a point pattern | |

plot.colourmap | Plot a Colour Map | |

plot.bermantest | Plot Result of Berman Test | |

pixelquad | Quadrature Scheme Based on Pixel Grid | |

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

summary.quad | Summarizing a Quadrature Scheme | |

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

nearestsegment | Find Line Segment Nearest to Each Point | |

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

trim.rectangle | Cut margins from rectangle | |

marks | Marks of a Point Pattern | |

shift.owin | Apply Vector Translation To Window | |

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

varblock | Estimate Variance of Summary Statistic by Subdivision | |

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

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

opening | Morphological Opening | |

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

spatstat.options | Internal Options in Spatstat Package | |

eroded.areas | Areas of Morphological Erosions | |

summary.im | Summarizing a Pixel Image | |

fv.object | Data Frames of Function Values | |

tiles | Extract List of Tiles in a Tessellation | |

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

linnet | Create a Linear Network | |

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

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

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

rknn | Theoretical Distribution of Nearest Neighbour Distance | |

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

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

pairdist.pp3 | Pairwise distances in Three Dimensions | |

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

model.images | Compute Images of Constructed Covariates | |

plot.envelope | Plot a Simulation Envelope | |

rotate.owin | Rotate a Window | |

msr | Signed or Vector-Valued Measure | |

markcorr | Mark Correlation Function | |

periodify | Make Periodic Copies of a Spatial Pattern | |

lut | Lookup Tables | |

rMaternI | Simulate Matern Model I | |

japanesepines | Japanese Pines Point Pattern | |

miplot | Morishita Index Plot | |

plot.quad | plot a Spatial Quadrature Scheme | |

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

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

methods.distfun | Methods for Distance Functions | |

rotate.ppp | Rotate a Point Pattern | |

spruces | Spruces Point Pattern | |

kppm | Fit cluster point process model | |

pppmatching | Create a Point Matching | |

rmpoispp | Generate Multitype Poisson Point Pattern | |

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

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

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

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

plot.tess | Plot a tessellation | |

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

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

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

quadrats | Divide Region into Quadrats | |

simplenet | Simple Example of Linear Network | |

rhohat | Smoothing Estimate of Covariate Transformation | |

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

print.quad | Print a Quadrature Scheme | |

integral.im | Integral of a Pixel Image | |

plot.owin | Plot a Spatial Window | |

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

spatstat-package | The Spatstat Package | |

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

pppdist | Distance Between Two Point Patterns | |

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

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

Kmulti | Marked K-Function | |

markvario | Mark Variogram | |

crossdist | Pairwise distances | |

Lest | L-function | |

rcell | Simulate Baddeley-Silverman Cell Process | |

Emark | Diagnostics for random marking | |

nncross | Nearest Neighbours Between Two Patterns | |

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

rSSI | Simulate Simple Sequential Inhibition | |

closing | Morphological Closing | |

rescue.rectangle | Convert Window Back To Rectangle | |

rmpoint | Generate N Random Multitype Points | |

rjitter | Random Perturbation of a Point Pattern | |

incircle | Find Largest Circle Inside Window | |

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

ppp.object | Class of Point Patterns | |

pixellate.owin | Convert Window to Pixel Image | |

summary.owin | Summary of a Spatial Window | |

plot.fasp | Plot a Function Array | |

scanpp | Read Point Pattern From Data File | |

plot.fv | Plot Function Values | |

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

matchingdist | Distance for a Point Pattern Matching | |

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

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

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

delaunay | Delaunay Triangulation of Point Pattern | |

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

unitname | Name for Unit of Length | |

smooth.fv | Apply Smoothing to Function Values | |

centroid.owin | Centroid of a window | |

runiflpp | Uniform Random Points on a Linear Network | |

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

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

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

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

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

envelope | Simulation Envelopes of Summary Function | |

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

volume | Volume of an Object | |

rpoislinetess | Poisson Line Tessellation | |

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

rMosaicSet | Mosaic Random Set | |

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

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

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

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

psp | Create a Line Segment Pattern | |

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

rlabel | Random Re-Labelling of Point Pattern | |

localK | Neighbourhood density function | |

ppp | Create a Point Pattern | |

bind.fv | Combine Function Value Tables | |

rNeymanScott | Simulate Neyman-Scott Process | |

MultiStrauss | The Multitype Strauss Point Process Model | |

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

whist | Weighted Histogram | |

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

corners | Corners of a rectangle | |

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

rescale | Convert dataset to another unit of length | |

plot.im | Plot a Pixel Image | |

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

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

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

progressreport | Print Progress Reports | |

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

lurking | Lurking variable plot | |

slrm | Spatial Logistic Regression | |

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

pairdist.default | Pairwise distances | |

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

bei | Tropical rain forest trees | |

markcorrint | Mark Correlation Integral | |

tess | Create a Tessellation | |

discpartarea | Area of Part of Disc | |

stieltjes | Compute Integral of Function Against Cumulative Distribution | |

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

rpoislpp | Poisson Point Process on a Linear Network | |

rstrat | Simulate Stratified Random Point Pattern | |

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

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

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

distmap.ppp | Distance Map of Point Pattern | |

rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |

suffstat | Sufficient Statistic of Point Process Model | |

circumradius | Circumradius and Diameter of a Linear Network | |

clickpoly | Interactively Define a Polygon | |

convexhull.xy | Convex Hull of Points | |

setcov | Set Covariance of a Window | |

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

vertices | Vertices of a Window | |

as.ppp | Convert Data To Class ppp | |

ripras | Estimate window from points alone | |

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

convexhull | Convex Hull | |

inforder.family | Infinite Order Interaction Family | |

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

spokes | Spokes pattern of dummy points | |

is.multitype | Test whether Object is Multitype | |

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

logLik.ppm | Log Likelihood for Poisson Point Process Model | |

areaLoss | Difference of Disc Areas | |

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

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

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

nndist | Nearest neighbour distances | |

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

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

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

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

project2segment | Move Point To Nearest Line | |

pppmatching.object | Class of Point Matchings | |

lengths.psp | Lengths of Line Segments | |

reach | Interaction Distance of a Point Process | |

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

urkiola | Urkiola Woods Point Pattern | |

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

rsyst | Simulate systematic random point pattern | |

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

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

Hardcore | The Hard Core Point Process Model | |

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

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

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

clarkevans | Clark and Evans Aggregation Index | |

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

pp3 | Three Dimensional Point Pattern | |

rThomas | Simulate Thomas Process | |

bdist.tiles | Distance to Boundary of Window | |

eval.fv | Evaluate Expression Involving Functions | |

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

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

Fest | Estimate the empty space function F | |

im.object | Class of Images | |

longleaf | Longleaf Pines Point Pattern | |

bramblecanes | Hutchings' Bramble Canes data | |

lansing | Lansing Woods Point Pattern | |

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

interp.im | Interpolate a Pixel Image | |

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

nnwhich | Nearest neighbour | |

quad.object | Class of Quadrature Schemes | |

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

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

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

swedishpines | Swedish Pines Point Pattern | |

nztrees | New Zealand Trees Point Pattern | |

pcf | Pair Correlation Function | |

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

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

markconnect | Mark Connection Function | |

No Results! |

## Last month downloads

## Details

Date | 2011-05-19 |

License | GPL (>= 2) |

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

Packaged | 2011-05-19 07:03:53 UTC; adrian |

Repository | CRAN |

Date/Publication | 2011-05-19 10:05:10 |

depends | base (>= 2.10.0) , deldir (>= 0.0-10) , graphics , mgcv , R (>= 2.10.0) , stats , utils |

suggests | gpclib , maptools , rpanel , scatterplot3d , sm , tkrplot |

Contributors | Rolf Turner, Adrian Baddeley |

#### Include our badge in your README

```
[![Rdoc](http://www.rdocumentation.org/badges/version/spatstat)](http://www.rdocumentation.org/packages/spatstat)
```