# spatstat v1.22-2

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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 | |

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

LennardJones | The Lennard-Jones Potential | |

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

Hardcore | The Hard Core Point Process Model | |

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

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

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

BadGey | Hybrid Geyer Point Process Model | |

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

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

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

Gmulti | Marked Nearest Neighbour Distance Function | |

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

bdist.pixels | Distance to Boundary of Window | |

Extract.fv | Extract Subset of Function Values | |

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

Jest | Estimate the J-function | |

as.im | Convert to Pixel Image | |

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

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

box3 | Three-Dimensional Box | |

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

angles.psp | Orientation Angles of Line Segments | |

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

as.tess | Convert Data To Tessellation | |

Kcross.inhom | Inhomogeneous Cross K Function | |

Kest.fft | K-function using FFT | |

Kinhom | Inhomogeneous K-function | |

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

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

Jmulti | Marked J Function | |

Ord | Generic Ord Interaction model | |

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

Saturated | Saturated Pairwise Interaction model | |

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

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

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

areaLoss | Difference of Disc Areas | |

Kmulti | Marked K-Function | |

Gfox | Foxall's Distance Functions | |

AreaInter | The Area Interaction Point Process Model | |

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

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

Extract.im | Extract Subset of Image | |

as.hyperframe | Convert Data to Hyperframe | |

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

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

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

Kscaled | Locally Scaled K-function | |

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

affine | Apply Affine Transformation | |

demopat | Artificial Data Point Pattern | |

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

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

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

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

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

Emark | Diagnostics for random marking | |

concatxy | Concatenate x,y Coordinate Vectors | |

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

Lcross.inhom | Inhomogeneous Cross Type L Function | |

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

Poisson | Poisson Point Process Model | |

Iest | Estimate the I-function | |

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

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

bei | Tropical rain forest trees | |

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

append.psp | Combine Two Line Segment Patterns | |

gpc2owin | Convert Polygonal Region into Different Format | |

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

deltametric | Delta Metric | |

bind.fv | Combine Function Value Tables | |

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

Fest | Estimate the empty space function F | |

Fiksel | The Fiksel Interaction | |

Strauss | The Strauss Point Process Model | |

Hest | Spherical Contact Distribution Function | |

Extract.quad | Subset of Quadrature Scheme | |

Linhom | L-function | |

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

Kest | K-function | |

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

boxx | Multi-Dimensional Box | |

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

DiggleGratton | Diggle-Gratton model | |

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

diameter | Diameter of an Object | |

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

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

Kmeasure | Reduced Second Moment Measure | |

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

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

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

endpoints.psp | Endpoints of Line Segment Pattern | |

dirichlet | Dirichlet Tessellation of Point Pattern | |

Ldot.inhom | Inhomogeneous Multitype L Dot Function | |

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

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

spatstat-deprecated | Deprecated spatstat functions | |

copper | Berman-Huntington points and lines data | |

bdist.points | Distance to Boundary of Window | |

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

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

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

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

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

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

distmap.owin | Distance Map of Window | |

diameter.owin | Diameter of a Window | |

msr | Signed or Vector-Valued Measure | |

ewcdf | Weighted Empirical Cumulative Distribution Function | |

hyperframe | Hyper Data Frame | |

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

distmap | Distance Map | |

intersect.tess | Intersection of Two Tessellations | |

closing | Morphological Closing | |

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

MultiStrauss | The Multitype Strauss Point Process Model | |

clickjoin | Interactively join vertices on a plot | |

lengths.psp | Lengths of Line Segments | |

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

clickppp | Interactively Add Points | |

betacells | Beta Ganglion Cells in Cat Retina | |

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

colourtools | Convert and Compare Colours in Different Formats | |

periodify | Make Periodic Copies of a Spatial Pattern | |

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

circumradius | Circumradius and Diameter of a Linear Network | |

bronzefilter | Bronze gradient filter data | |

harmonic | Basis for Harmonic Functions | |

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

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

crossdist | Pairwise distances | |

plot.linnet | Plot a linear network | |

clarkevans.test | Clark and Evans Test | |

as.rectangle | Window Frame | |

anemones | Beadlet Anemones Data | |

default.expand | Compute Expansion Window for Simulation | |

bramblecanes | Hutchings' Bramble Canes data | |

connected | Connected components of an image or window | |

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

OrdThresh | Ord's Interaction model | |

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

delaunay | Delaunay Triangulation of Point Pattern | |

integral.im | Integral of a Pixel Image | |

hamster | Aherne's hamster tumour data | |

affine.owin | Apply Affine Transformation To Window | |

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

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

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

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

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

nnwhich.ppx | Nearest Neighbours in Any Dimensions | |

plot.ppp | plot a Spatial Point Pattern | |

nnwhich.pp3 | Nearest neighbours in three dimensions | |

amacrine | Hughes' Amacrine Cell Data | |

eval.fasp | Evaluate Expression Involving Function Arrays | |

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

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

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

eval.im | Evaluate Expression Involving Pixel Images | |

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

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

dilated.areas | Areas of Morphological Dilations | |

fryplot | Fry Plot of Point Pattern | |

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

as.owin | Convert Data To Class owin | |

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

clarkevans | Clark and Evans Aggregation Index | |

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

contour.im | Contour plot of pixel image | |

heather | Diggle's Heather Data | |

complement.owin | Take Complement of a Window | |

gridcentres | Rectangular grid of points | |

fasp.object | Function Arrays for Spatial Patterns | |

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

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

MultiHard | The Multitype Hard Core Point Process Model | |

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

pppdist | Distance Between Two Point Patterns | |

area.owin | Area of a Window | |

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

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

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

ppp.object | Class of Point Patterns | |

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

clickpoly | Interactively Define a Polygon | |

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

owin | Create a Window | |

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

dilation | Morphological Dilation | |

distmap.ppp | Distance Map of Point Pattern | |

japanesepines | Japanese Pines Point Pattern | |

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

rMosaicSet | Mosaic Random Set | |

ord.family | Ord Interaction Process Family | |

localK | Neighbourhood density function | |

pairdist.default | Pairwise distances | |

letterR | Window in Shape of Letter R | |

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

pairwise.family | Pairwise Interaction Process Family | |

nearestsegment | Find Line Segment Nearest to Each Point | |

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

infline | Infinite Straight Lines | |

rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |

nncross | Nearest Neighbours Between Two Patterns | |

distfun | Distance Map as a Function | |

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

rcell | Simulate Baddeley-Silverman Cell Process | |

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

eroded.areas | Areas of Morphological Erosions | |

nnclean | Nearest Neighbour Clutter Removal | |

spatstat-internal | Internal spatstat functions | |

colourmap | Colour Lookup Tables | |

pairdist.ppx | Pairwise Distances in Any Dimensions | |

inforder.family | Infinite Order Interaction Family | |

eval.fv | Evaluate Expression Involving Functions | |

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

im.object | Class of Images | |

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

rgbim | Create Colour-Valued Pixel Image | |

pairdist.psp | Pairwise distances between line segments | |

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

envelope | Simulation Envelopes of Summary Function | |

levelset | Level Set of a Pixel Image | |

lpp | Create Point Pattern on Linear Network | |

blur | Apply Gaussian Blur to a Pixel Image | |

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

eem | Exponential Energy Marks | |

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

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

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

rotate.psp | Rotate a Line Segment Pattern | |

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

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

rshift.ppp | Randomly Shift a Point Pattern | |

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

border | Border Region of a Window | |

opening | Morphological Opening | |

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

runifpoint | Generate N Uniform Random Points | |

longleaf | Longleaf Pines Point Pattern | |

pixelquad | Quadrature Scheme Based on Pixel Grid | |

linearK | Network K Function | |

profilepl | Profile Maximum Pseudolikelihood | |

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

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

nbfires | Point Patterns of New Brunswick Forest Fires | |

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

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

rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |

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

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

lurking | Lurking variable plot | |

pairs.im | Scatterplot Matrix for Pixel Images | |

is.marked | Test Whether Marks Are Present | |

is.multitype | Test whether Object is Multitype | |

rescale | Convert dataset to another unit of length | |

markcorrint | Mark Correlation Integral | |

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

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

midpoints.psp | Midpoints of Line Segment Pattern | |

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

perimeter | Perimeter Length of Window | |

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

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

rshift | Random Shift | |

im | Create a Pixel Image Object | |

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

plot.hyperframe | Plot Entries in a Hyperframe | |

plot.listof | Plot a List of Things | |

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

rhohat | Smoothing Estimate of Covariate Transformation | |

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

lut | Lookup Tables | |

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

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

discpartarea | Area of Part of Disc | |

shift.owin | Apply Vector Translation To Window | |

fv | Create a Function Value Table | |

unitname | Name for Unit of Length | |

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

kppm | Fit Cluster or Cox Point Process Model | |

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

rmpoispp | Generate Multitype Poisson Point Pattern | |

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

plot.tess | Plot a tessellation | |

rpoislpp | Poisson Point Process on a Linear Network | |

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

ppx | Multidimensional Space-Time Point Pattern | |

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

methods.distfun | Methods for Distance Functions | |

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

pcfinhom | Inhomogeneous Pair Correlation Function | |

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

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

pairdist.pp3 | Pairwise distances in Three Dimensions | |

marks | Marks of a Point Pattern | |

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

nnwhich | Nearest neighbour | |

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

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

ppm | Fit Point Process Model to Data | |

owin.object | Class owin | |

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

tess | Create a Tessellation | |

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

rotate.ppp | Rotate a Point Pattern | |

pppmatching.object | Class of Point Matchings | |

lansing | Lansing Woods Point Pattern | |

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

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

npoints | Number of Points in a Point Pattern | |

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

convexhull | Convex Hull | |

logLik.slrm | Loglikelihood of Spatial Logistic Regression | |

rpoint | Generate N Random Points | |

rotate | Rotate | |

matchingdist | Distance for a Point Pattern Matching | |

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

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

rMosaicField | Mosaic Random Field | |

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

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

quadrats | Divide Region into Quadrats | |

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

smooth.fv | Apply Smoothing to Function Values | |

as.psp | Convert Data To Class psp | |

plot.bermantest | Plot Result of Berman Test | |

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

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

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

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

quadratcount | Quadrat counting for a point pattern | |

rGaussPoisson | Simulate Gauss-Poisson Process | |

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

plot.quad | plot a Spatial Quadrature Scheme | |

rmpoint | Generate N Random Multitype Points | |

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

setcov | Set Covariance of a Window | |

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

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

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

scaletointerval | Rescale Data to Lie Between Specified Limits | |

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

model.images | Compute Images of Constructed Covariates | |

print.quad | Print a Quadrature Scheme | |

pairdist | Pairwise distances | |

rstrat | Simulate Stratified Random Point Pattern | |

murchison | Murchison gold deposits | |

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

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

ppp | Create a Point Pattern | |

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

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

rknn | Theoretical Distribution of Nearest Neighbour Distance | |

plot.fasp | Plot a Function Array | |

simdat | Simulated Point Pattern | |

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

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

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

unmark | Remove Marks | |

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

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

summary.quad | Summarizing a Quadrature Scheme | |

rsyst | Simulate systematic random point pattern | |

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

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

rpoisline | Generate Poisson Random Line Process | |

spruces | Spruces Point Pattern | |

rLGCP | Simulate Log-Gaussian Cox Process | |

persp.im | Perspective Plot of Pixel Image | |

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

spokes | Spokes pattern of dummy points | |

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

ripras | Estimate window from points alone | |

suffstat | Sufficient Statistic of Point Process Model | |

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

quantile.im | Sample Quantiles of Pixel Image | |

shapley | Galaxies in the Shapley Supercluster | |

plot.colourmap | Plot a Colour Map | |

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

rpoislinetess | Poisson Line Tessellation | |

disc | Circular Window | |

rMatClust | Simulate Matern Cluster Process | |

superimpose | Superimpose Several Geometric Patterns | |

rMaternII | Simulate Matern Model II | |

rMaternI | Simulate Matern Model I | |

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

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

rSSI | Simulate Simple Sequential Inhibition | |

project2segment | Move Point To Nearest Line | |

urkiola | Urkiola Woods Point Pattern | |

markconnect | Mark Connection Function | |

expand.owin | Expand Window By Factor | |

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

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

shift | Apply Vector Translation | |

pairdist.ppp | Pairwise distances | |

scanpp | Read Point Pattern From Data File | |

rNeymanScott | Simulate Neyman-Scott Process | |

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

vertices | Vertices of a Window | |

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

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

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

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

stieltjes | Compute Integral of Function Against Cumulative Distribution | |

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

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

swedishpines | Swedish Pines Point Pattern | |

volume | Volume of an Object | |

quad.object | Class of Quadrature Schemes | |

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

nztrees | New Zealand Trees Point Pattern | |

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

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

rpoispp | Generate Poisson Point Pattern | |

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

rotate.owin | Rotate a Window | |

pppmatching | Create a Point Matching | |

psp | Create a Line Segment Pattern | |

pixellate | Convert Spatial Object to Pixel Image | |

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

sharpen | Data Sharpening of Point Pattern | |

simplenet | Simple Example of Linear Network | |

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

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

varblock | Estimate Variance of Summary Statistic by Subdivision | |

rStrauss | Perfect Simulation of the Strauss Process | |

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

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

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

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

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

whist | Weighted Histogram | |

rlabel | Random Re-Labelling of Point Pattern | |

tiles | Extract List of Tiles in a Tessellation | |

Softcore | The Soft Core Point Process Model | |

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

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

corners | Corners of a rectangle | |

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

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

fv.object | Function Value Table | |

gridweights | Compute Quadrature Weights Based on Grid Counts | |

incircle | Find Largest Circle Inside Window | |

interp.im | Interpolate a Pixel Image | |

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

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

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

markvario | Mark Variogram | |

plot.envelope | Plot a Simulation Envelope | |

psp.object | Class of Line Segment Patterns | |

rescue.rectangle | Convert Window Back To Rectangle | |

reach | Interaction Distance of a Point Process | |

rjitter | Random Perturbation of a Point Pattern | |

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

rthin | Random Thinning | |

square | Square Window | |

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

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

Extract.fasp | Extract Subset of Function Array | |

Pairwise | Generic Pairwise Interaction model | |

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

bdist.tiles | Distance to Boundary of Window | |

centroid.owin | Centroid of a window | |

chorley | Chorley-Ribble Cancer Data | |

erosion | Morphological Erosion | |

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

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

linnet | Create a Linear Network | |

methods.linnet | Methods for Linear Networks | |

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

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

plot.fv | Plot Function Values | |

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

pointsOnLines | Place Points Evenly Along Specified Lines | |

ponderosa | Ponderosa Pine Tree Point Pattern | |

progressreport | Print Progress Reports | |

rThomas | Simulate Thomas Process | |

trim.rectangle | Cut margins from rectangle | |

spatstat-package | The Spatstat Package | |

summary.owin | Summary of a Spatial Window | |

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

Lest | L-function | |

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

areaGain | Difference of Disc Areas | |

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

as.ppp | Convert Data To Class ppp | |

cells | Biological Cells Point Pattern | |

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

miplot | Morishita Index Plot | |

mincontrast | Method of Minimum Contrast | |

nndist | Nearest neighbour distances | |

pcf | Pair Correlation Function | |

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

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

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

pixellate.owin | Convert Window to Pixel Image | |

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

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

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

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

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

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

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

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

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

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

Kmodel | K function of a model | |

localpcf | Local pair correlation function | |

convexhull.xy | Convex Hull of Points | |

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

finpines | Pine saplings in Finland. | |

ants | Harkness-Isham ants' nests data | |

pp3 | Three Dimensional Point Pattern | |

runiflpp | Uniform Random Points on a Linear Network | |

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

Gest | Nearest Neighbour Distance Function G | |

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

spatstat.options | Internal Options in Spatstat Package | |

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

markcorr | Mark Correlation Function | |

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

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

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

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

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

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

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

plot.im | Plot a Pixel Image | |

plot.owin | Plot a Spatial Window | |

slrm | Spatial Logistic Regression | |

summary.im | Summarizing a Pixel Image | |

No Results! |

## Last month downloads

## Details

Date | 2011-06-13 |

License | GPL (>= 2) |

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

Packaged | 2011-06-13 09:45:14 UTC; adrian |

Repository | CRAN |

Date/Publication | 2011-06-15 18:11:32 |

depends | base (>= 2.10.0) , deldir (>= 0.0-10) , graphics , mgcv , R (>= 2.10.0) , RandomFields (>= 2.0) , stats , utils |

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

Contributors | Rolf Turner, Adrian Baddeley |

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