# spatstat v1.27-0

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

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

## Functions in spatstat

Name | Description | |

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

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

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

Extract.quad | Subset of Quadrature Scheme | |

Extract.fasp | Extract Subset of Function Array | |

Hardcore | The Hard Core Point Process Model | |

Kmodel | K function of a model | |

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

Gmulti | Marked Nearest Neighbour Distance Function | |

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

as.im | Convert to Pixel Image | |

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

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

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

as.interact | Extract Interaction Structure | |

areaLoss | Difference of Disc Areas | |

Hest | Spherical Contact Distribution Function | |

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

as.psp | Convert Data To Class psp | |

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

as.ppp | Convert Data To Class ppp | |

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

circumradius | Circumradius and Diameter of a Linear Network | |

LennardJones | The Lennard-Jones Potential | |

bronzefilter | Bronze gradient filter data | |

Kest.fft | K-function using FFT | |

Kinhom | Inhomogeneous K-function | |

Emark | Diagnostics for random marking | |

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

dirichlet | Dirichlet Tessellation of Point Pattern | |

boxx | Multi-Dimensional Box | |

envelope | Simulation Envelopes of Summary Function | |

BadGey | Hybrid Geyer Point Process Model | |

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

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

methods.linnet | Methods for Linear Networks | |

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

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

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

Fest | Estimate the empty space function F | |

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

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

Linhom | L-function | |

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

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

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

flu | Influenza Virus Proteins | |

cells | Biological Cells Point Pattern | |

pixelquad | Quadrature Scheme Based on Pixel Grid | |

MultiStrauss | The Multitype Strauss Point Process Model | |

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

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

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

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

Tstat | Third order summary statistic | |

envelope.envelope | Recompute Envelopes | |

distmap | Distance Map | |

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

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

fv.object | Function Value Table | |

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

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

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

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

hyperframe | Hyper Data Frame | |

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

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

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

Kmeasure | Reduced Second Moment Measure | |

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

incircle | Find Largest Circle Inside Window | |

ewcdf | Weighted Empirical Cumulative Distribution Function | |

corners | Corners of a rectangle | |

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

erosion | Morphological Erosion | |

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

hamster | Aherne's hamster tumour data | |

infline | Infinite Straight Lines | |

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

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

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

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

gorillas | Gorilla Nesting Sites | |

intersect.tess | Intersection of Two Tessellations | |

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

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

deltametric | Delta Metric | |

lohboot | Bootstrap Confidence Bands for Summary Function | |

eval.fasp | Evaluate Expression Involving Function Arrays | |

kppm | Fit Cluster or Cox Point Process Model | |

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

eval.im | Evaluate Expression Involving Pixel Images | |

localK | Neighbourhood density function | |

markvario | Mark Variogram | |

inforder.family | Infinite Order Interaction Family | |

rmpoispp | Generate Multitype Poisson Point Pattern | |

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

integral.im | Integral of a Pixel Image | |

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

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

lurking | Lurking variable plot | |

rstrat | Simulate Stratified Random Point Pattern | |

markcorr | Mark Correlation Function | |

rpoislpp | Poisson Point Process on a Linear Network | |

matchingdist | Distance for a Point Pattern Matching | |

fv | Create a Function Value Table | |

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

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

nnwhich.pp3 | Nearest neighbours in three dimensions | |

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

pairwise.family | Pairwise Interaction Process Family | |

imcov | Spatial Covariance of a Pixel Image | |

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

marks | Marks of a Point Pattern | |

pairdist.pp3 | Pairwise distances in Three Dimensions | |

lpp | Create Point Pattern on Linear Network | |

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

nnclean | Nearest Neighbour Clutter Removal | |

methods.distfun | Methods for Distance Functions | |

pairdist.ppx | Pairwise Distances in Any Dimensions | |

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

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

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

plot.fasp | Plot a Function Array | |

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

methods.units | Methods for Units | |

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

nndist | Nearest neighbour distances | |

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

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

pixellate.owin | Convert Window to Pixel Image | |

Extract.fv | Extract Subset of Function Values | |

plot.fv | Plot Function Values | |

perimeter | Perimeter Length of Window | |

periodify | Make Periodic Copies of a Spatial Pattern | |

nearestsegment | Find Line Segment Nearest to Each Point | |

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

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

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

nnwhich | Nearest neighbour | |

plot.linnet | Plot a linear network | |

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

rhohat | Smoothing Estimate of Covariate Transformation | |

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

rMaternI | Simulate Matern Model I | |

scalardilate | Apply Scalar Dilation | |

plot.colourmap | Plot a Colour Map | |

betacells | Beta Ganglion Cells in Cat Retina | |

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

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

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

psp | Create a Line Segment Pattern | |

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

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

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

rStrauss | Perfect Simulation of the Strauss Process | |

pp3 | Three Dimensional Point Pattern | |

rThomas | Simulate Thomas Process | |

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

ripras | Estimate window from points alone | |

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

reflect | Reflect In Origin | |

scaletointerval | Rescale Data to Lie Between Specified Limits | |

ppp.object | Class of Point Patterns | |

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

rsyst | Simulate systematic random point pattern | |

runiflpp | Uniform Random Points on a Linear Network | |

spatstat-deprecated | Deprecated spatstat functions | |

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

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

chicago | Chicago Street Crime Data | |

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

vertices | Vertices of a Window | |

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

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

rgbim | Create Colour-Valued Pixel Image | |

clickppp | Interactively Add Points | |

rpoint | Generate N Random Points | |

summary.owin | Summary of a Spatial Window | |

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

shift | Apply Vector Translation | |

rMaternII | Simulate Matern Model II | |

rHardcore | Perfect Simulation of the Hardcore Process | |

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

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

rpoisline | Generate Poisson Random Line Process | |

dfbetas.ppm | Parameter influence measure | |

rMatClust | Simulate Matern Cluster Process | |

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

dilated.areas | Areas of Morphological Dilations | |

transect.im | Pixel Values Along a Transect | |

tess | Create a Tessellation | |

Lcross.inhom | Inhomogeneous Cross Type L Function | |

Lest | L-function | |

OrdThresh | Ord's Interaction model | |

scanpp | Read Point Pattern From Data File | |

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

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

expand.owin | Apply Expansion Rule | |

triplet.family | Triplet Interaction Family | |

will.expand | Test Expansion Rule | |

blur | Apply Gaussian Blur to a Pixel Image | |

slrm | Spatial Logistic Regression | |

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

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

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

swedishpines | Swedish Pines Point Pattern | |

gpc2owin | Convert Polygonal Region into Different Format | |

harmonic | Basis for Harmonic Functions | |

im | Create a Pixel Image Object | |

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

connected | Connected components of an image or window | |

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

distfun | Distance Map as a Function | |

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

markcorrint | Mark Correlation Integral | |

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

mincontrast | Method of Minimum Contrast | |

flipxy | Exchange X and Y Coordinates | |

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

nnwhich.ppx | Nearest Neighbours in Any Dimensions | |

plot.im | Plot a Pixel Image | |

plot.tess | Plot a tessellation | |

linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |

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

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

print.quad | Print a Quadrature Scheme | |

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

Ldot.inhom | Inhomogeneous Multitype L Dot Function | |

msr | Signed or Vector-Valued Measure | |

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

Pairwise | Generic Pairwise Interaction model | |

clickjoin | Interactively join vertices on a plot | |

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

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

quantile.im | Sample Quantiles of Pixel Image | |

rMosaicField | Mosaic Random Field | |

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

owin | Create a Window | |

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

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

rjitter | Random Perturbation of a Point Pattern | |

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

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

pairdist.psp | Pairwise distances between line segments | |

border | Border Region of a Window | |

plot.listof | Plot a List of Things | |

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

spatstat.options | Internal Options in Spatstat Package | |

ppp | Create a Point Pattern | |

endpoints.psp | Endpoints of Line Segment Pattern | |

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

is.multitype | Test whether Object is Multitype | |

linnet | Create a Linear Network | |

ppx | Multidimensional Space-Time Point Pattern | |

quad.object | Class of Quadrature Schemes | |

linearpcf | Linear Pair Correlation Function | |

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

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

crossdist | Pairwise distances | |

rSSI | Simulate Simple Sequential Inhibition | |

contour.listof | Plot a List of Things | |

rotate | Rotate | |

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

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

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

nbfires | Point Patterns of New Brunswick Forest Fires | |

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

owin.object | Class owin | |

rpoispp | Generate Poisson Point Pattern | |

rshift | Random Shift | |

pairdist.ppp | Pairwise distances | |

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

rthin | Random Thinning | |

plot.ppp | plot a Spatial Point Pattern | |

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

scan.test | Spatial Scan Test | |

smooth.fv | Apply Smoothing to Function Values | |

Gcom | Model Compensator of Nearest Neighbour Function | |

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

Gres | Residual G Function | |

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

profilepl | Profile Maximum Pseudolikelihood | |

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

quadrats | Divide Region into Quadrats | |

rescue.rectangle | Convert Window Back To Rectangle | |

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

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

spokes | Spokes pattern of dummy points | |

rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |

Kmulti.inhom | Inhomogeneous Marked K-Function | |

rknn | Theoretical Distribution of Nearest Neighbour Distance | |

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

summary.im | Summarizing a Pixel Image | |

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

anemones | Beadlet Anemones Data | |

bei | Tropical rain forest trees | |

stieltjes | Compute Integral of Function Against Cumulative Distribution | |

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

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

discpartarea | Area of Part of Disc | |

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

rshift.ppp | Randomly Shift a Point Pattern | |

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

fasp.object | Function Arrays for Spatial Patterns | |

fryplot | Fry Plot of Point Pattern | |

finpines | Pine saplings in Finland. | |

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

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

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

AreaInter | The Area Interaction Point Process Model | |

Ord | Generic Ord Interaction model | |

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

Strauss | The Strauss Point Process Model | |

Gfox | Foxall's Distance Functions | |

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

Iest | Estimate the I-function | |

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

amacrine | Hughes' Amacrine Cell Data | |

Gest | Nearest Neighbour Distance Function G | |

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

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

pixellate | Convert Spatial Object to Pixel Image | |

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

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

Poisson | Poisson Point Process Model | |

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

rNeymanScott | Simulate Neyman-Scott Process | |

clarkevans.test | Clark and Evans Test | |

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

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

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

Jmulti | Marked J Function | |

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

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

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

compatible | Test Whether Objects Are Compatible | |

delaunay | Delaunay Triangulation of Point Pattern | |

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

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

distmap.ppp | Distance Map of Point Pattern | |

clarkevans | Clark and Evans Aggregation Index | |

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

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

rotate.ppp | Rotate a Point Pattern | |

rescale | Convert dataset to another unit of length | |

bdist.points | Distance to Boundary of Window | |

box3 | Three-Dimensional Box | |

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

copper | Berman-Huntington points and lines data | |

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

rmpoint | Generate N Random Multitype Points | |

im.object | Class of Images | |

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

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

levelset | Level Set of a Pixel Image | |

spatstat-internal | Internal spatstat functions | |

centroid.owin | Centroid of a window | |

edges2triangles | List Triangles in a Graph | |

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

clickpoly | Interactively Define a Polygon | |

linearK | Linear K Function | |

longleaf | Longleaf Pines Point Pattern | |

eem | Exponential Energy Marks | |

markconnect | Mark Connection Function | |

pcf | Pair Correlation Function | |

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

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

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

convexhull | Convex Hull | |

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

colourmap | Colour Lookup Tables | |

contour.im | Contour plot of pixel image | |

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

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

model.images | Compute Images of Constructed Covariates | |

persp.im | Perspective Plot of Pixel Image | |

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

layered | Create List of Plotting Layers | |

nztrees | New Zealand Trees Point Pattern | |

miplot | Morishita Index Plot | |

letterR | Window in Shape of Letter R | |

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

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

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

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

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

pcfinhom | Inhomogeneous Pair Correlation Function | |

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

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

npfun | Dummy Function Returns Number of Points | |

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

opening | Morphological Opening | |

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

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

rMosaicSet | Mosaic Random Set | |

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

plot.influence.ppm | Plot Influence Measure | |

sharpen | Data Sharpening of Point Pattern | |

plot.hyperframe | Plot Entries in a Hyperframe | |

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

progressreport | Print Progress Reports | |

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

simdat | Simulated Point Pattern | |

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

varblock | Estimate Variance of Summary Statistic by Subdivision | |

whist | Weighted Histogram | |

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

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

project2segment | Move Point To Nearest Line | |

quadratcount | Quadrat counting for a point pattern | |

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

rlabel | Random Re-Labelling of Point Pattern | |

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

rmhexpand | Specify Simulation Window or Expansion Rule | |

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

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

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

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

rotate.owin | Rotate a Window | |

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

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

suffstat | Sufficient Statistic of Point Process Model | |

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

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

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

affine | Apply Affine Transformation | |

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

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

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

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

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

trim.rectangle | Cut margins from rectangle | |

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

superimpose | Superimpose Several Geometric Patterns | |

unnormdensity | Weighted kernel smoother | |

urkiola | Urkiola Woods Point Pattern | |

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

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

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

eval.fv | Evaluate Expression Involving Functions | |

lengths.psp | Lengths of Line Segments | |

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

linim | Create Pixel Image on Linear Network | |

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

lut | Lookup Tables | |

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

interp.im | Interpolate a Pixel Image | |

npoints | Number of Points in a Point Pattern | |

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

pairdist | Pairwise distances | |

plot.layered | Layered Plot | |

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

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

shapley | Galaxies in the Shapley Supercluster | |

shift.owin | Apply Vector Translation To Window | |

setcov | Set Covariance of a Window | |

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

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

Kcross.inhom | Inhomogeneous Cross K Function | |

Kmulti | Marked K-Function | |

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

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

ants | Harkness-Isham ants' nests data | |

as.owin | Convert Data To Class owin | |

bdist.pixels | Distance to Boundary of Window | |

bdist.tiles | Distance to Boundary of Window | |

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

affine.owin | Apply Affine Transformation To Window | |

diameter | Diameter of an Object | |

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

gridweights | Compute Quadrature Weights Based on Grid Counts | |

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

area.owin | Area of a Window | |

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

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

complement.owin | Take Complement of a Window | |

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

convolve.im | Convolution of Pixel Images | |

gridcentres | Rectangular grid of points | |

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

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

nncross | Nearest Neighbours Between Two Patterns | |

logLik.slrm | Loglikelihood of Spatial Logistic Regression | |

pairdist.default | Pairwise distances | |

localKinhom | Inhomogeneous Neighbourhood Density Function | |

pairs.im | Scatterplot Matrix for Pixel Images | |

murchison | Murchison gold deposits | |

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

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

plot.owin | Plot a Spatial Window | |

ponderosa | Ponderosa Pine Tree Point Pattern | |

rPoissonCluster | Simulate Poisson Cluster Process | |

reach | Interaction Distance of a Point Process | |

rGaussPoisson | Simulate Gauss-Poisson Process | |

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

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

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

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

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

rotate.psp | Rotate a Line Segment Pattern | |

square | Square Window | |

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

unmark | Remove Marks | |

volume | Volume of an Object | |

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

DiggleGratton | Diggle-Gratton model | |

Kscaled | Locally Scaled K-function | |

Softcore | The Soft Core Point Process Model | |

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

as.rectangle | Window Frame | |

colourtools | Convert and Compare Colours in Different Formats | |

concatxy | Concatenate x,y Coordinate Vectors | |

convexhull.xy | Convex Hull of Points | |

demopat | Artificial Data Point Pattern | |

harmonise.im | Make Pixel Images Compatible | |

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

japanesepines | Japanese Pines Point Pattern | |

lansing | Lansing Woods Point Pattern | |

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

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

plot.envelope | Plot a Simulation Envelope | |

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

pppmatching | Create a Point Matching | |

MultiHard | The Multitype Hard Core Point Process Model | |

Saturated | Saturated Pairwise Interaction model | |

runifpoint | Generate N Uniform Random Points | |

angles.psp | Orientation Angles of Line Segments | |

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

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

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

spatstat-package | The Spatstat Package | |

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

sumouter | Compute Quadratic Forms | |

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

closing | Morphological Closing | |

dilation | Morphological Dilation | |

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

eroded.areas | Areas of Morphological Erosions | |

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

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

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

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

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

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

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

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

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

rLGCP | Simulate Log-Gaussian Cox Process | |

summary.quad | Summarizing a Quadrature Scheme | |

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

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

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

Fiksel | The Fiksel Interaction | |

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

Kest | K-function | |

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

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

bramblecanes | Hutchings' Bramble Canes data | |

compareFit | Residual Diagnostics for Multiple Fitted Models | |

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

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

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

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

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

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

is.rectangle | Determine Type of Window | |

localpcf | Local pair correlation function | |

plot.bermantest | Plot Result of Berman Test | |

plot.leverage.ppm | Plot Leverage Function | |

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

pool.envelope | Pool Data from Several Envelopes | |

rat | Ratio object | |

plot.quad | plot a Spatial Quadrature Scheme | |

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

pointsOnLines | Place Points Evenly Along Specified Lines | |

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

rpoislinetess | Poisson Line Tessellation | |

rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |

zapsmall.im | Rounding of Pixel Values | |

Jest | Estimate the J-function | |

Kcom | Model Compensator of K Function | |

append.psp | Combine Two Line Segment Patterns | |

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

areaGain | Difference of Disc Areas | |

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

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

disc | Circular Window | |

diameter.owin | Diameter of a Window | |

distmap.owin | Distance Map of Window | |

heather | Diggle's Heather Data | |

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

linearKinhom | Inhomogeneous Linear K Function | |

ppm | Fit Point Process Model to Data | |

pppdist | Distance Between Two Point Patterns | |

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

pppmatching.object | Class of Point Matchings | |

psp.object | Class of Line Segment Patterns | |

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

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

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

tiles | Extract List of Tiles in a Tessellation | |

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

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

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

Kres | Residual K Function | |

bind.fv | Combine Function Value Tables | |

chorley | Chorley-Ribble Cancer Data | |

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

pool | Pool Data | |

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

rcell | Simulate Baddeley-Silverman Cell Process | |

unitname | Name for Unit of Length | |

Extract.im | Extract Subset of Image | |

is.marked | Test Whether Marks Are Present | |

spruces | Spruces Point Pattern | |

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

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

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

ord.family | Ord Interaction Process Family | |

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

Geyer | Geyer's Saturation Point Process Model | |

simplenet | Simple Example of Linear Network | |

midpoints.psp | Midpoints of Line Segment Pattern | |

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

as.hyperframe | Convert Data to Hyperframe | |

as.tess | Convert Data To Tessellation | |

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

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

Triplets | The Triplet Point Process Model | |

No Results! |

## Last month downloads

## Details

Date | 2012-05-16 |

License | GPL (>= 2) |

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

LazyData | true |

LazyLoad | true |

ByteCompile | true |

Packaged | 2012-05-16 10:29:46 UTC; adrian |

Repository | CRAN |

Date/Publication | 2012-05-16 12:44:15 |

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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