# spatstat v1.30-0

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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 | |

Emark | Diagnostics for random marking | |

Kmulti | Marked K-Function | |

Lest | L-function | |

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

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

erosion | Morphological Erosion | |

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

fasp.object | Function Arrays for Spatial Patterns | |

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

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

matchingdist | Distance for a Point Pattern Matching | |

Kest | K-function | |

Kmulti.inhom | Inhomogeneous Marked K-Function | |

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

Lcross.inhom | Inhomogeneous Cross Type L Function | |

miplot | Morishita Index Plot | |

MultiHard | The Multitype Hard Core Point Process Model | |

nearestsegment | Find Line Segment Nearest to Each Point | |

markconnect | Mark Connection Function | |

Softcore | The Soft Core Point Process Model | |

Gres | Residual G Function | |

Kcom | Model Compensator of K Function | |

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

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

OrdThresh | Ord's Interaction model | |

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

MultiStrauss | The Multitype Strauss Point Process Model | |

intersect.tess | Intersection of Two Tessellations | |

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

bronzefilter | Bronze gradient filter data | |

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

AreaInter | The Area Interaction Point Process Model | |

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

ppm | Fit Point Process Model to Data | |

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

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

as.ppm | Extract Fitted Point Process Model | |

blur | Apply Gaussian Blur to a Pixel Image | |

affine | Apply Affine Transformation | |

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

closing | Morphological Closing | |

as.hyperframe | Convert Data to Hyperframe | |

BadGey | Hybrid Geyer Point Process Model | |

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

Kcross.inhom | Inhomogeneous Cross K Function | |

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

concatxy | Concatenate x,y Coordinate Vectors | |

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

as.ppp | Convert Data To Class ppp | |

rescale | Convert dataset to another unit of length | |

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

flu | Influenza Virus Proteins | |

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

distcdf | Distribution Function of Interpoint Distance | |

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

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

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

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

expand.owin | Apply Expansion Rule | |

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

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

bramblecanes | Hutchings' Bramble Canes data | |

gordon | People in Gordon Square | |

rotate.owin | Rotate a Window | |

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

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

methods.units | Methods for Units | |

midpoints.psp | Midpoints of Line Segment Pattern | |

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

nnwhich | Nearest neighbour | |

clickjoin | Interactively join vertices on a plot | |

scalardilate | Apply Scalar Dilation | |

npfun | Dummy Function Returns Number of Points | |

mincontrast | Method of Minimum Contrast | |

sumouter | Compute Quadratic Forms | |

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

Extract.im | Extract Subset of Image | |

longleaf | Longleaf Pines Point Pattern | |

periodify | Make Periodic Copies of a Spatial Pattern | |

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

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

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

nncross | Nearest Neighbours Between Two Patterns | |

varblock | Estimate Variance of Summary Statistic by Subdivision | |

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

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

simplenet | Simple Example of Linear Network | |

crossdist | Pairwise distances | |

Poisson | Poisson Point Process Model | |

LennardJones | The Lennard-Jones Potential | |

dfbetas.ppm | Parameter influence measure | |

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

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

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

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

dirichlet | Dirichlet Tessellation of Point Pattern | |

pixelquad | Quadrature Scheme Based on Pixel Grid | |

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

hybrid.family | Hybrid Interaction Family | |

plot.tess | Plot a tessellation | |

imcov | Spatial Covariance of a Pixel Image | |

bdist.points | Distance to Boundary of Window | |

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

rMaternII | Simulate Matern Model II | |

perimeter | Perimeter Length of Window | |

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

ord.family | Ord Interaction Process Family | |

border | Border Region of a Window | |

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

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

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

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

shapley | Galaxies in the Shapley Supercluster | |

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

smooth.fv | Apply Smoothing to Function Values | |

lengths.psp | Lengths of Line Segments | |

rMosaicSet | Mosaic Random Set | |

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

levelset | Level Set of a Pixel Image | |

diameter | Diameter of an Object | |

Extract.fv | Extract Subset of Function Values | |

Fest | Estimate the empty space function F | |

rpoint | Generate N Random Points | |

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

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

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

areaLoss | Difference of Disc Areas | |

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

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

chorley | Chorley-Ribble Cancer Data | |

markcorr | Mark Correlation Function | |

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

profilepl | Profile Maximum Pseudolikelihood | |

rNeymanScott | Simulate Neyman-Scott Process | |

rpoispp | Generate Poisson Point Pattern | |

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

rgbim | Create Colour-Valued Pixel Image | |

tiles | Extract List of Tiles in a Tessellation | |

spatstat-package | The Spatstat Package | |

pairdist | Pairwise distances | |

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

connected | Connected components of an image or window | |

slrm | Spatial Logistic Regression | |

pool.envelope | Pool Data from Several Envelopes | |

stieltjes | Compute Integral of Function Against Cumulative Distribution | |

corners | Corners of a rectangle | |

append.psp | Combine Two Line Segment Patterns | |

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

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

distmap | Distance Map | |

im.object | Class of Images | |

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

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

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

clarkevans.test | Clark and Evans Test | |

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

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

rpoisline | Generate Poisson Random Line Process | |

as.rectangle | Window Frame | |

as.tess | Convert Data To Tessellation | |

lpp | Create Point Pattern on Linear Network | |

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

fv.object | Function Value Table | |

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

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

angles.psp | Orientation Angles of Line Segments | |

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

clickpoly | Interactively Define a Polygon | |

print.quad | Print a Quadrature Scheme | |

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

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

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

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

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

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

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

is.rectangle | Determine Type of Window | |

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

discpartarea | Area of Part of Disc | |

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

finpines | Pine saplings in Finland. | |

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

edges2triangles | List Triangles in a Graph | |

compareFit | Residual Diagnostics for Multiple Fitted Models | |

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

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

envelope | Simulation Envelopes of Summary Function | |

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

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

eval.fv | Evaluate Expression Involving Functions | |

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

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

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

disc | Circular Window | |

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

endpoints.psp | Endpoints of Line Segment Pattern | |

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

rmpoispp | Generate Multitype Poisson Point Pattern | |

Geyer | Geyer's Saturation Point Process Model | |

rpoislinetess | Poisson Line Tessellation | |

Kest.fft | K-function using FFT | |

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

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

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

Kmodel | K function of a model | |

hyperframe | Hyper Data Frame | |

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

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

persp.im | Perspective Plot of Pixel Image | |

gorillas | Gorilla Nesting Sites | |

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

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

harmonise.im | Make Pixel Images Compatible | |

fv | Create a Function Value Table | |

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

unmark | Remove Marks | |

pairdist.default | Pairwise distances | |

kppm | Fit Cluster or Cox Point Process Model | |

pairwise.family | Pairwise Interaction Process Family | |

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

incircle | Find Largest Circle Inside Window | |

rshift | Random Shift | |

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

linearK | Linear K Function | |

ants | Harkness-Isham ants' nests data | |

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

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

inforder.family | Infinite Order Interaction Family | |

localKinhom | Inhomogeneous Neighbourhood Density Function | |

plot.layered | Layered Plot | |

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

area.owin | Area of a Window | |

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

linnet | Create a Linear Network | |

localpcf | Local pair correlation function | |

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

rmpoint | Generate N Random Multitype Points | |

marks | Marks of a Point Pattern | |

integral.im | Integral of a Pixel Image | |

lohboot | Bootstrap Confidence Bands for Summary Function | |

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

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

localK | Neighbourhood density function | |

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

spatstat.options | Internal Options in Spatstat Package | |

linim | Create Pixel Image on Linear Network | |

colourmap | Colour Lookup Tables | |

clmfires | Castilla-La Mancha Forest Fires | |

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

logLik.slrm | Loglikelihood of Spatial Logistic Regression | |

owin | Create a Window | |

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

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

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

rStrauss | Perfect Simulation of the Strauss Process | |

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

unitname | Name for Unit of Length | |

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

intensity | Intensity of a Dataset or a Model | |

unnormdensity | Weighted kernel smoother | |

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

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

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

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

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

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

ponderosa | Ponderosa Pine Tree Point Pattern | |

paracou | Kimboto trees at Paracou, French Guiana | |

zapsmall.im | Rounding of Pixel Values | |

pairdist.psp | Pairwise distances between line segments | |

ppx | Multidimensional Space-Time Point Pattern | |

pairdist.ppx | Pairwise Distances in Any Dimensions | |

dilated.areas | Areas of Morphological Dilations | |

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

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

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

delaunay | Delaunay Triangulation of Point Pattern | |

pool | Pool Data | |

nnwhich.ppx | Nearest Neighbours in Any Dimensions | |

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

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

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

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

eval.fasp | Evaluate Expression Involving Function Arrays | |

pixellate | Convert Spatial Object to Pixel Image | |

plot.listof | Plot a List of Things | |

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

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

gpc2owin | Convert Polygonal Region into Different Format | |

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

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

summary.quad | Summarizing a Quadrature Scheme | |

setcov | Set Covariance of a Window | |

rpoislpp | Poisson Point Process on a Linear Network | |

pp3 | Three Dimensional Point Pattern | |

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

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

Extract.quad | Subset of Quadrature Scheme | |

pppdist | Distance Between Two Point Patterns | |

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

ripras | Estimate window from points alone | |

quadrats | Divide Region into Quadrats | |

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

Finhom | Inhomogeneous Empty Space Function | |

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

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

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

rotate.psp | Rotate a Line Segment Pattern | |

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

volume | Volume of an Object | |

is.marked | Test Whether Marks Are Present | |

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

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

Tstat | Third order summary statistic | |

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

clusterset | Allard-Fraley Estimator of Cluster Feature | |

Fiksel | The Fiksel Interaction | |

distmap.owin | Distance Map of Window | |

linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |

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

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

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

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

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

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

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

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

reflect | Reflect In Origin | |

vertices | Vertices of a Window | |

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

reach | Interaction Distance of a Point Process | |

Saturated | Saturated Pairwise Interaction model | |

owin.object | Class owin | |

superimpose | Superimpose Several Geometric Patterns | |

flipxy | Exchange X and Y Coordinates | |

whist | Weighted Histogram | |

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

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

rknn | Theoretical Distribution of Nearest Neighbour Distance | |

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

anemones | Beadlet Anemones Data | |

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

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

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

nnfun | Nearest Neighbour Map as a Function | |

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

psp | Create a Line Segment Pattern | |

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

heather | Diggle's Heather Data | |

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

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

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

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

opening | Morphological Opening | |

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

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

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

contour.im | Contour plot of pixel image | |

convexhull.xy | Convex Hull of Points | |

quad.object | Class of Quadrature Schemes | |

rMaternI | Simulate Matern Model I | |

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

pppmatching | Create a Point Matching | |

rcell | Simulate Baddeley-Silverman Cell Process | |

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

diameter.owin | Diameter of a Window | |

gridweights | Compute Quadrature Weights Based on Grid Counts | |

rat | Ratio object | |

rSSI | Simulate Simple Sequential Inhibition | |

Jmulti | Marked J Function | |

spatstat-internal | Internal spatstat functions | |

letterR | Window in Shape of Letter R | |

runiflpp | Uniform Random Points on a Linear Network | |

murchison | Murchison gold deposits | |

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

Hybrid | Hybrid Interaction Point Process Model | |

Strauss | The Strauss Point Process Model | |

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

Triplets | The Triplet Point Process Model | |

funxy | Spatial Function Class | |

trim.rectangle | Cut margins from rectangle | |

clarkevans | Clark and Evans Aggregation Index | |

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

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

will.expand | Test Expansion Rule | |

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

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

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

as.owin | Convert Data To Class owin | |

plot.owin | Plot a Spatial Window | |

bdist.pixels | Distance to Boundary of Window | |

centroid.owin | Centroid of a window | |

bei | Tropical rain forest trees | |

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

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

bdist.tiles | Distance to Boundary of Window | |

boxx | Multi-Dimensional Box | |

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

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

eroded.areas | Areas of Morphological Erosions | |

rHardcore | Perfect Simulation of the Hardcore Process | |

layered | Create List of Plotting Layers | |

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

methods.linnet | Methods for Linear Networks | |

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

rotate.ppp | Rotate a Point Pattern | |

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

rshift.ppp | Randomly Shift a Point Pattern | |

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

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

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

Kscaled | Locally Scaled K-function | |

suffstat | Sufficient Statistic of Point Process Model | |

Linhom | L-function | |

ppp.object | Class of Point Patterns | |

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

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

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

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

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

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

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

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

progressreport | Print Progress Reports | |

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

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

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

lansing | Lansing Woods Point Pattern | |

contour.listof | Plot a List of Things | |

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

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

lut | Lookup Tables | |

Jinhom | Inhomogeneous J-function | |

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

nnwhich.pp3 | Nearest neighbours in three dimensions | |

scan.test | Spatial Scan Test | |

bind.fv | Combine Function Value Tables | |

spokes | Spokes pattern of dummy points | |

spatstat-deprecated | Deprecated spatstat functions | |

parres | Partial Residuals for Point Process Model | |

clickppp | Interactively Add Points | |

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

convexhull | Convex Hull | |

deltametric | Delta Metric | |

demopat | Artificial Data Point Pattern | |

rlabel | Random Re-Labelling of Point Pattern | |

plot.bermantest | Plot Result of Berman Test | |

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

envelope.envelope | Recompute Envelopes | |

plot.envelope | Plot a Simulation Envelope | |

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

pointsOnLines | Place Points Evenly Along Specified Lines | |

ewcdf | Weighted Empirical Cumulative Distribution Function | |

intensity.ppp | Empirical Intensity of Point Pattern | |

is.multitype | Test whether Object is Multitype | |

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

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

markvario | Mark Variogram | |

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

rotate | Rotate | |

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

Hest | Spherical Contact Distribution Function | |

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

nndist | Nearest neighbour distances | |

nztrees | New Zealand Trees Point Pattern | |

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

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

as.im | Convert to Pixel Image | |

pcfinhom | Inhomogeneous Pair Correlation Function | |

tess | Create a Tessellation | |

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

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

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

infline | Infinite Straight Lines | |

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

hamster | Aherne's hamster tumour data | |

Ldot.inhom | Inhomogeneous Multitype L Dot Function | |

eem | Exponential Energy Marks | |

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

pool.quadrattest | Pool Several Quadrat Tests | |

square | Square Window | |

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

methods.funxy | Methods for Spatial Functions | |

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

msr | Signed or Vector-Valued Measure | |

Kmeasure | Reduced Second Moment Measure | |

quadratcount | Quadrat counting for a point pattern | |

interp.im | Interpolate a Pixel Image | |

addvar | Added Variable Plot for Point Process Model | |

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

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

areaGain | Difference of Disc Areas | |

pairdist.pp3 | Pairwise distances in Three Dimensions | |

rmhexpand | Specify Simulation Window or Expansion Rule | |

pairdist.ppp | Pairwise distances | |

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

rotate.im | Rotate a Pixel Image | |

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

colourtools | Convert and Compare Colours in Different Formats | |

shift.owin | Apply Vector Translation To Window | |

rMosaicField | Mosaic Random Field | |

complement.owin | Take Complement of a Window | |

delaunay.distance | Distance on Delaunay Triangulation | |

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

plot.im | Plot a Pixel Image | |

urkiola | Urkiola Woods Point Pattern | |

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

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

dilation | Morphological Dilation | |

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

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

distfun | Distance Map as a Function | |

Ginhom | Inhomogeneous Nearest Neighbour Function | |

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

spruces | Spruces Point Pattern | |

distmap.ppp | Distance Map of Point Pattern | |

psp.object | Class of Line Segment Patterns | |

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

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

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

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

npoints | Number of Points in a Point Pattern | |

im | Create a Pixel Image Object | |

hyytiala | Scots pines and other trees at Hyytiala | |

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

rstrat | Simulate Stratified Random Point Pattern | |

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

linearpcf | Linear Pair Correlation Function | |

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

markcorrint | Mark Correlation Integral | |

rPoissonCluster | Simulate Poisson Cluster Process | |

scaletointerval | Rescale Data to Lie Between Specified Limits | |

mucosa | Cells in Gastric Mucosa | |

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

fryplot | Fry Plot of Point Pattern | |

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

plot.influence.ppm | Plot Influence Measure | |

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

plot.linnet | Plot a linear network | |

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

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

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

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

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

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

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

plot.fasp | Plot a Function Array | |

pppmatching.object | Class of Point Matchings | |

Gcom | Model Compensator of Nearest Neighbour Function | |

Gmulti | Marked Nearest Neighbour Distance Function | |

affine.owin | Apply Affine Transformation To Window | |

Jest | Estimate the J-function | |

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

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

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

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

eval.im | Evaluate Expression Involving Pixel Images | |

gridcentres | Rectangular grid of points | |

compatible | Test Whether Objects Are Compatible | |

nbfires | Point Patterns of New Brunswick Forest Fires | |

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

pcf | Pair Correlation Function | |

plot.leverage.ppm | Plot Leverage Function | |

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

project2segment | Move Point To Nearest Line | |

rLGCP | Simulate Log-Gaussian Cox Process | |

rhohat | Smoothing Estimate of Covariate Transformation | |

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

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

rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |

rsyst | Simulate systematic random point pattern | |

plot.ppp | plot a Spatial Point Pattern | |

sharpen | Data Sharpening of Point Pattern | |

shift | Apply Vector Translation | |

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

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

summary.owin | Summary of a Spatial Window | |

scanpp | Read Point Pattern From Data File | |

Hardcore | The Hard Core Point Process Model | |

DiggleGratton | Diggle-Gratton model | |

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

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

Gest | Nearest Neighbour Distance Function G | |

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

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

cells | Biological Cells Point Pattern | |

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

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

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

japanesepines | Japanese Pines Point Pattern | |

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

plot.fv | Plot Function Values | |

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

ppp | Create a Point Pattern | |

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

rescue.rectangle | Convert Window Back To Rectangle | |

box3 | Three-Dimensional Box | |

rjitter | Random Perturbation of a Point Pattern | |

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

runifpoint | Generate N Uniform Random Points | |

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

transect.im | Pixel Values Along a Transect | |

Extract.fasp | Extract Subset of Function Array | |

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

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

Gfox | Foxall's Distance Functions | |

LambertW | Lambert's W Function | |

Ord | Generic Ord Interaction model | |

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

amacrine | Hughes' Amacrine Cell Data | |

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

chicago | Chicago Street Crime Data | |

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

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

model.images | Compute Images of Constructed Covariates | |

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

pairs.im | Scatterplot Matrix for Pixel Images | |

plot.hyperframe | Plot Entries in a Hyperframe | |

plot.quad | plot a Spatial Quadrature Scheme | |

rMatClust | Simulate Matern Cluster Process | |

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

summary.im | Summarizing a Pixel Image | |

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

waka | Trees in Waka national park | |

rthin | Random Thinning | |

as.interact | Extract Interaction Structure | |

rGaussPoisson | Simulate Gauss-Poisson Process | |

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

copper | Berman-Huntington points and lines data | |

linearKinhom | Inhomogeneous Linear K Function | |

rThomas | Simulate Thomas Process | |

Iest | Estimate the I-function | |

Kinhom | Inhomogeneous K-function | |

Kres | Residual K Function | |

Pairwise | Generic Pairwise Interaction model | |

betacells | Beta Ganglion Cells in Cat Retina | |

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

circumradius | Circumradius and Diameter of a Linear Network | |

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

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

convolve.im | Convolution of Pixel Images | |

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

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

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

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

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

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

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

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

lurking | Lurking variable plot | |

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

nnclean | Nearest Neighbour Clutter Removal | |

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

plot.colourmap | Plot a Colour Map | |

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

pixellate.owin | Convert Window to Pixel Image | |

quantile.im | Sample Quantiles of Pixel Image | |

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

rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |

simdat | Simulated Point Pattern | |

swedishpines | Swedish Pines Point Pattern | |

triplet.family | Triplet Interaction Family | |

as.psp | Convert Data To Class psp | |

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

harmonic | Basis for Harmonic Functions | |

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

No Results! |

## Last month downloads

## Details

Date | 2012-12-23 |

License | GPL (>= 2) |

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

LazyData | true |

LazyLoad | true |

ByteCompile | true |

Packaged | 2012-12-23 10:49:06 UTC; adrian |

Repository | CRAN |

Date/Publication | 2012-12-23 13:15:36 |

depends | base (>= 2.14.0) , deldir (>= 0.0-21) , graphics , grDevices , mgcv , R (>= 2.14.0) , stats , utils |

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

Contributors | Rolf Turner, Adrian Baddeley |

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