# spatstat v1.42-2

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## Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests

Comprehensive open-source toolbox 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, space-time point patterns in any number of dimensions, and point patterns on a linear network.
Contains about 2000 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, tessellations, and linear networks.
Exploratory methods include quadrat counts, K-functions and their simulation envelopes, 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, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Diggle-Cressie-Loosmore-Ford, Dao-Genton) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov) are also supported.
Parametric models can be fitted to point pattern data using the functions ppm, kppm, slrm similar to glm. Types of models include Poisson, Gibbs, Cox and cluster point processes. Models may involve dependence on covariates, interpoint interaction, cluster formation and dependence on marks. Models are fitted by maximum likelihood, logistic regression, minimum contrast, and composite likelihood methods.
Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise, AIC). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots.

## Functions in spatstat

Name | Description | |

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

Extract.layered | Extract or Replace Subset of a Layered Object | |

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

BadGey | Hybrid Geyer Point Process Model | |

DiggleGratton | Diggle-Gratton model | |

Hybrid | Hybrid Interaction Point Process Model | |

Lcross.inhom | Inhomogeneous Cross Type L Function | |

Extract.influence.ppm | Extract Subset of Influence Object | |

Gres | Residual G Function | |

Extract.fv | Extract or Replace Subset of Function Values | |

Emark | Diagnostics for random marking | |

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

Extract.hyperframe | Extract or Replace Subset of Hyperframe | |

Hardcore | The Hard Core Point Process Model | |

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

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

Extract.owin | Extract Subset of Window | |

Iest | Estimate the I-function | |

HierStrauss | The Hierarchical Strauss Point Process Model | |

Concom | The Connected Component Process Model | |

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

Math.linim | S3 Group Generic Methods for Images on a Linear Network | |

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

Extract.linnet | Extract Subset of Linear Network | |

Extract.fasp | Extract Subset of Function Array | |

Gfox | Foxall's Distance Functions | |

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

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

Ginhom | Inhomogeneous Nearest Neighbour Function | |

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

Ldot.inhom | Inhomogeneous Multitype L Dot Function | |

anemones | Beadlet Anemones Data | |

Extract.leverage.ppm | Extract Subset of Leverage Object | |

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

Smoothfun.ppp | Smooth Interpolation of Marks as a Spatial Function | |

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

AreaInter | The Area Interaction Point Process Model | |

Fest | Estimate the Empty Space Function or its Hazard Rate | |

angles.psp | Orientation Angles of Line Segments | |

Kovesi | Colour Sequences with Uniform Perceptual Contrast | |

anova.mppm | ANOVA for Fitted Multiple Point Process Models | |

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

Kest | K-function | |

Extract.solist | Extract or Replace Subset of a List of Spatial Objest | |

Geyer | Geyer's Saturation Point Process Model | |

Jinhom | Inhomogeneous J-function | |

Gmulti | Marked Nearest Neighbour Distance Function | |

Gest | Nearest Neighbour Distance Function G | |

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

Frame | Extract or Change the Containing Rectangle of a Spatial Object | |

LennardJones | The Lennard-Jones Potential | |

Triplets | The Triplet Point Process Model | |

affine.lpp | Apply Geometrical Transformations to Point Pattern on a Linear Network | |

Lest | L-function | |

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

Softcore | The Soft Core Point Process Model | |

affine.owin | Apply Affine Transformation To Window | |

Pairwise | Generic Pairwise Interaction model | |

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

Gcom | Model Compensator of Nearest Neighbour Function | |

HierHard | The Hierarchical Hard Core Point Process Model | |

Math.im | S3 Group Generic methods for images | |

LambertW | Lambert's W Function | |

Tstat | Third order summary statistic | |

Kmodel.kppm | K Function or Pair Correlation Function of Cluster Model or Cox model | |

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

Finhom | Inhomogeneous Empty Space Function | |

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

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

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

Extract.quad | Subset of Quadrature Scheme | |

as.psp | Convert Data To Class psp | |

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

Poisson | Poisson Point Process Model | |

Kmeasure | Reduced Second Moment Measure | |

Kscaled | Locally Scaled K-function | |

Kcross.inhom | Inhomogeneous Cross K Function | |

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

Kinhom | Inhomogeneous K-function | |

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

cdf.test | Spatial Distribution Test for Point Pattern or Point Process Model | |

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

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

Kmark | Mark-Weighted K Function | |

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

boxx | Multi-Dimensional Box | |

Jest | Estimate the J-function | |

affine.linnet | Apply Geometrical Transformations to a Linear Network | |

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

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

Fiksel | The Fiksel Interaction | |

Extract.im | Extract Subset of Image | |

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

amacrine | Hughes' Amacrine Cell Data | |

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

Jmulti | Marked J Function | |

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

Kmulti | Marked K-Function | |

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

Kmodel.ppm | K Function or Pair Correlation Function of Gibbs Point Process model | |

Hest | Spherical Contact Distribution Function | |

Kcom | Model Compensator of K Function | |

HierStraussHard | The Hierarchical Strauss Hard Core Point Process Model | |

WindowOnly | Extract Window of Spatial Object | |

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

Ord | Generic Ord Interaction model | |

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

Strauss | The Strauss Point Process Model | |

Kest.fft | K-function using FFT | |

Kmodel | K Function or Pair Correlation Function of a Point Process Model | |

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

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

convexhull | Convex Hull | |

blur | Apply Gaussian Blur to a Pixel Image | |

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

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

as.layered | Convert Data To Layered Object | |

Ksector | Sector K-function | |

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

bdist.points | Distance to Boundary of Window | |

as.solist | Convert List of Two-Dimensional Spatial Objects | |

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

Kmulti.inhom | Inhomogeneous Marked K-Function | |

bramblecanes | Hutchings' Bramble Canes data | |

MultiStrauss | The Multitype Strauss Point Process Model | |

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

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

as.hyperframe | Convert Data to Hyperframe | |

as.lpp | Convert Data to a Point Pattern on a Linear Network | |

Linhom | L-function | |

as.im | Convert to Pixel Image | |

clarkevans.test | Clark and Evans Test | |

Window | Extract or Change the Window of a Spatial Object | |

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

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

as.fv | Convert Data To Class fv | |

coef.mppm | Coefficients of Point Process Model Fitted to Multiple Point Patterns | |

clarkevans | Clark and Evans Aggregation Index | |

affine | Apply Affine Transformation | |

MultiHard | The Multitype Hard Core Point Process Model | |

affine.tess | Apply Geometrical Transformation To Tessellation | |

anylist | List of Objects | |

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

as.ppm | Extract Fitted Point Process Model | |

connected | Connected components | |

area.owin | Area of a Window | |

as.function.im | Convert Pixel Image to Function of Coordinates | |

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

ants | Harkness-Isham ants' nests data | |

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

clickpoly | Interactively Define a Polygon | |

clusterradius | Compute or Extract Effective Range of Cluster Kernel | |

as.linnet.psp | Convert Line Segment Pattern to Linear Network | |

Saturated | Saturated Pairwise Interaction model | |

compatible | Test Whether Objects Are Compatible | |

bw.ppl | Likelihood Cross Validation Bandwidth Selection for Kernel Density | |

chorley | Chorley-Ribble Cancer Data | |

Smooth.fv | Apply Smoothing to Function Values | |

areaGain | Difference of Disc Areas | |

Smooth | Spatial smoothing of data | |

Kres | Residual K Function | |

bind.fv | Combine Function Value Tables | |

branchlabelfun | Tree Branch Membership Labelling Function | |

circumradius | Circumradius of a Window | |

closepairs.pp3 | Close Pairs of Points in 3 Dimensions | |

begins | Check Start of Character String | |

OrdThresh | Ord's Interaction model | |

circdensity | Density Estimation for Circular Data | |

clusterset | Allard-Fraley Estimator of Cluster Feature | |

corners | Corners of a rectangle | |

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

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

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

colourmap | Colour Lookup Tables | |

beachcolours | Create Colour Scheme for a Range of Numbers | |

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

bdspots | Breakdown Spots in Microelectronic Materials | |

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

convexhull.xy | Convex Hull of Points | |

append.psp | Combine Two Line Segment Patterns | |

clusterfield | Field of clusters | |

as.ppp | Convert Data To Class ppp | |

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

as.data.frame.owin | Convert Window to Data Frame | |

berman.test | Berman's Tests for Point Process Model | |

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

addvar | Added Variable Plot for Point Process Model | |

contour.imlist | Array of Contour Plots | |

add.texture | Fill Plot With Texture | |

closing | Morphological Closing | |

as.linnet.linim | Extract Linear Network from Data on a Linear Network | |

as.rectangle | Window Frame | |

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

colourtools | Convert and Compare Colours in Different Formats | |

as.tess | Convert Data To Tessellation | |

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

clickjoin | Interactively join vertices on a plot | |

beginner | Print Introduction For Beginners | |

bdist.pixels | Distance to Boundary of Window | |

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

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

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

bei | Tropical rain forest trees | |

bronzefilter | Bronze gradient filter data | |

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

chicago | Chicago Street Crime Data | |

clickdist | Interactively Measure Distance | |

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

boundingbox | Bounding Box of a Window, Image, or Point Pattern | |

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

clusterkernel | Extract Cluster Offspring Kernel | |

contour.im | Contour plot of pixel image | |

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

copyExampleFiles | Copy Data Files for Example | |

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

as.owin | Convert Data To Class owin | |

border | Border Region of a Window | |

clickbox | Interactively Define a Rectangle | |

cells | Biological Cells Point Pattern | |

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

clmfires | Castilla-La Mancha Forest Fires | |

clickppp | Interactively Add Points | |

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

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

complement.owin | Take Complement of a Window | |

compareFit | Residual Diagnostics for Multiple Fitted Models | |

betacells | Beta Ganglion Cells in Cat Retina | |

closepairs | Close Pairs of Points | |

bdist.tiles | Distance to Boundary of Window | |

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

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

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

clusterfit | Fit Cluster or Cox Point Process Model via Minimum Contrast | |

box3 | Three-Dimensional Box | |

connected.ppp | Connected components of a point pattern | |

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

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

concatxy | Concatenate x,y Coordinate Vectors | |

cdf.test.mppm | Spatial Distribution Test for Multiple Point Process Model | |

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

convolve.im | Convolution of Pixel Images | |

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

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

areaLoss | Difference of Disc Areas | |

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

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

as.interact | Extract Interaction Structure | |

auc | Area Under ROC Curve | |

centroid.owin | Centroid of a window | |

crossdist | Pairwise distances | |

copper | Berman-Huntington points and lines data | |

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

deriv.fv | Calculate Derivative of Function Values | |

disc | Circular Window | |

edges2triangles | List Triangles in a Graph | |

delaunayDistance | Distance on Delaunay Triangulation | |

edit.hyperframe | Invoke Text Editor on Hyperframe | |

domain | Extract the Domain of any Spatial Object | |

eval.im | Evaluate Expression Involving Pixel Images | |

distcdf | Distribution Function of Interpoint Distance | |

flipxy | Exchange X and Y Coordinates | |

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

ellipse | Elliptical Window. | |

gridweights | Compute Quadrature Weights Based on Grid Counts | |

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

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

fitted.lppm | Fitted Intensity for Point Process on Linear Network | |

is.multitype | Test whether Object is Multitype | |

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

finpines | Pine saplings in Finland. | |

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

fitted.mppm | Fitted Conditional Intensity for Multiple Point Process Model | |

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

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

expand.owin | Apply Expansion Rule | |

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

dclf.progress | Progress Plot of Test of Spatial Pattern | |

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

dilation | Morphological Dilation | |

is.rectangle | Determine Type of Window | |

lohboot | Bootstrap Confidence Bands for Summary Function | |

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

demopat | Artificial Data Point Pattern | |

demohyper | Demonstration Example of Hyperframe of Spatial Data | |

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

fv.object | Function Value Table | |

dfbetas.ppm | Parameter influence measure | |

flu | Influenza Virus Proteins | |

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

dendrite | Dendritic Spines Data | |

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

infline | Infinite Straight Lines | |

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

distmap | Distance Map | |

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

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

grow.rectangle | Add margins to rectangle | |

deletebranch | Delete or Extract a Branch of a Tree | |

im.object | Class of Images | |

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

linfun | Function on a Linear Network | |

delaunay | Delaunay Triangulation of Point Pattern | |

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

distfun | Distance Map as a Function | |

ewcdf | Weighted Empirical Cumulative Distribution Function | |

dilated.areas | Areas of Morphological Dilations | |

localK | Neighbourhood density function | |

dirichletWeights | Compute Quadrature Weights Based on Dirichlet Tessellation | |

is.lpp | Test Whether An Object Is A Point Pattern on a Linear Network | |

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

edge.Ripley | Ripley's Isotropic Edge Correction | |

hierpair.family | Hierarchical Pairwise Interaction Process Family | |

dirichletVertices | Vertices and Edges of Dirichlet Tessellation | |

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

diameter.linnet | Circumradius and Diameter of a Linear Network | |

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

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

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

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

linearKcross | Multitype K Function (Cross-type) for Linear Point Pattern | |

edges2vees | List Dihedral Triples in a Graph | |

envelope.envelope | Recompute Envelopes | |

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

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

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

delaunayNetwork | Linear Network of Delaunay Triangulation or Dirichlet Tessellation | |

fasp.object | Function Arrays for Spatial Patterns | |

harmonise | Make Objects Compatible | |

localpcf | Local pair correlation function | |

hextess | Hexagonal Grid or Tessellation | |

diameter | Diameter of an Object | |

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

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

increment.fv | Increments of a Function | |

edges | Extract Boundary Edges of a Window. | |

dmixpois | Mixed Poisson Distribution | |

distmap.owin | Distance Map of Window | |

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

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

eval.linim | Evaluate Expression Involving Pixel Images on Linear Network | |

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

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

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

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

discpartarea | Area of Part of Disc | |

eval.fasp | Evaluate Expression Involving Function Arrays | |

erosion | Morphological Erosion | |

lut | Lookup Tables | |

eem | Exponential Energy Marks | |

endpoints.psp | Endpoints of Line Segment Pattern | |

im | Create a Pixel Image Object | |

deltametric | Delta Metric | |

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

funxy | Spatial Function Class | |

eval.fv | Evaluate Expression Involving Functions | |

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

logLik.slrm | Loglikelihood of Spatial Logistic Regression | |

fryplot | Fry Plot of Point Pattern | |

harmonise.fv | Make Function Tables Compatible | |

inforder.family | Infinite Order Interaction Family | |

envelope | Simulation Envelopes of Summary Function | |

linnet | Create a Linear Network | |

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

harmonise.im | Make Pixel Images Compatible | |

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

overlap.owin | Compute Area of Overlap | |

markcorr | Mark Correlation Function | |

marks | Marks of a Point Pattern | |

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

distmap.ppp | Distance Map of Point Pattern | |

markvario | Mark Variogram | |

methods.units | Methods for Units | |

fardist | Farthest Distance to Boundary of Window | |

linearKinhom | Inhomogeneous Linear K Function | |

fvnames | Abbreviations for Groups of Columns in Function Value Table | |

pairdist | Pairwise distances | |

hamster | Aherne's hamster tumour data | |

nnmark | Mark of Nearest Neighbour | |

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

layered | Create List of Plotting Layers | |

pairdist.pp3 | Pairwise distances in Three Dimensions | |

msr | Signed or Vector-Valued Measure | |

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

linearmarkconnect | Mark Connection Function for Multitype Point Pattern on Linear Network | |

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

nndist | Nearest neighbour distances | |

gorillas | Gorilla Nesting Sites | |

incircle | Find Largest Circle Inside Window | |

imcov | Spatial Covariance of a Pixel Image | |

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

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

paracou | Kimboto trees at Paracou, French Guiana | |

nnfun.lpp | Nearest Neighbour Map on Linear Network | |

plot.solist | Plot a List of Spatial Objects | |

gordon | People in Gordon Square | |

improve.kppm | Improve Intensity Estimate of Fitted Cluster Point Process Model | |

is.dppm | Recognise Fitted Determinantal Point Process Models | |

hyytiala | Scots pines and other trees at Hyytiala | |

hyperframe | Hyper Data Frame | |

iplot | Point and Click Interface for Displaying Spatial Data | |

gauss.hermite | Gauss-Hermite Quadrature Approximation to Expectation for Normal Distribution | |

letterR | Window in Shape of Letter R | |

objsurf | Objective Function Surface | |

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

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

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

hybrid.family | Hybrid Interaction Family | |

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

plot.tess | Plot a tessellation | |

nnwhich.pp3 | Nearest neighbours in three dimensions | |

harmonic | Basis for Harmonic Functions | |

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

intersect.tess | Intersection of Two Tessellations | |

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

layout.boxes | Generate a Row or Column Arrangement of Rectangles. | |

im.apply | Apply Function Pixelwise to List of Images | |

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

japanesepines | Japanese Pines Point Pattern | |

is.marked | Test Whether Marks Are Present | |

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

intensity | Intensity of a Dataset or a Model | |

pairs.im | Scatterplot Matrix for Pixel Images | |

methods.objsurf | Methods for Objective Function Surfaces | |

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

fv | Create a Function Value Table | |

nbfires | Point Patterns of New Brunswick Forest Fires | |

ippm | Fit Point Process Model Involving Irregular Trend Parameters | |

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

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

intensity.lpp | Empirical Intensity of Point Pattern on Linear Network | |

linearpcfdot | Multitype Pair Correlation Function (Dot-type) for Linear Point Pattern | |

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

intensity.quadratcount | Intensity Estimates Using Quadrat Counts | |

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

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

dirichlet | Dirichlet Tessellation of Point Pattern | |

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

intensity.ppp | Empirical Intensity of Point Pattern | |

distfun.lpp | Distance Map on Linear Network | |

discs | Union of Discs | |

invoke.symbolmap | Plot Data Using Graphics Symbol Map | |

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

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

heather | Diggle's Heather Data | |

longleaf | Longleaf Pines Point Pattern | |

pixelquad | Quadrature Scheme Based on Pixel Grid | |

linearpcf | Linear Pair Correlation Function | |

linearmarkequal | Mark Connection Function for Multitype Point Pattern on Linear Network | |

integral.msr | Integral of a Measure | |

diameter.owin | Diameter of a Window | |

interp.colourmap | Interpolate smoothly between specified colours | |

plot.mppm | plot a Fitted Multiple Point Process Model | |

nestsplit | Nested Split | |

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

methods.linfun | Methods for Functions on Linear Network | |

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

mppm | Fit Point Process Model to Several Point Patterns | |

interp.im | Interpolate a Pixel Image | |

integral.im | Integral of a Pixel Image | |

rMaternI | Simulate Matern Model I | |

linearpcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Dot-type) for Linear Point Pattern | |

linearKdot | Multitype K Function (Dot-type) for Linear Point Pattern | |

localKinhom | Inhomogeneous Neighbourhood Density Function | |

linearpcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-type) for Linear Point Pattern | |

pairwise.family | Pairwise Interaction Process Family | |

nnorient | Nearest Neighbour Orientation Distribution | |

plot.imlist | Plot a List of Images | |

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

dirichletAreas | Compute Areas of Tiles in Dirichlet Tessellation | |

plot.lpp | Plot Point Pattern on Linear Network | |

lengths.psp | Lengths of Line Segments | |

pyramidal | Pyramidal Neurons in Cingulate Cortex | |

methods.linnet | Methods for Linear Networks | |

linearpcfcross | Multitype Pair Correlation Function (Cross-type) for Linear Point Pattern | |

pairdist.psp | Pairwise distances between line segments | |

levelset | Level Set of a Pixel Image | |

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

plot.layered | Layered Plot | |

gridcentres | Rectangular grid of points | |

kppm | Fit Cluster or Cox Point Process Model | |

methods.fii | Methods for Fitted Interactions | |

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

npfun | Dummy Function Returns Number of Points | |

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

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

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

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

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

linearKcross.inhom | Inhomogeneous multitype K Function (Cross-type) for Linear Point Pattern | |

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

quadratcount | Quadrat counting for a point pattern | |

perimeter | Perimeter Length of Window | |

layerplotargs | Extract or Replace the Plot Arguments of a Layered Object | |

plot.leverage.ppm | Plot Leverage Function | |

maxnndist | Compute Minimum or Maximum Nearest-Neighbour Distance | |

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

methods.funxy | Methods for Spatial Functions | |

pairdist.ppx | Pairwise Distances in Any Dimensions | |

rpoislinetess | Poisson Line Tessellation | |

nnclean | Nearest Neighbour Clutter Removal | |

pixelcentres | Extract Pixel Centres as Point Pattern | |

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

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

rPoissonCluster | Simulate Poisson Cluster Process | |

perspPoints | Draw Points or Lines on a Surface Viewed in Perspective | |

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

ppp | Create a Point Pattern | |

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

plot.envelope | Plot a Simulation Envelope | |

nnmap | K-th Nearest Point Map | |

midpoints.psp | Midpoints of Line Segment Pattern | |

plot.anylist | Plot a List of Things | |

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

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

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

nnwhich.lpp | Identify Nearest Neighbours on a Linear Network | |

nnwhich.ppx | Nearest Neighbours in Any Dimensions | |

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

range.fv | Range of Function Values | |

linim | Create Pixel Image on Linear Network | |

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

pixellate | Convert Spatial Object to Pixel Image | |

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

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

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

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

pcfinhom | Inhomogeneous Pair Correlation Function | |

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

plot.colourmap | Plot a Colour Map | |

nearestsegment | Find Line Segment Nearest to Each Point | |

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

nncross | Nearest Neighbours Between Two Patterns | |

quadrats | Divide Region into Quadrats | |

plot.onearrow | Plot an Arrow | |

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

plot.ppp | plot a Spatial Point Pattern | |

murchison | Murchison gold deposits | |

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

lansing | Lansing Woods Point Pattern | |

runiflpp | Uniform Random Points on a Linear Network | |

vesicles | Vesicles Data | |

ppm.ppp | Fit Point Process Model to Point Pattern Data | |

methods.linim | Methods for Images on a Linear Network | |

plot.owin | Plot a Spatial Window | |

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

padimage | Pad the Border of a Pixel Image | |

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

linearK | Linear K Function | |

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

marks.tess | Marks of a Tessellation | |

nnwhich | Nearest neighbour | |

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

plot.pp3 | Plot a Three-Dimensional Point Pattern | |

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

plot.fv | Plot Function Values | |

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

reach | Interaction Distance of a Point Process | |

pcfmulti | Marked pair correlation function | |

plot.texturemap | Plot a Texture Map | |

nztrees | New Zealand Trees Point Pattern | |

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

integral.linim | Integral on a Linear Network | |

ripras | Estimate window from points alone | |

plot.influence.ppm | Plot Influence Measure | |

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

residuals.mppm | Residuals for Point Process Model Fitted to Multiple Point Patterns | |

pool.fv | Pool Several Functions | |

pcf | Pair Correlation Function | |

matchingdist | Distance for a Point Pattern Matching | |

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

rotate.owin | Rotate a Window | |

panel.contour | Panel Plots using Colour Image or Contour Lines | |

rknn | Theoretical Distribution of Nearest Neighbour Distance | |

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

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

ppm | Fit Point Process Model to Data | |

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

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

parameters | Extract Model Parameters in Understandable Form | |

project2set | Find Nearest Point in a Region | |

rMaternII | Simulate Matern Model II | |

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

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

scaletointerval | Rescale Data to Lie Between Specified Limits | |

rThomas | Simulate Thomas Process | |

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

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

plot.quadratcount | Plot Quadrat Counts | |

owin | Create a Window | |

project2segment | Move Point To Nearest Line | |

rmpoispp | Generate Multitype Poisson Point Pattern | |

pixellate.owin | Convert Window to Pixel Image | |

spokes | Spokes pattern of dummy points | |

rGaussPoisson | Simulate Gauss-Poisson Process | |

plot.bermantest | Plot Result of Berman Test | |

plot.scan.test | Plot Result of Scan Test | |

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

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

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

rSSI | Simulate Simple Sequential Inhibition | |

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

npoints | Number of Points in a Point Pattern | |

periodify | Make Periodic Copies of a Spatial Pattern | |

miplot | Morisita Index Plot | |

plot.linnet | Plot a linear network | |

linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |

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

rounding | Detect Numerical Rounding | |

whist | Weighted Histogram | |

scanpp | Read Point Pattern From Data File | |

rHardcore | Perfect Simulation of the Hardcore Process | |

rpoispp | Generate Poisson Point Pattern | |

rstrat | Simulate Stratified Random Point Pattern | |

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

nndensity.ppp | Estimate Intensity of Point Pattern Using Nearest Neighbour Distances | |

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

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

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

plot.lppm | Plot a Fitted Point Process Model on a Linear Network | |

plot.fasp | Plot a Function Array | |

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

sharpen | Data Sharpening of Point Pattern | |

plot.quad | Plot a Spatial Quadrature Scheme | |

pool.envelope | Pool Data from Several Envelopes | |

plot.yardstick | Plot a Yardstick or Scale Bar | |

rhohat | Smoothing Estimate of Covariate Transformation | |

logLik.kppm | Log Likelihood and AIC for Fitted Cox or Cluster Point Process Model | |

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

pool.anylist | Pool Data from a List of Objects | |

slrm | Spatial Logistic Regression | |

simdat | Simulated Point Pattern | |

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

sumouter | Compute Quadratic Forms | |

unmark | Remove Marks | |

pointsOnLines | Place Points Evenly Along Specified Lines | |

quad.object | Class of Quadrature Schemes | |

plot.hyperframe | Plot Entries in a Hyperframe | |

psp.object | Class of Line Segment Patterns | |

pool.quadrattest | Pool Several Quadrat Tests | |

plot.listof | Plot a List of Things | |

predict.mppm | Prediction for Fitted Multiple Point Process Model | |

spiders | Spider Webs on Mortar Lines of a Brick Wall | |

rpoisline | Generate Poisson Random Line Process | |

rMatClust | Simulate Matern Cluster Process | |

plot.quadrattest | Display the result of a quadrat counting test. | |

quantile.ewcdf | Quantiles of Weighted Empirical Cumulative Distribution Function | |

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

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

mucosa | Cells in Gastric Mucosa | |

selfcut.psp | Cut Line Segments Where They Intersect | |

persp.im | Perspective Plot of Pixel Image | |

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

ppx | Multidimensional Space-Time Point Pattern | |

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

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

reflect | Reflect In Origin | |

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

waka | Trees in Waka national park | |

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

rLGCP | Simulate Log-Gaussian Cox Process | |

nnfun | Nearest Neighbour Index Map as a Function | |

model.images | Compute Images of Constructed Covariates | |

rescue.rectangle | Convert Window Back To Rectangle | |

rshift.ppp | Randomly Shift a Point Pattern | |

owin.object | Class owin | |

spatstat-package | The Spatstat Package | |

pool | Pool Data | |

unnormdensity | Weighted kernel smoother | |

shift.owin | Apply Vector Translation To Window | |

subset.hyperframe | Subset of Hyperframe Satisfying A Condition | |

sessionLibs | Print Names and Version Numbers of Libraries Loaded | |

rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |

quantess | Quantile Tessellation | |

psp | Create a Line Segment Pattern | |

pppmatching | Create a Point Matching | |

tiles | Extract List of Tiles in a Tessellation | |

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

lurking | Lurking variable plot | |

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

nndist.lpp | Nearest neighbour distances on a linear network | |

rMosaicField | Mosaic Random Field | |

treebranchlabels | Label Vertices of a Tree by Branch Membership | |

rotate.ppp | Rotate a Point Pattern | |

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

nncross.lpp | Nearest Neighbours on a Linear Network | |

simba | Simulated data from a two-group experiment with replication within each group. | |

subfits | Extract List of Individual Point Process Models | |

harmonise.owin | Make Windows Compatible | |

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

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

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

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

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

relrisk | Estimate of Spatially-Varying Relative Risk | |

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

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

reload.or.compute | Compute Unless Previously Saved | |

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

rlabel | Random Re-Labelling of Point Pattern | |

nncross.pp3 | Nearest Neighbours Between Two Patterns in 3D | |

spatstat.options | Internal Options in Spatstat Package | |

ppp.object | Class of Point Patterns | |

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

progressreport | Print Progress Reports | |

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

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

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

tweak.colourmap | Change Colour Values in a Colour Map | |

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

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

rpoint | Generate N Random Points | |

segregation.test | Test of Spatial Segregation of Types | |

run.simplepanel | Run Point-and-Click Interface | |

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

pairdist.default | Pairwise distances | |

timed | Record the Computation Time | |

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

studpermu.test | Studentised Permutation Test | |

rQuasi | Generate Quasirandom Point Pattern in Given Window | |

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

profilepl | Profile Maximum Pseudolikelihood or AIC | |

unitname | Name for Unit of Length | |

rcell | Simulate Baddeley-Silverman Cell Process | |

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

round.ppp | Apply Numerical Rounding to Spatial Coordinates | |

transect.im | Pixel Values Along a Transect | |

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

relevel.im | Reorder Levels of a Factor-Valued Image or Pattern | |

summary.quad | Summarizing a Quadrature Scheme | |

setcov | Set Covariance of a Window | |

residuals.kppm | Residuals for Fitted Cox or Cluster Point Process Model | |

rthin | Random Thinning | |

roc | Receiver Operating Characteristic | |

rescale | Convert dataset to another unit of length | |

parres | Partial Residuals for Point Process Model | |

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

rmhexpand | Specify Simulation Window or Expansion Rule | |

pp3 | Three Dimensional Point Pattern | |

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

moribund | Outdated Functions | |

rStrauss | Perfect Simulation of the Strauss Process | |

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

methods.layered | Methods for Layered Objects | |

urkiola | Urkiola Woods Point Pattern | |

summary.kppm | Summarizing a Fitted Cox or Cluster Point Process Model | |

runifpoint | Generate N Uniform Random Points | |

solapply | Apply a Function Over a List and Obtain a List of Objects | |

rNeymanScott | Simulate Neyman-Scott Process | |

shift | Apply Vector Translation | |

subset.ppp | Subset of Point Pattern Satisfying A Condition | |

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

triangulate.owin | Decompose Window into Triangles | |

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

spatialcdf | Spatial Cumulative Distribution Function | |

spruces | Spruces Point Pattern | |

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

ponderosa | Ponderosa Pine Tree Point Pattern | |

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

summary.im | Summarizing a Pixel Image | |

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

ord.family | Ord Interaction Process Family | |

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

spatstat-internal | Internal spatstat functions | |

swedishpines | Swedish Pines Point Pattern | |

summary.owin | Summary of a Spatial Window | |

sporophores | Sporophores Data | |

update.symbolmap | Update a Graphics Symbol Map. | |

rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |

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

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

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

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

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

quasirandom | Quasirandom Patterns | |

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

rose | Rose Diagram | |

rotate.psp | Rotate a Line Segment Pattern | |

plot.cdftest | Plot a Spatial Distribution Test | |

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

scan.test | Spatial Scan Test | |

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

rotmean | Rotational Average of a Pixel Image | |

simplenet | Simple Example of Linear Network | |

superimpose | Superimpose Several Geometric Patterns | |

mincontrast | Method of Minimum Contrast | |

markconnect | Mark Connection Function | |

print.quad | Print a Quadrature Scheme | |

pairdist.ppp | Pairwise distances | |

rotate | Rotate | |

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

treeprune | Prune Tree to Given Level | |

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

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

triplet.family | Triplet Interaction Family | |

rpoislpp | Poisson Point Process on a Linear Network | |

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

rjitter | Random Perturbation of a Point Pattern | |

rshift | Random Shift | |

pppmatching.object | Class of Point Matchings | |

rnoise | Random Pixel Noise | |

shapley | Galaxies in the Shapley Supercluster | |

varblock | Estimate Variance of Summary Statistic by Subdivision | |

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

spatstat-deprecated | Deprecated spatstat functions | |

rsyst | Simulate systematic random point pattern | |

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

plot.symbolmap | Plot a Graphics Symbol Map | |

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

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

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

waterstriders | Waterstriders data. Three independent replications of a point pattern formed by insects. | |

symbolmap | Graphics Symbol Map | |

with.msr | Evaluate Expression Involving Components of a Measure | |

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

lpp | Create Point Pattern on Linear Network | |

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

volume | Volume of an Object | |

rmpoint | Generate N Random Multitype Points | |

rMosaicSet | Mosaic Random Set | |

density.lpp | Kernel Estimate of Intensity on a Linear Network | |

quadscheme.logi | Generate a Logistic Regression Quadrature Scheme from a Point Pattern | |

hopskel | Hopkins-Skellam Test | |

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

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

pairorient | Point Pair Orientation Distribution | |

plot.im | Plot a Pixel Image | |

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

scalardilate | Apply Scalar Dilation | |

yardstick | Text, Arrow or Scale Bar in a Diagram | |

rgbim | Create Colour-Valued Pixel Image | |

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

edit.ppp | Invoke Text Editor on Spatial Data | |

foo | Foo is Not a Real Name | |

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

solist | List of Two-Dimensional Spatial Objects | |

plot.textstring | Plot a Text String | |

pppdist | Distance Between Two Point Patterns | |

scanLRTS | Likelihood Ratio Test Statistic for Scan Test | |

square | Square Window | |

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

rat | Ratio object | |

split.hyperframe | Divide Hyperframe Into Subsets and Reassemble | |

eroded.areas | Areas of Morphological Erosions | |

stienen | Stienen Diagram | |

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

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

stieltjes | Compute Integral of Function Against Cumulative Distribution | |

superimpose.lpp | Superimpose Several Point Patterns on Linear Network | |

summary.solist | Summary of a List of Spatial Objects | |

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

simulate.lppm | Simulate a Fitted Point Process Model on a Linear Network | |

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

stratrand | Stratified random point pattern | |

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

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

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

tess | Create a Tessellation | |

suffstat | Sufficient Statistic of Point Process Model | |

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

rcellnumber | Generate Random Numbers of Points for Cell Process | |

trim.rectangle | Cut margins from rectangle | |

will.expand | Test Expansion Rule | |

relrisk.ppm | Parametric Estimate of Spatially-Varying Relative Risk | |

vertices | Vertices of a Window | |

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

tilenames | Names of Tiles in a Tessellation | |

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

quantile.im | Sample Quantiles of Pixel Image | |

zapsmall.im | Rounding of Pixel Values | |

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

quadrat.test.mppm | Chi-Squared Test for Multiple Point Process Model Based on Quadrat Counts | |

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

simplepanel | Simple Point-and-Click Interface Panels | |

texturemap | Texture Map | |

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

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

textureplot | Plot Image or Tessellation Using Texture Fill | |

rotate.im | Rotate a Pixel Image | |

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

transmat | Convert Pixel Array Between Different Conventions | |

edge.Trans | Translation Edge Correction | |

opening | Morphological Opening | |

vcov.mppm | Calculate Variance-Covariance Matrix for Fitted Multiple Point Process Model | |

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

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

mergeLevels | Merge Levels of a Factor | |

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

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

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

linearKdot.inhom | Inhomogeneous multitype K Function (Dot-type) for Linear Point Pattern | |

No Results! |

## Last month downloads

## Details

Nickname | Barking at Balloons |

Date | 2015-06-28 |

License | GPL (>= 2) |

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

LazyData | true |

NeedsCompilation | yes |

ByteCompile | true |

Packaged | 2015-06-28 16:25:57 UTC; adrian |

Repository | CRAN |

Date/Publication | 2015-06-29 07:38:54 |

imports | abind , deldir (>= 0.0-21) , goftest , Matrix , mgcv , polyclip (>= 1.3-0) , tensor |

depends | base (>= 3.2.0) , graphics , grDevices , methods , R (>= 3.2.0) , stats , utils |

suggests | gsl , locfit , maptools , RandomFields (>= 3.0.0) , rpanel , sm , spatial , tkrplot |

Contributors | Rolf Turner, Adrian Baddeley, Ege Rubak |

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