# spatstat v1.63-0

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

Comprehensive open-source toolbox for analysing Spatial Point Patterns. Focused mainly on two-dimensional point patterns, including multitype/marked points, in any spatial region. Also supports three-dimensional point patterns, space-time point patterns in any number of dimensions, point patterns on a linear network, and patterns of other geometrical objects. Supports spatial covariate data such as pixel images.
Contains over 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, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported.
Parametric models can be fitted to point pattern data using the functions ppm(), kppm(), slrm(), dppm() similar to glm(). Types of models include Poisson, Gibbs and Cox point processes, Neyman-Scott cluster processes, and determinantal point processes. Models may involve dependence on covariates, inter-point interaction, cluster formation and dependence on marks. Models are fitted by maximum likelihood, logistic regression, minimum contrast, and composite likelihood methods.
A model can be fitted to a list of point patterns (replicated point pattern data) using the function mppm(). The model can include random effects and fixed effects depending on the experimental design, in addition to all the features listed above.
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()) and variable selection (sdr). 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.influence.ppm | Extract Subset of Influence Object | |

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

DiggleGratton | Diggle-Gratton model | |

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

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

[.ssf | Subset of spatially sampled function | |

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

Hardcore | The Hard Core Point Process Model | |

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

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

Kmodel.dppm | K-function or Pair Correlation Function of a Determinantal Point Process Model | |

Kmeasure | Reduced Second Moment Measure | |

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

Extract.linim | Extract Subset of Pixel Image on Linear Network | |

BadGey | Hybrid Geyer Point Process Model | |

AreaInter | The Area Interaction Point Process Model | |

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

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

Extract.quad | Subset of Quadrature Scheme | |

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

Concom | The Connected Component Process Model | |

Hest | Spherical Contact Distribution Function | |

Gfox | Foxall's Distance Functions | |

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

CDF | Cumulative Distribution Function From Kernel Density Estimate | |

Geyer | Geyer's Saturation Point Process Model | |

Gcom | Model Compensator of Nearest Neighbour Function | |

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

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

Kcom | Model Compensator of K Function | |

GmultiInhom | Inhomogeneous Marked G-Function | |

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

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

Lcross.inhom | Inhomogeneous Cross Type L Function | |

Extract.im | Extract Subset of Image | |

Ord | Generic Ord Interaction model | |

Gres | Residual G Function | |

Finhom | Inhomogeneous Empty Space Function | |

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

adaptive.density | Adaptive Estimate of Intensity of Point Pattern | |

Extract.fasp | Extract Subset of Function Array | |

Jest | Estimate the J-function | |

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

Kest | K-function | |

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

Emark | Diagnostics for random marking | |

FmultiInhom | Inhomogeneous Marked F-Function | |

Replace.linim | Reset Values in Subset of Image on Linear Network | |

Extract.linnet | Extract Subset of Linear Network | |

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

OrdThresh | Ord's Interaction model | |

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

LennardJones | The Lennard-Jones Potential | |

Kres | Residual K Function | |

areaLoss | Difference of Disc Areas | |

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

Kinhom | Inhomogeneous K-function | |

append.psp | Combine Two Line Segment Patterns | |

affine.tess | Apply Geometrical Transformation To Tessellation | |

Kest.fft | K-function using FFT | |

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

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

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

add.texture | Fill Plot With Texture | |

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

Gest | Nearest Neighbour Distance Function G | |

Kmulti.inhom | Inhomogeneous Marked K-Function | |

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

Extract.owin | Extract Subset of Window | |

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

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

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

Jinhom | Inhomogeneous J-function | |

Jmulti | Marked J Function | |

Fiksel | The Fiksel Interaction | |

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

HierStrauss | The Hierarchical Strauss Point Process Model | |

HierHard | The Hierarchical Hard Core Point Process Model | |

Ldot.inhom | Inhomogeneous Multitype L Dot Function | |

as.function.tess | Convert a Tessellation to a Function | |

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

as.data.frame.lintess | Convert Network Tessellation to Data Frame | |

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

auc | Area Under ROC Curve | |

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

as.function.owin | Convert Window to Indicator Function | |

Ginhom | Inhomogeneous Nearest Neighbour Function | |

Poisson | Poisson Point Process Model | |

Gmulti | Marked Nearest Neighbour Distance Function | |

Pairwise | Generic Pairwise Interaction model | |

Iest | Estimate the I-function | |

Penttinen | Penttinen Interaction | |

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

Strauss | The Strauss Point Process Model | |

as.boxx | Convert Data to Multi-Dimensional Box | |

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

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

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

Kmark | Mark-Weighted K Function | |

as.ppp | Convert Data To Class ppp | |

anova.mppm | ANOVA for Fitted Point Process Models for Replicated Patterns | |

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

as.tess | Convert Data To Tessellation | |

Linhom | Inhomogeneous L-function | |

Kscaled | Locally Scaled K-function | |

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

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

as.psp | Convert Data To Class psp | |

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

Lest | L-function | |

Ksector | Sector K-function | |

WindowOnly | Extract Window of Spatial Object | |

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

Ops.msr | Arithmetic Operations on Measures | |

Smooth.fv | Apply Smoothing to Function Values | |

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

closepairs | Close Pairs of Points | |

boundingcircle | Smallest Enclosing Circle | |

clickdist | Interactively Measure Distance | |

branchlabelfun | Tree Branch Membership Labelling Function | |

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

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

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

bugfixes | List Recent Bug Fixes | |

as.data.frame.envelope | Coerce Envelope to Data Frame | |

as.linfun | Convert Data to a Function on a Linear Network | |

Kcross.inhom | Inhomogeneous Cross K Function | |

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

Saturated | Saturated Pairwise Interaction model | |

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

colourtools | Convert and Compare Colours in Different Formats | |

MinkowskiSum | Minkowski Sum of Windows | |

colouroutputs | Extract or Assign Colour Values in a Colour Map | |

affine.owin | Apply Affine Transformation To Window | |

corners | Corners of a rectangle | |

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

delaunayDistance | Distance on Delaunay Triangulation | |

contour.im | Contour plot of pixel image | |

LambertW | Lambert's W Function | |

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

distmap.owin | Distance Map of Window | |

clickjoin | Interactively join vertices on a plot | |

compareFit | Residual Diagnostics for Multiple Fitted Models | |

as.function.leverage.ppm | Convert Leverage Object to Function of Coordinates | |

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

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

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

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

Hybrid | Hybrid Interaction Point Process Model | |

anylist | List of Objects | |

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

divide.linnet | Divide Linear Network at Cut Points | |

densityfun.ppp | Kernel Estimate of Intensity as a Spatial Function | |

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

dilation | Morphological Dilation | |

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

contour.imlist | Array of Contour Plots | |

cut.lpp | Classify Points in a Point Pattern on a Network | |

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

Math.imlist | S3 Group Generic methods for List of Images | |

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

dppparbounds | Parameter Bound for a Determinantal Point Process Model | |

PPversion | Transform a Function into its P-P or Q-Q Version | |

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

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

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

deriv.fv | Calculate Derivative of Function Values | |

emend | Force Model to be Valid | |

harmonic | Basis for Harmonic Functions | |

diameter | Diameter of an Object | |

distmap | Distance Map | |

dim.detpointprocfamily | Dimension of Determinantal Point Process Model | |

dkernel | Kernel distributions and random generation | |

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

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

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

edge.Trans | Translation Edge Correction | |

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

dppspecden | Extract Spectral Density from Determinantal Point Process Model Object | |

intensity | Intensity of a Dataset or a Model | |

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

anyNA.im | Check Whether Image Contains NA Values | |

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

Smooth | Spatial smoothing of data | |

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

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

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

addvar | Added Variable Plot for Point Process Model | |

Kmulti | Marked K-Function | |

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

fv | Create a Function Value Table | |

Triplets | The Triplet Point Process Model | |

as.ppm | Extract Fitted Point Process Model | |

intensity.ppx | Intensity of a Multidimensional Space-Time Point Pattern | |

fv.object | Function Value Table | |

expand.owin | Apply Expansion Rule | |

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

Tstat | Third order summary statistic | |

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

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

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

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

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

bw.CvL | Cronie and van Lieshout's Criterion for Bandwidth Selection for Kernel Density | |

as.im | Convert to Pixel Image | |

imcov | Spatial Covariance of a Pixel Image | |

harmonise | Make Objects Compatible | |

intensity.dppm | Intensity of Determinantal Point Process Model | |

im.object | Class of Images | |

Smooth.ssf | Smooth a Spatially Sampled Function | |

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

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

MultiStrauss | The Multitype Strauss Point Process Model | |

MultiHard | The Multitype Hard Core Point Process Model | |

is.connected | Determine Whether an Object is Connected | |

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

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

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

bdist.pixels | Distance to Boundary of Window | |

clusterfield | Field of clusters | |

bc.ppm | Bias Correction for Fitted Model | |

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

bits.test | Balanced Independent Two-Stage Monte Carlo Test | |

border | Border Region of a Window | |

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

is.connected.ppp | Determine Whether a Point Pattern is Connected | |

intensity.ppp | Empirical Intensity of Point Pattern | |

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

markcrosscorr | Mark Cross-Correlation Function | |

as.rectangle | Window Frame | |

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

begins | Check Start of Character String | |

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

blur | Apply Gaussian Blur to a Pixel Image | |

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

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

as.layered | Convert Data To Layered Object | |

layered | Create List of Plotting Layers | |

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

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

lohboot | Bootstrap Confidence Bands for Summary Function | |

as.hyperframe | Convert Data to Hyperframe | |

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

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

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

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

clickppp | Interactively Add Points | |

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

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

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

as.fv | Convert Data To Class fv | |

clusterset | Allard-Fraley Estimator of Cluster Feature | |

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

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

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

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

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

chop.linnet | Divide a Linear Network into Tiles Using Infinite Lines | |

localpcf | Local pair correlation function | |

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

clarkevans | Clark and Evans Aggregation Index | |

mean.im | Mean and Median of Pixel Values in an Image | |

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

linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |

logLik.dppm | Log Likelihood and AIC for Fitted Determinantal Point Process Model | |

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

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

box3 | Three-Dimensional Box | |

beginner | Print Introduction For Beginners | |

convexhull | Convex Hull | |

convexhull.xy | Convex Hull of Points | |

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

concatxy | Concatenate x,y Coordinate Vectors | |

connected | Connected components | |

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

detpointprocfamilyfun | Construct a New Determinantal Point Process Model Family Function | |

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

boxx | Multi-Dimensional Box | |

affine | Apply Affine Transformation | |

Softcore | The Soft Core Point Process Model | |

areaGain | Difference of Disc Areas | |

area.owin | Area of a Window | |

as.owin | Convert Data To Class owin | |

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

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

bw.voronoi | Cross Validated Bandwidth Selection for Voronoi Estimator of Intensity on a Network | |

compileK | Generic Calculation of K Function and Pair Correlation Function | |

lpp | Create Point Pattern on Linear Network | |

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

clickpoly | Interactively Define a Polygon | |

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

angles.psp | Orientation Angles of Line Segments | |

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

clicklpp | Interactively Add Points on a Linear Network | |

complement.owin | Take Complement of a Window | |

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

centroid.owin | Centroid of a window | |

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

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

dirichletWeights | Compute Quadrature Weights Based on Dirichlet Tessellation | |

data.lppm | Extract Original Data from a Fitted Point Process Model on a Network | |

diameter.owin | Diameter of a Window | |

dffit.ppm | Case Deletion Effect Measure of Fitted Model | |

dfbetas.ppm | Parameter Influence Measure | |

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

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

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

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

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

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

as.interact | Extract Interaction Structure | |

bind.fv | Combine Function Value Tables | |

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

methods.unitname | Methods for Units | |

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

markmarkscatter | Mark-Mark Scatter Plot | |

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

msr | Signed or Vector-Valued Measure | |

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

dppPowerExp | Power Exponential Spectral Determinantal Point Process Model | |

as.data.frame.tess | Convert Tessellation to Data Frame | |

methods.ssf | Methods for Spatially Sampled Functions | |

dg.envelope | Global Envelopes for Dao-Genton Test | |

dilated.areas | Areas of Morphological Dilations | |

fasp.object | Function Arrays for Spatial Patterns | |

connected.linnet | Connected Components of a Linear Network | |

discs | Union of Discs | |

bdist.points | Distance to Boundary of Window | |

dppapproxkernel | Approximate Determinantal Point Process Kernel | |

hyperframe | Hyper Data Frame | |

erosion | Morphological Erosion by a Disc | |

eem | Exponential Energy Marks | |

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

distcdf | Distribution Function of Interpoint Distance | |

bw.abram | Abramson's Adaptive Bandwidths | |

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

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

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

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

dclf.sigtrace | Significance Trace of Cressie-Loosmore-Ford or Maximum Absolute Deviation Test | |

methods.zclustermodel | Methods for Cluster Models | |

eroded.areas | Areas of Morphological Erosions | |

closetriples | Close Triples of Points | |

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

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

bdist.tiles | Distance to Boundary of Window | |

extrapolate.psp | Extrapolate Line Segments to Obtain Infinite Lines | |

bw.lppl | Likelihood Cross Validation Bandwidth Selection for Kernel Density on a Linear Network | |

densityVoronoi | Intensity Estimate of Point Pattern Using Voronoi-Dirichlet Tessellation | |

bits.envelope | Global Envelopes for Balanced Independent Two-Stage Test | |

bw.pcf | Cross Validated Bandwidth Selection for Pair Correlation Function | |

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

endpoints.psp | Endpoints of Line Segment Pattern | |

connected.lpp | Connected Components of a Point Pattern on a Linear Network | |

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

insertVertices | Insert New Vertices in a Linear Network | |

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

density.psp | Kernel Smoothing of Line Segment Pattern or Linear Network | |

circdensity | Density Estimation for Circular Data | |

closing | Morphological Closing | |

clarkevans.test | Clark and Evans Test | |

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

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

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

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

disc | Circular Window | |

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

delaunay | Delaunay Triangulation of Point Pattern | |

objsurf | Objective Function Surface | |

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

fardist | Farthest Distance to Boundary of Window | |

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

kernel.squint | Integral of Squared Kernel | |

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

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

distfun | Distance Map as a Function | |

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

clusterkernel | Extract Cluster Offspring Kernel | |

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

has.close | Check Whether Points Have Close Neighbours | |

headtail | First or Last Part of a Spatial Pattern | |

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

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

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

nnwhich.ppx | Nearest Neighbours in Any Dimensions | |

convexify | Weil's Convexifying Operation | |

diameter.linnet | Diameter and Bounding Radius of a Linear Network | |

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

clickbox | Interactively Define a Rectangle | |

crossing.linnet | Crossing Points between Linear Network and Other Lines | |

connected.ppp | Connected Components of a Point Pattern | |

colourmap | Colour Lookup Tables | |

dmixpois | Mixed Poisson Distribution | |

distfun.lpp | Distance Map on Linear Network | |

densityAdaptiveKernel | Adaptive Kernel Estimate of Intensity of Point Pattern | |

convolve.im | Convolution of Pixel Images | |

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

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

fryplot | Fry Plot of Point Pattern | |

densityQuick.lpp | Kernel Estimation of Intensity on a Network using a 2D Kernel | |

compatible | Test Whether Objects Are Compatible | |

is.rectangle | Determine Type of Window | |

inforder.family | Infinite Order Interaction Family | |

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

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

opening | Morphological Opening | |

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

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

intersect.tess | Intersection of Two Tessellations | |

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

inside.boxx | Test Whether Points Are Inside A Multidimensional Box | |

nnfromvertex | Nearest Data Point From Each Vertex in a Network | |

nobjects | Count Number of Geometrical Objects in a Spatial Dataset | |

predict.dppm | Prediction from a Fitted Determinantal Point Process Model | |

pairdist.ppx | Pairwise Distances in Any Dimensions | |

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

dg.test | Dao-Genton Adjusted Goodness-Of-Fit Test | |

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

dppCauchy | Generalized Cauchy Determinantal Point Process Model | |

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

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

persp.im | Perspective Plot of Pixel Image | |

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

linfun | Function on a Linear Network | |

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

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

edges | Extract Boundary Edges of a Window. | |

kernel.moment | Moment of Smoothing Kernel | |

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

dppspecdenrange | Range of Spectral Density of a Determinantal Point Process Model | |

edges2triangles | List Triangles in a Graph | |

domain | Extract the Domain of any Spatial Object | |

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

erosionAny | Morphological Erosion of Windows | |

envelope | Simulation Envelopes of Summary Function | |

densityVoronoi.lpp | Intensity Estimate of Point Pattern on Linear Network Using Voronoi-Dirichlet Tessellation | |

dirichlet | Dirichlet Tessellation of Point Pattern | |

connected.tess | Connected Components of Tiles of a Tessellation | |

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

periodify | Make Periodic Copies of a Spatial Pattern | |

plot.bermantest | Plot Result of Berman Test | |

dimhat | Estimate Dimension of Central Subspace | |

plot.textstring | Plot a Text String | |

pairdist.psp | Pairwise distances between line segments | |

plot.cdftest | Plot a Spatial Distribution Test | |

plot.influence.ppm | Plot Influence Measure | |

plot.listof | Plot a List of Things | |

laslett | Laslett's Transform | |

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

plot.texturemap | Plot a Texture Map | |

interp.colourmap | Interpolate smoothly between specified colours | |

dppBessel | Bessel Type Determinantal Point Process Model | |

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

discpartarea | Area of Part of Disc | |

covering | Cover Region with Discs | |

kernel.factor | Scale factor for density kernel | |

crossdist | Pairwise distances | |

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

lurking.mppm | Lurking Variable Plot for Multiple Point Patterns | |

dirichletAreas | Compute Areas of Tiles in Dirichlet Tessellation | |

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

dg.progress | Progress Plot of Dao-Genton Test of Spatial Pattern | |

deltametric | Delta Metric | |

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

eval.fasp | Evaluate Expression Involving Function Arrays | |

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

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

hist.funxy | Histogram of Values of a Spatial Function | |

predict.rppm | Make Predictions From a Recursively Partitioned Point Process Model | |

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

increment.fv | Increments of a Function | |

foo | Foo is Not a Real Name | |

dppm | Fit Determinantal Point Process Model | |

dppkernel | Extract Kernel from Determinantal Point Process Model Object | |

ellipse | Elliptical Window. | |

grow.boxx | Add margins to box in any dimension | |

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

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

linim | Create Pixel Image on Linear Network | |

localKcross | Local Multitype K Function (Cross-Type) | |

distmap.ppp | Distance Map of Point Pattern | |

fixef.mppm | Extract Fixed Effects from Point Process Model | |

dg.sigtrace | Significance Trace of Dao-Genton Test | |

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

miplot | Morisita Index Plot | |

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

localKcross.inhom | Inhomogeneous Multitype K Function | |

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

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

lut | Lookup Tables | |

markvario | Mark Variogram | |

is.marked | Test Whether Marks Are Present | |

dppGauss | Gaussian Determinantal Point Process Model | |

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

dirichletVertices | Vertices and Edges of Dirichlet Tessellation | |

envelopeArray | Array of Simulation Envelopes of Summary Function | |

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

envelope.envelope | Recompute Envelopes | |

fourierbasis | Fourier Basis Functions | |

dppMatern | Whittle-Matern Determinantal Point Process Model | |

dppapproxpcf | Approximate Pair Correlation Function of Determinantal Point Process Model | |

edit.hyperframe | Invoke Text Editor on Hyperframe | |

mean.linim | Mean, Median, Quantiles of Pixel Values on a Linear Network | |

pool.quadrattest | Pool Several Quadrat Tests | |

psp | Create a Line Segment Pattern | |

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

ppx | Multidimensional Space-Time Point Pattern | |

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

eval.fv | Evaluate Expression Involving Functions | |

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

hybrid.family | Hybrid Interaction Family | |

eval.im | Evaluate Expression Involving Pixel Images | |

linearpcf | Linear Pair Correlation Function | |

intensity.quadratcount | Intensity Estimates Using Quadrat Counts | |

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

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

dppeigen | Internal function calculating eig and index | |

integral.im | Integral of a Pixel Image | |

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

im | Create a Pixel Image Object | |

grow.rectangle | Add margins to rectangle | |

intensity.psp | Empirical Intensity of Line Segment Pattern | |

edges2vees | List Dihedral Triples in a Graph | |

measureContinuous | Discrete and Continuous Components of a Measure | |

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

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

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

methods.linnet | Methods for Linear Networks | |

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

funxy | Spatial Function Class | |

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

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

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

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

linearK | Linear K Function | |

linnet | Create a Linear Network | |

kppm | Fit Cluster or Cox Point Process Model | |

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

lengths.psp | Lengths of Line Segments | |

ewcdf | Weighted Empirical Cumulative Distribution Function | |

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

psib | Sibling Probability of Cluster Point Process | |

rpoispp | Generate Poisson Point Pattern | |

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

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

rPenttinen | Perfect Simulation of the Penttinen Process | |

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

quadrats | Divide Region into Quadrats | |

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

repul.dppm | Repulsiveness Index of a Determinantal Point Process Model | |

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

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

rPoissonCluster | Simulate Poisson Cluster Process | |

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

rMaternI | Simulate Matern Model I | |

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

rat | Ratio object | |

rMatClust | Simulate Matern Cluster Process | |

rotate.psp | Rotate a Line Segment Pattern | |

integral.msr | Integral of a Measure | |

pairorient | Point Pair Orientation Distribution | |

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

interp.im | Interpolate a Pixel Image | |

nnmark | Mark of Nearest Neighbour | |

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

harmonise.msr | Make Measures Compatible | |

hextess | Hexagonal Grid or Tessellation | |

hierpair.family | Hierarchical Pairwise Interaction Process Family | |

harmonise.owin | Make Windows Compatible | |

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

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

rex | Richardson Extrapolation | |

requireversion | Require a Specific Version of a Package | |

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

markcorr | Mark Correlation Function | |

flipxy | Exchange X and Y Coordinates | |

lintess | Tessellation on a Linear Network | |

mergeLevels | Merge Levels of a Factor | |

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

nnmap | K-th Nearest Point Map | |

infline | Infinite Straight Lines | |

nearestsegment | Find Line Segment Nearest to Each Point | |

linequad | Quadrature Scheme on a Linear Network | |

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

methods.layered | Methods for Layered Objects | |

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

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

is.multitype | Test whether Object is Multitype | |

rgbim | Create Colour-Valued Pixel Image | |

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

rjitter | Random Perturbation of a Point Pattern | |

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

ripras | Estimate window from points alone | |

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

nvertices | Count Number of Vertices | |

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

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

pixelcentres | Extract Pixel Centres as Point Pattern | |

gridcentres | Rectangular grid of points | |

lineardirichlet | Dirichlet Tessellation on a Linear Network | |

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

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

pcf | Pair Correlation Function | |

markconnect | Mark Connection Function | |

methods.distfun | Geometrical Operations for Distance Functions | |

gridweights | Compute Quadrature Weights Based on Grid Counts | |

lurking | Lurking Variable Plot | |

pairs.im | Scatterplot Matrix for Pixel Images | |

hopskel | Hopkins-Skellam Test | |

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

rmhexpand | Specify Simulation Window or Expansion Rule | |

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

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

pcfinhom | Inhomogeneous Pair Correlation Function | |

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

measureVariation | Positive and Negative Parts, and Variation, of a Measure | |

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

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

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

plot.colourmap | Plot a Colour Map | |

sdrPredict | Compute Predictors from Sufficient Dimension Reduction | |

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

methods.dppm | Methods for Determinantal Point Process Models | |

model.matrix.mppm | Extract Design Matrix of Point Process Model for Several Point Patterns | |

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

levelset | Level Set of a Pixel Image | |

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

lineartileindex | Determine Which Tile Contains Each Given Point on a Linear Network | |

plot.dppm | Plot a fitted determinantal point process | |

localK | Neighbourhood density function | |

marks | Marks of a Point Pattern | |

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

harmonise.im | Make Pixel Images Compatible | |

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

harmonise.fv | Make Function Tables Compatible | |

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

plot.owin | Plot a Spatial Window | |

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

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

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

plot.symbolmap | Plot a Graphics Symbol Map | |

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

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

lixellate | Subdivide Segments of a Network | |

matrixpower | Power of a Matrix | |

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

logLik.slrm | Loglikelihood of Spatial Logistic Regression | |

plot.tess | Plot a Tessellation | |

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

rMosaicField | Mosaic Random Field | |

rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |

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

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

intersect.lintess | Intersection of Tessellations on a Linear Network | |

integral.linim | Integral on a Linear Network | |

incircle | Find Largest Circle Inside Window | |

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

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

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

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

joinVertices | Join Vertices in a Network | |

rshift.ppp | Randomly Shift a Point Pattern | |

simulate.mppm | Simulate a Point Process Model Fitted to Several Point Patterns | |

rotmean | Rotational Average of a Pixel Image | |

scanLRTS | Likelihood Ratio Test Statistic for Scan Test | |

sdr | Sufficient Dimension Reduction | |

scanpp | Read Point Pattern From Data File | |

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

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

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

localKinhom | Inhomogeneous Neighbourhood Density Function | |

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

matchingdist | Distance for a Point Pattern Matching | |

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

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

marks.tess | Marks of a Tessellation | |

linearKinhom | Inhomogeneous Linear K Function | |

owin.object | Class owin | |

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

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

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

methods.funxy | Methods for Spatial Functions | |

logLik.mppm | Log Likelihood and AIC for Multiple Point Process Model | |

localKdot | Local Multitype K Function (Dot-Type) | |

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

methods.objsurf | Methods for Objective Function Surfaces | |

rSwitzerlpp | Switzer-type Point Process on Linear Network | |

psp.object | Class of Line Segment Patterns | |

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

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

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

pool.fv | Pool Several Functions | |

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

rThomas | Simulate Thomas Process | |

quad.object | Class of Quadrature Schemes | |

ragsMultiHard | Alternating Gibbs Sampler for Multitype Hard Core Process | |

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

model.images | Compute Images of Constructed Covariates | |

nncross | Nearest Neighbours Between Two Patterns | |

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

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

quantile.density | Quantiles of a Density Estimate | |

nnwhich | Nearest neighbour | |

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

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

rMaternII | Simulate Matern Model II | |

nnorient | Nearest Neighbour Orientation Distribution | |

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

mincontrast | Method of Minimum Contrast | |

methods.fii | Methods for Fitted Interactions | |

midpoints.psp | Midpoints of Line Segment Pattern | |

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

ragsAreaInter | Alternating Gibbs Sampler for Area-Interaction Process | |

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

nestsplit | Nested Split | |

reach | Interaction Distance of a Point Process | |

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

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

nnclean | Nearest Neighbour Clutter Removal | |

npfun | Dummy Function Returns Number of Points | |

pairs.linim | Scatterplot Matrix for Pixel Images on a Linear Network | |

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

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

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

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

pairdist.pp3 | Pairwise distances in Three Dimensions | |

reach.dppm | Range of Interaction for a Determinantal Point Process Model | |

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

owin | Create a Window | |

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

plot.leverage.ppm | Plot Leverage Function | |

parres | Partial Residuals for Point Process Model | |

pcfmulti | Marked pair correlation function | |

repairNetwork | Repair Internal Data in a Linear Network | |

plot.envelope | Plot a Simulation Envelope | |

pairdist.ppp | Pairwise distances | |

parameters | Extract Model Parameters in Understandable Form | |

points.lpp | Draw Points on Existing Plot | |

perimeter | Perimeter Length of Window | |

plot.fasp | Plot a Function Array | |

plot.anylist | Plot a List of Things | |

pixelquad | Quadrature Scheme Based on Pixel Grid | |

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

plot.onearrow | Plot an Arrow | |

plot.rppm | Plot a Recursively Partitioned Point Process Model | |

pairdist.default | Pairwise distances | |

overlap.owin | Compute Area of Overlap | |

ppm | Fit Point Process Model to Data | |

ppp.object | Class of Point Patterns | |

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

pp3 | Three Dimensional Point Pattern | |

rthin | Random Thinning | |

rotate.im | Rotate a Pixel Image | |

rlpp | Random Points on a Linear Network | |

rppm | Recursively Partitioned Point Process Model | |

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

nncross.ppx | Nearest Neighbours Between Two Patterns in Any Dimensions | |

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

pixellate | Convert Spatial Object to Pixel Image | |

rshift | Random Shift | |

setcov | Set Covariance of a Window | |

rotate.infline | Rotate or Shift Infinite Lines | |

rthinclumps | Random Thinning of Clumps | |

npoints | Number of Points in a Point Pattern | |

rNeymanScott | Simulate Neyman-Scott Process | |

nndist | Nearest neighbour distances | |

sharpen | Data Sharpening of Point Pattern | |

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

scalardilate | Apply Scalar Dilation | |

pairdist | Pairwise distances | |

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

shift.owin | Apply Vector Translation To Window | |

project2segment | Move Point To Nearest Line | |

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

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

slrm | Spatial Logistic Regression | |

padimage | Pad the Border of a Pixel Image | |

nnwhich.pp3 | Nearest neighbours in three dimensions | |

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

plot.linnet | Plot a linear network | |

nnfun | Nearest Neighbour Index Map as a Function | |

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

pppdist | Distance Between Two Point Patterns | |

pairwise.family | Pairwise Interaction Process Family | |

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

pool | Pool Data | |

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

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

plot.lintess | Plot a Tessellation on a Linear Network | |

plot.fv | Plot Function Values | |

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

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

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

plot.studpermutest | Plot a Studentised Permutation Test | |

ord.family | Ord Interaction Process Family | |

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

plot.hyperframe | Plot Entries in a Hyperframe | |

quadratcount | Quadrat counting for a point pattern | |

plot.quad | Plot a Spatial Quadrature Scheme | |

pool.envelope | Pool Data from Several Envelopes | |

plot.profilepl | Plot Profile Likelihood | |

ppmInfluence | Leverage and Influence Measures for Spatial Point Process Model | |

plot.quadratcount | Plot Quadrat Counts | |

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

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

polynom | Polynomial in One or Two Variables | |

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

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

project2set | Find Nearest Point in a Region | |

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

ppp | Create a Point Pattern | |

plot.layered | Layered Plot | |

prune.rppm | Prune a Recursively Partitioned Point Process Model | |

pseudoR2 | Calculate Pseudo-R-Squared for Point Process Model | |

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

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

quasirandom | Quasirandom Patterns | |

print.quad | Print a Quadrature Scheme | |

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

rMosaicSet | Mosaic Random Set | |

reflect | Reflect In Origin | |

quantile.im | Sample Quantiles of Pixel Image | |

plot.laslett | Plot Laslett Transform | |

rStrauss | Perfect Simulation of the Strauss Process | |

rcelllpp | Simulate Cell Process on Linear Network | |

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

reach.kppm | Range of Interaction for a Cox or Cluster Point Process Model | |

rescale | Convert dataset to another unit of length | |

rcell | Simulate Baddeley-Silverman Cell Process | |

plot.im | Plot a Pixel Image | |

rknn | Theoretical Distribution of Nearest Neighbour Distance | |

plot.ppp | plot a Spatial Point Pattern | |

rectcontact | Contact Distribution Function using Rectangular Structuring Element | |

pixellate.owin | Convert Window to Pixel Image | |

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

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

ranef.mppm | Extract Random Effects from Point Process Model | |

plot.imlist | Plot a List of Images | |

pointsOnLines | Place Points Evenly Along Specified Lines | |

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

rhohat | Nonparametric Estimate of Intensity as Function of a Covariate | |

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

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

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

plot.pppmatching | Plot a Point Matching | |

rGaussPoisson | Simulate Gauss-Poisson Process | |

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

plot.ssf | Plot a Spatially Sampled Function | |

pppmatching | Create a Point Matching | |

pppmatching.object | Class of Point Matchings | |

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

rdpp | Simulation of a Determinantal Point Process | |

rHardcore | Perfect Simulation of the Hardcore Process | |

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

polartess | Tessellation Using Polar Coordinates | |

simulate.dppm | Simulation of Determinantal Point Process Model | |

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

progressreport | Print Progress Reports | |

profilepl | Fit Models by Profile Maximum Pseudolikelihood or AIC | |

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

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

rectdistmap | Distance Map Using Rectangular Distance Metric | |

quantess | Quantile Tessellation | |

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

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

range.fv | Range of Function Values | |

rags | Alternating Gibbs Sampler for Multitype Point Processes | |

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

rounding | Detect Numerical Rounding | |

rlabel | Random Re-Labelling of Point Pattern | |

spatstat-internal | Internal spatstat functions | |

rQuasi | Generate Quasirandom Point Pattern in Given Window | |

regularpolygon | Create A Regular Polygon | |

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

rLGCP | Simulate Log-Gaussian Cox Process | |

rSSI | Simulate Simple Sequential Inhibition | |

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

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

rpoint | Generate N Random Points | |

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

rotate.owin | Rotate a Window | |

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

relrisk | Estimate of Spatially-Varying Relative Risk | |

residuals.dppm | Residuals for Fitted Determinantal Point Process Model | |

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

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

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

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

rpoisline | Generate Poisson Random Line Process | |

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

rescue.rectangle | Convert Window Back To Rectangle | |

rmpoispp | Generate Multitype Poisson Point Pattern | |

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

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

rose | Rose Diagram | |

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

scaletointerval | Rescale Data to Lie Between Specified Limits | |

rpoislinetess | Poisson Line Tessellation | |

rmpoint | Generate N Random Multitype Points | |

rstrat | Simulate Stratified Random Point Pattern | |

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

solist | List of Two-Dimensional Spatial Objects | |

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

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

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

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

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

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

rotate | Rotate | |

scan.test | Spatial Scan Test | |

rnoise | Random Pixel Noise | |

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

rpoislpp | Poisson Point Process on a Linear Network | |

rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |

rtemper | Simulated Annealing or Simulated Tempering for Gibbs Point Processes | |

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

roc | Receiver Operating Characteristic | |

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

runiflpp | Uniform Random Points on a Linear Network | |

rsyst | Simulate systematic random point pattern | |

shift | Apply Vector Translation | |

rotate.ppp | Rotate a Point Pattern | |

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

runifpoint | Generate N Uniform Random Points | |

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

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

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

spatstat-deprecated | Deprecated spatstat functions | |

spatdim | Spatial Dimension of a Dataset | |

spatialcdf | Spatial Cumulative Distribution Function | |

No Results! |

## Vignettes of spatstat

Name | ||

bugfixes.Rnw | ||

datasets.Rnw | ||

getstart.Rnw | ||

hexagon.eps | ||

hexagon.pdf | ||

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replicated.Rnw | ||

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updates.Rnw | ||

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## Last month downloads

## Details

Date | 2020-01-23 |

License | GPL (>= 2) |

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

LazyData | true |

NeedsCompilation | yes |

ByteCompile | true |

BugReports | https://github.com/spatstat/spatstat/issues |

Packaged | 2020-01-23 07:15:11 UTC; adrian |

Repository | CRAN |

Date/Publication | 2020-01-23 14:00:02 UTC |

imports | abind , deldir (>= 0.0-21) , goftest (>= 1.2-2) , Matrix , mgcv , polyclip (>= 1.10-0) , spatstat.utils (>= 1.15-0) , tensor |

suggests | fftwtools (>= 0.9-8) , gsl , locfit , maptools , RandomFields (>= 3.1.24.1) , RandomFieldsUtils (>= 0.3.3.1) , rpanel , sm , spatial , tkrplot |

depends | graphics , grDevices , methods , nlme , R (>= 3.3.0) , rpart , spatstat.data (>= 1.4-0) , stats , utils |

Contributors | Adrian Baddeley, Rolf Turner, Ege Rubak |

#### Include our badge in your README

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