# spatstat v1.59-0

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

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

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

Extract.quad | Subset of Quadrature Scheme | |

GmultiInhom | Inhomogeneous Marked G-Function | |

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

BadGey | Hybrid Geyer Point Process Model | |

Extract.im | Extract Subset of Image | |

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

Gest | Nearest Neighbour Distance Function G | |

Gres | Residual G Function | |

Extract.linnet | Extract Subset of Linear Network | |

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

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

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

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

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

[.ssf | Subset of spatially sampled function | |

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

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

Kcom | Model Compensator of K Function | |

Extract.owin | Extract Subset of Window | |

Jinhom | Inhomogeneous J-function | |

Jmulti | Marked J Function | |

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

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

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

Fiksel | The Fiksel Interaction | |

Kmulti.inhom | Inhomogeneous Marked K-Function | |

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

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

Geyer | Geyer's Saturation Point Process Model | |

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

Kres | Residual K Function | |

Finhom | Inhomogeneous Empty Space Function | |

FmultiInhom | Inhomogeneous Marked F-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 | |

HierHard | The Hierarchical Hard Core Point Process Model | |

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

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

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

Gfox | Foxall's Distance Functions | |

MinkowskiSum | Minkowski Sum of Windows | |

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

Hest | Spherical Contact Distribution Function | |

HierStrauss | The Hierarchical Strauss Point Process Model | |

Kmeasure | Reduced Second Moment Measure | |

Gcom | Model Compensator of Nearest Neighbour Function | |

LambertW | Lambert's W Function | |

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

Ord | Generic Ord Interaction model | |

Jest | Estimate the J-function | |

Kest | K-function | |

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

Ginhom | Inhomogeneous Nearest Neighbour Function | |

Gmulti | Marked Nearest Neighbour Distance Function | |

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

Lest | L-function | |

Linhom | L-function | |

Kest.fft | K-function using FFT | |

Hybrid | Hybrid Interaction Point Process Model | |

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

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

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

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

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

Ops.msr | Arithmetic Operations on Measures | |

Iest | Estimate the I-function | |

Kmulti | Marked K-Function | |

Poisson | Poisson Point Process Model | |

OrdThresh | Ord's Interaction model | |

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

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

Ldot.inhom | Inhomogeneous Multitype L Dot Function | |

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

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

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

Kinhom | Inhomogeneous K-function | |

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

Kcross.inhom | Inhomogeneous Cross K Function | |

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

Smooth.fv | Apply Smoothing to Function Values | |

WindowOnly | Extract Window of Spatial Object | |

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

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

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

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

add.texture | Fill Plot With Texture | |

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

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

LennardJones | The Lennard-Jones Potential | |

Pairwise | Generic Pairwise Interaction model | |

MultiHard | The Multitype Hard Core Point Process Model | |

Kmark | Mark-Weighted K Function | |

Penttinen | Penttinen Interaction | |

MultiStrauss | The Multitype Strauss Point Process Model | |

Saturated | Saturated Pairwise Interaction model | |

Kscaled | Locally Scaled K-function | |

Ksector | Sector K-function | |

Softcore | The Soft Core Point Process Model | |

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

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

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

anylist | List of Objects | |

Lcross.inhom | Inhomogeneous Cross Type L Function | |

angles.psp | Orientation Angles of Line Segments | |

affine.owin | Apply Affine Transformation To Window | |

area.owin | Area of a Window | |

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

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

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

Smooth | Spatial smoothing of data | |

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

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

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

as.im | Convert to Pixel Image | |

as.interact | Extract Interaction Structure | |

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

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

Smooth.ssf | Smooth a Spatially Sampled Function | |

as.tess | Convert Data To Tessellation | |

addvar | Added Variable Plot for Point Process Model | |

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

affine | Apply Affine Transformation | |

bdist.pixels | Distance to Boundary of Window | |

Strauss | The Strauss Point Process Model | |

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

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

bdist.points | Distance to Boundary of Window | |

branchlabelfun | Tree Branch Membership Labelling Function | |

Triplets | The Triplet Point Process Model | |

affine.tess | Apply Geometrical Transformation To Tessellation | |

Tstat | Third order summary statistic | |

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

as.psp | Convert Data To Class psp | |

bugfixes | List Recent Bug Fixes | |

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

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

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

append.psp | Combine Two Line Segment Patterns | |

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

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

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

bw.abram | Abramson's Adaptive Bandwidths | |

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

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

areaGain | Difference of Disc Areas | |

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

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

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

clickdist | Interactively Measure Distance | |

clickjoin | Interactively join vertices on a plot | |

clusterkernel | Extract Cluster Offspring Kernel | |

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

as.rectangle | Window Frame | |

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

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

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

as.hyperframe | Convert Data to Hyperframe | |

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

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

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

beginner | Print Introduction For Beginners | |

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

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

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

begins | Check Start of Character String | |

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

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

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

as.ppm | Extract Fitted Point Process Model | |

box3 | Three-Dimensional Box | |

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

as.layered | Convert Data To Layered Object | |

as.ppp | Convert Data To Class ppp | |

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

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

boxx | Multi-Dimensional Box | |

as.owin | Convert Data To Class owin | |

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

areaLoss | Difference of Disc Areas | |

centroid.owin | Centroid of a window | |

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

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

bind.fv | Combine Function Value Tables | |

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

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

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

covering | Cover Region with Discs | |

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

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

as.fv | Convert Data To Class fv | |

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

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

boundingcircle | Smallest Enclosing Circle | |

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

clickppp | Interactively Add Points | |

crossdist | Pairwise distances | |

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

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

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

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

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

compareFit | Residual Diagnostics for Multiple Fitted Models | |

auc | Area Under ROC Curve | |

blur | Apply Gaussian Blur to a Pixel Image | |

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

bdist.tiles | Distance to Boundary of Window | |

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

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

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

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

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

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

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

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

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

clicklpp | Interactively Add Points on a Linear Network | |

complement.owin | Take Complement of a Window | |

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

clarkevans.test | Clark and Evans Test | |

clickbox | Interactively Define a Rectangle | |

convexhull | Convex Hull | |

clickpoly | Interactively Define a Polygon | |

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

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

bc.ppm | Bias Correction for Fitted Model | |

clusterset | Allard-Fraley Estimator of Cluster Feature | |

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

convexhull.xy | Convex Hull of Points | |

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

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

closetriples | Close Triples of Points | |

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

circdensity | Density Estimation for Circular Data | |

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

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

closing | Morphological Closing | |

clarkevans | Clark and Evans Aggregation Index | |

border | Border Region of a Window | |

delaunay | Delaunay Triangulation of Point Pattern | |

colourmap | Colour Lookup Tables | |

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

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

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

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

colourtools | Convert and Compare Colours in Different Formats | |

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

delaunayDistance | Distance on Delaunay Triangulation | |

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

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

deltametric | Delta Metric | |

concatxy | Concatenate x,y Coordinate Vectors | |

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

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

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

connected | Connected components | |

dilation | Morphological Dilation | |

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

dfbetas.ppm | Parameter Influence Measure | |

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

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

closepairs | Close Pairs of Points | |

discpartarea | Area of Part of Disc | |

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

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

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

clusterfield | Field of clusters | |

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

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

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

dirichletAreas | Compute Areas of Tiles in Dirichlet Tessellation | |

compatible | Test Whether Objects Are Compatible | |

dppBessel | Bessel Type Determinantal Point Process Model | |

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

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

dppCauchy | Generalized Cauchy Determinantal Point Process Model | |

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

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

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

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

dirichletVertices | Vertices and Edges of Dirichlet Tessellation | |

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

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

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

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

distmap.ppp | Distance Map of Point Pattern | |

convexify | Weil's Convexifying Operation | |

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

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

diameter.owin | Diameter of a Window | |

convolve.im | Convolution of Pixel Images | |

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

edges | Extract Boundary Edges of a Window. | |

dppeigen | Internal function calculating eig and index | |

edges2vees | List Dihedral Triples in a Graph | |

edit.hyperframe | Invoke Text Editor on Hyperframe | |

emend | Force Model to be Valid | |

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

fourierbasis | Fourier Basis Functions | |

contour.im | Contour plot of pixel image | |

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

edges2triangles | List Triangles in a Graph | |

contour.imlist | Array of Contour Plots | |

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

dilated.areas | Areas of Morphological Dilations | |

corners | Corners of a rectangle | |

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

fryplot | Fry Plot of Point Pattern | |

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

envelope.envelope | Recompute Envelopes | |

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

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

discs | Union of Discs | |

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

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

gridcentres | Rectangular grid of points | |

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

erosionAny | Morphological Erosion of Windows | |

hybrid.family | Hybrid Interaction Family | |

hyperframe | Hyper Data Frame | |

eval.fasp | Evaluate Expression Involving Function Arrays | |

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

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

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

distcdf | Distribution Function of Interpoint Distance | |

expand.owin | Apply Expansion Rule | |

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

dmixpois | Mixed Poisson Distribution | |

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

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

deriv.fv | Calculate Derivative of Function Values | |

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

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

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

dimhat | Estimate Dimension of Central Subspace | |

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

domain | Extract the Domain of any Spatial Object | |

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

dppPowerExp | Power Exponential Spectral Determinantal Point Process Model | |

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

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

distmap | Distance Map | |

funxy | Spatial Function Class | |

dirichlet | Dirichlet Tessellation of Point Pattern | |

dirichletWeights | Compute Quadrature Weights Based on Dirichlet Tessellation | |

distmap.owin | Distance Map of Window | |

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

dppapproxkernel | Approximate Determinantal Point Process Kernel | |

fv | Create a Function Value Table | |

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

gridweights | Compute Quadrature Weights Based on Grid Counts | |

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

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

im.object | Class of Images | |

disc | Circular Window | |

dppm | Fit Determinantal Point Process Model | |

diameter | Diameter of an Object | |

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

eem | Exponential Energy Marks | |

distfun | Distance Map as a Function | |

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

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

im | Create a Pixel Image Object | |

endpoints.psp | Endpoints of Line Segment Pattern | |

inforder.family | Infinite Order Interaction Family | |

integral.msr | Integral of a Measure | |

intensity | Intensity of a Dataset or a Model | |

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

envelope | Simulation Envelopes of Summary Function | |

distfun.lpp | Distance Map on Linear Network | |

insertVertices | Insert New Vertices in a Linear Network | |

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

envelopeArray | Array of Simulation Envelopes of Summary Function | |

intensity.quadratcount | Intensity Estimates Using Quadrat Counts | |

interp.colourmap | Interpolate smoothly between specified colours | |

ewcdf | Weighted Empirical Cumulative Distribution Function | |

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

dkernel | Kernel distributions and random generation | |

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

dppGauss | Gaussian Determinantal Point Process Model | |

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

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

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

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

intersect.tess | Intersection of Two Tessellations | |

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

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

kernel.squint | Integral of Squared Kernel | |

kernel.moment | Moment of Smoothing Kernel | |

is.multitype | Test whether Object is Multitype | |

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

is.marked | Test Whether Marks Are Present | |

dppMatern | Whittle-Matern Determinantal Point Process Model | |

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

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

kernel.factor | Scale factor for density kernel | |

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

erosion | Morphological Erosion by a Disc | |

eroded.areas | Areas of Morphological Erosions | |

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

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

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

flipxy | Exchange X and Y Coordinates | |

lengths.psp | Lengths of Line Segments | |

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

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

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

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

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

grow.rectangle | Add margins to rectangle | |

harmonise.im | Make Pixel Images Compatible | |

harmonise.msr | Make Measures Compatible | |

harmonic | Basis for Harmonic Functions | |

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

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

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

edge.Trans | Translation Edge Correction | |

foo | Foo is Not a Real Name | |

ellipse | Elliptical Window. | |

hextess | Hexagonal Grid or Tessellation | |

eval.fv | Evaluate Expression Involving Functions | |

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

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

lineardirichlet | Dirichlet Tessellation on a Linear Network | |

linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |

harmonise.owin | Make Windows Compatible | |

hopskel | Hopkins-Skellam Test | |

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

imcov | Spatial Covariance of a Pixel Image | |

eval.im | Evaluate Expression Involving Pixel Images | |

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

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

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

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

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

integral.im | Integral of a Pixel Image | |

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

matrixpower | Power of a Matrix | |

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

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

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

integral.linim | Integral on a Linear Network | |

intensity.ppp | Empirical Intensity of Point Pattern | |

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

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

fardist | Farthest Distance to Boundary of Window | |

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

levelset | Level Set of a Pixel Image | |

incircle | Find Largest Circle Inside Window | |

methods.linnet | Methods for Linear Networks | |

increment.fv | Increments of a Function | |

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

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

fasp.object | Function Arrays for Spatial Patterns | |

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

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

localKinhom | Inhomogeneous Neighbourhood Density Function | |

localpcf | Local pair correlation function | |

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

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

fv.object | Function Value Table | |

interp.im | Interpolate a Pixel Image | |

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

model.images | Compute Images of Constructed Covariates | |

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

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

lurking | Lurking Variable Plot | |

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

harmonise | Make Objects Compatible | |

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

linearpcf | Linear Pair Correlation Function | |

harmonise.fv | Make Function Tables Compatible | |

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

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

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

hierpair.family | Hierarchical Pairwise Interaction Process Family | |

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

linnet | Create a Linear Network | |

infline | Infinite Straight Lines | |

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

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

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

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

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

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

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

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

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

is.rectangle | Determine Type of Window | |

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

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

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

npfun | Dummy Function Returns Number of Points | |

lintess | Tessellation on a Linear Network | |

lpp | Create Point Pattern on Linear Network | |

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

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

npoints | Number of Points in a Point Pattern | |

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

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

mergeLevels | Merge Levels of a Factor | |

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

laslett | Laslett's Transform | |

pairdist.ppx | Pairwise Distances in Any Dimensions | |

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

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

kppm | Fit Cluster or Cox Point Process Model | |

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

pairdist.psp | Pairwise distances between line segments | |

marks.tess | Marks of a Tessellation | |

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

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

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

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

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

linearK | Linear K Function | |

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

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

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

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

methods.fii | Methods for Fitted Interactions | |

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

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

linequad | Quadrature Scheme on a Linear Network | |

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

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

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

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

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

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

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

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

joinVertices | Join Vertices in a Network | |

markcorr | Mark Correlation Function | |

layered | Create List of Plotting Layers | |

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

lixellate | Subdivide Segments of a Network | |

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

markcrosscorr | Mark Cross-Correlation Function | |

periodify | Make Periodic Copies of a Spatial Pattern | |

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

linearKinhom | Inhomogeneous Linear K Function | |

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

persp.im | Perspective Plot of Pixel Image | |

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

localK | Neighbourhood density function | |

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

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

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

nnclean | Nearest Neighbour Clutter Removal | |

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

lut | Lookup Tables | |

nncross | Nearest Neighbours Between Two Patterns | |

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

linfun | Function on a Linear Network | |

pixelquad | Quadrature Scheme Based on Pixel Grid | |

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

linim | Create Pixel Image on Linear Network | |

markconnect | Mark Connection Function | |

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

plot.anylist | Plot a List of Things | |

logLik.slrm | Loglikelihood of Spatial Logistic Regression | |

methods.ssf | Methods for Spatially Sampled Functions | |

methods.distfun | Geometrical Operations for Distance Functions | |

markvario | Mark Variogram | |

lohboot | Bootstrap Confidence Bands for Summary Function | |

plot.envelope | Plot a Simulation Envelope | |

nndist | Nearest neighbour distances | |

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

matchingdist | Distance for a Point Pattern Matching | |

nnwhich.ppx | Nearest Neighbours in Any Dimensions | |

methods.unitname | Methods for Units | |

plot.fasp | Plot a Function Array | |

plot.leverage.ppm | Plot Leverage Function | |

markmarkscatter | Mark-Mark Scatter Plot | |

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

plot.ppp | plot a Spatial Point Pattern | |

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

padimage | Pad the Border of a Pixel Image | |

pairdist | Pairwise distances | |

measureContinuous | Discrete and Continuous Components of a Measure | |

nnfun | Nearest Neighbour Index Map as a Function | |

marks | Marks of a Point Pattern | |

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

methods.layered | Methods for Layered Objects | |

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

pairorient | Point Pair Orientation Distribution | |

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

methods.funxy | Methods for Spatial Functions | |

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

msr | Signed or Vector-Valued Measure | |

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

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

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

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

nnwhich.pp3 | Nearest neighbours in three dimensions | |

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

nnmap | K-th Nearest Point Map | |

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

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

project2segment | Move Point To Nearest Line | |

pcfmulti | Marked pair correlation function | |

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

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

objsurf | Objective Function Surface | |

perimeter | Perimeter Length of Window | |

opening | Morphological Opening | |

pixellate | Convert Spatial Object to Pixel Image | |

methods.objsurf | Methods for Objective Function Surfaces | |

midpoints.psp | Midpoints of Line Segment Pattern | |

methods.zclustermodel | Methods for Cluster Models | |

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

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

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

nnmark | Mark of Nearest Neighbour | |

project2set | Find Nearest Point in a Region | |

owin | Create a Window | |

plot.fv | Plot Function Values | |

pairs.im | Scatterplot Matrix for Pixel Images | |

quantess | Quantile Tessellation | |

owin.object | Class owin | |

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

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

plot.hyperframe | Plot Entries in a Hyperframe | |

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

rMaternII | Simulate Matern Model II | |

rGaussPoisson | Simulate Gauss-Poisson Process | |

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

rMosaicField | Mosaic Random Field | |

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

mincontrast | Method of Minimum Contrast | |

plot.onearrow | Plot an Arrow | |

plot.quad | Plot a Spatial Quadrature Scheme | |

nnorient | Nearest Neighbour Orientation Distribution | |

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

miplot | Morisita Index Plot | |

parameters | Extract Model Parameters in Understandable Form | |

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

pairwise.family | Pairwise Interaction Process Family | |

rThomas | Simulate Thomas Process | |

plot.quadratcount | Plot Quadrat Counts | |

plot.textstring | Plot a Text String | |

nvertices | Count Number of Vertices | |

nnwhich | Nearest neighbour | |

plot.texturemap | Plot a Texture Map | |

polynom | Polynomial in One or Two Variables | |

pool | Pool Data | |

ppp.object | Class of Point Patterns | |

nearestsegment | Find Line Segment Nearest to Each Point | |

pppdist | Distance Between Two Point Patterns | |

nestsplit | Nested Split | |

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

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

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

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

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

parres | Partial Residuals for Point Process Model | |

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

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

pcf | Pair Correlation Function | |

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

plot.imlist | Plot a List of Images | |

plot.linnet | Plot a linear network | |

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

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

plot.im | Plot a Pixel Image | |

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

print.quad | Print a Quadrature Scheme | |

ord.family | Ord Interaction Process Family | |

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

rectcontact | Contact Distribution Function using Rectangular Structuring Element | |

overlap.owin | Compute Area of Overlap | |

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

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

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

rectdistmap | Distance Map Using Rectangular Distance Metric | |

plot.owin | Plot a Spatial Window | |

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

pairdist.default | Pairwise distances | |

relrisk | Estimate of Spatially-Varying Relative Risk | |

pixellate.owin | Convert Window to Pixel Image | |

pairdist.pp3 | Pairwise distances in Three Dimensions | |

pairdist.ppp | Pairwise distances | |

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

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

rMatClust | Simulate Matern Cluster Process | |

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

quad.object | Class of Quadrature Schemes | |

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

quadratcount | Quadrat counting for a point pattern | |

plot.influence.ppm | Plot Influence Measure | |

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

rlabel | Random Re-Labelling of Point Pattern | |

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

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

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

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

plot.ssf | Plot a Spatially Sampled Function | |

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

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

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

plot.listof | Plot a List of Things | |

ppm | Fit Point Process Model to Data | |

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

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

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

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

pixelcentres | Extract Pixel Centres as Point Pattern | |

pointsOnLines | Place Points Evenly Along Specified Lines | |

plot.bermantest | Plot Result of Berman Test | |

pcfinhom | Inhomogeneous Pair Correlation Function | |

plot.cdftest | Plot a Spatial Distribution Test | |

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

pppmatching | Create a Point Matching | |

plot.symbolmap | Plot a Graphics Symbol Map | |

roc | Receiver Operating Characteristic | |

polartess | Tessellation Using Polar Coordinates | |

rose | Rose Diagram | |

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

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

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

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

rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |

pppmatching.object | Class of Point Matchings | |

pool.fv | Pool Several Functions | |

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

ppp | Create a Point Pattern | |

pp3 | Three Dimensional Point Pattern | |

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

psp.object | Class of Line Segment Patterns | |

rat | Ratio object | |

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

sdr | Sufficient Dimension Reduction | |

rcell | Simulate Baddeley-Silverman Cell Process | |

pool.quadrattest | Pool Several Quadrat Tests | |

plot.tess | Plot a Tessellation | |

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

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

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

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

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

points.lpp | Draw Points on Existing Plot | |

rQuasi | Generate Quasirandom Point Pattern in Given Window | |

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

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

requireversion | Require a Specific Version of a Package | |

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

rshift | Random Shift | |

spatialcdf | Spatial Cumulative Distribution Function | |

rshift.ppp | Randomly Shift a Point Pattern | |

rescale | Convert dataset to another unit of length | |

psib | Sibling Probability of Cluster Point Process | |

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

ppx | Multidimensional Space-Time Point Pattern | |

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

psp | Create a Line Segment Pattern | |

plot.laslett | Plot Laslett Transform | |

quadrats | Divide Region into Quadrats | |

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

rmhexpand | Specify Simulation Window or Expansion Rule | |

plot.colourmap | Plot a Colour Map | |

progressreport | Print Progress Reports | |

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

rLGCP | Simulate Log-Gaussian Cox Process | |

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

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

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

rMosaicSet | Mosaic Random Set | |

rdpp | Simulation of a Determinantal Point Process | |

pool.envelope | Pool Data from Several Envelopes | |

plot.layered | Layered Plot | |

rSSI | Simulate Simple Sequential Inhibition | |

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

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

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

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

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

quantile.density | Quantiles of a Density Estimate | |

sdrPredict | Compute Predictors from Sufficient Dimension Reduction | |

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

ripras | Estimate window from points alone | |

rNeymanScott | Simulate Neyman-Scott Process | |

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

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

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

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

spatdim | Spatial Dimension of a Dataset | |

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

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

range.fv | Range of Function Values | |

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

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

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

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

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

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

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

rMaternI | Simulate Matern Model I | |

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

rgbim | Create Colour-Valued Pixel Image | |

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

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

plot.studpermutest | Plot a Studentised Permutation Test | |

rex | Richardson Extrapolation | |

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

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

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

rsyst | Simulate systematic random point pattern | |

quantile.im | Sample Quantiles of Pixel Image | |

rStrauss | Perfect Simulation of the Strauss Process | |

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

quasirandom | Quasirandom Patterns | |

scaletointerval | Rescale Data to Lie Between Specified Limits | |

rPenttinen | Perfect Simulation of the Penttinen Process | |

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

rpoislpp | Poisson Point Process on a Linear Network | |

rotate | Rotate | |

scanLRTS | Likelihood Ratio Test Statistic for Scan Test | |

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

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

rPoissonCluster | Simulate Poisson Cluster Process | |

rotmean | Rotational Average of a Pixel Image | |

rpoispp | Generate Poisson Point Pattern | |

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

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

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

rags | Alternating Gibbs Sampler for Multitype Point Processes | |

scan.test | Spatial Scan Test | |

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

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

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

rotate.im | Rotate a Pixel Image | |

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

shift.owin | Apply Vector Translation To Window | |

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

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

reflect | Reflect In Origin | |

scanpp | Read Point Pattern From Data File | |

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

scalardilate | Apply Scalar Dilation | |

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

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

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

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

rstrat | Simulate Stratified Random Point Pattern | |

rescue.rectangle | Convert Window Back To Rectangle | |

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

rmpoint | Generate N Random Multitype Points | |

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

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

rlpp | Random Points on a Linear Network | |

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

rotate.ppp | Rotate a Point Pattern | |

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

rotate.psp | Rotate a Line Segment Pattern | |

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

runiflpp | Uniform Random Points on a Linear Network | |

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

rjitter | Random Perturbation of a Point Pattern | |

slrm | Spatial Logistic Regression | |

rHardcore | Perfect Simulation of the Hardcore Process | |

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

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

solist | List of Two-Dimensional Spatial Objects | |

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

rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |

rppm | Recursively Partitioned Point Process Model | |

rpoisline | Generate Poisson Random Line Process | |

sharpen | Data Sharpening of Point Pattern | |

rknn | Theoretical Distribution of Nearest Neighbour Distance | |

rpoislinetess | Poisson Line Tessellation | |

regularpolygon | Create A Regular Polygon | |

reach | Interaction Distance of a Point Process | |

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

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

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

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

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

shift | Apply Vector Translation | |

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

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

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

rotate.infline | Rotate or Shift Infinite Lines | |

rnoise | Random Pixel Noise | |

rmpoispp | Generate Multitype Poisson Point Pattern | |

spatstat-deprecated | Deprecated spatstat functions | |

runifpoint | Generate N Uniform Random Points | |

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

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

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

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

rotate.owin | Rotate a Window | |

spatstat-internal | Internal spatstat functions | |

rounding | Detect Numerical Rounding | |

rpoint | Generate N Random Points | |

rthin | Random Thinning | |

setcov | Set Covariance of a Window | |

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

Extract.fasp | Extract Subset of Function Array | |

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

Emark | Diagnostics for random marking | |

CDF | Cumulative Distribution Function From Kernel Density Estimate | |

DiggleGratton | Diggle-Gratton model | |

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

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

AreaInter | The Area Interaction Point Process Model | |

Concom | The Connected Component Process Model | |

No Results! |

## Vignettes of spatstat

Name | ||

bugfixes.Rnw | ||

datasets.Rnw | ||

getstart.Rnw | ||

hexagon.eps | ||

hexagon.pdf | ||

irregpoly.eps | ||

irregpoly.pdf | ||

replicated.Rnw | ||

shapefiles.Rnw | ||

updates.Rnw | ||

No Results! |

## Last month downloads

## Details

Date | 2019-03-22 |

License | GPL (>= 2) |

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

LazyData | true |

NeedsCompilation | yes |

ByteCompile | true |

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

Packaged | 2019-03-22 09:59:08 UTC; adrian |

Repository | CRAN |

Date/Publication | 2019-03-22 13:40:03 UTC |

imports | abind , deldir (>= 0.0-21) , goftest , Matrix , mgcv , polyclip (>= 1.10-0) , spatstat.utils (>= 1.13-0) , 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)
```