# spatstat v1.57-1

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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.fasp | Extract Subset of Function Array | |

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

Extract.linnet | Extract Subset of Linear Network | |

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

Gcom | Model Compensator of Nearest Neighbour Function | |

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

HierHard | The Hierarchical Hard Core Point Process Model | |

HierStrauss | The Hierarchical Strauss Point Process Model | |

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

Kcom | Model Compensator of K Function | |

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

Kcross.inhom | Inhomogeneous Cross K Function | |

Kres | Residual K Function | |

Kmulti.inhom | Inhomogeneous Marked K-Function | |

Ldot.inhom | Inhomogeneous Multitype L Dot Function | |

LennardJones | The Lennard-Jones Potential | |

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

Ops.msr | Arithmetic Operations on Measures | |

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

Smooth.ssf | Smooth a Spatially Sampled Function | |

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

WindowOnly | Extract Window of Spatial Object | |

Emark | Diagnostics for random marking | |

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

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

anylist | List of Objects | |

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

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

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

as.hyperframe | Convert Data to Hyperframe | |

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

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

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

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

as.ppm | Extract Fitted Point Process Model | |

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

Extract.owin | Extract Subset of Window | |

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

as.ppp | Convert Data To Class ppp | |

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

auc | Area Under ROC Curve | |

bc.ppm | Bias Correction for Fitted Model | |

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

blur | Apply Gaussian Blur to a Pixel Image | |

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

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

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

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

Gest | Nearest Neighbour Distance Function G | |

Jest | Estimate the J-function | |

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

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

Kinhom | Inhomogeneous K-function | |

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

Ginhom | Inhomogeneous Nearest Neighbour Function | |

Gmulti | Marked Nearest Neighbour Distance Function | |

Kmark | Mark-Weighted K Function | |

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

Kest | K-function | |

Kmulti | Marked K-Function | |

Kest.fft | K-function using FFT | |

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

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

clicklpp | Interactively Add Points on a Linear Network | |

MinkowskiSum | Minkowski Sum of Windows | |

Kscaled | Locally Scaled K-function | |

Ksector | Sector K-function | |

clickpoly | Interactively Define a Polygon | |

MultiHard | The Multitype Hard Core Point Process Model | |

MultiStrauss | The Multitype Strauss Point Process Model | |

Saturated | Saturated Pairwise Interaction model | |

Lcross.inhom | Inhomogeneous Cross Type L Function | |

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

Smooth | Spatial smoothing of data | |

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

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

Pairwise | Generic Pairwise Interaction model | |

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

contour.im | Contour plot of pixel image | |

Penttinen | Penttinen Interaction | |

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

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

Smooth.fv | Apply Smoothing to Function Values | |

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

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

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

CDF | Cumulative Distribution Function From Kernel Density Estimate | |

Softcore | The Soft Core Point Process Model | |

Concom | The Connected Component Process Model | |

contour.imlist | Array of Contour Plots | |

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

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

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

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

BadGey | Hybrid Geyer Point Process Model | |

AreaInter | The Area Interaction Point Process Model | |

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

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

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

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

DiggleGratton | Diggle-Gratton model | |

[.ssf | Subset of spatially sampled function | |

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

distfun.lpp | Distance Map on Linear Network | |

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

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

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

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

append.psp | Combine Two Line Segment Patterns | |

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

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

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

dppMatern | Whittle-Matern Determinantal Point Process Model | |

disc | Circular Window | |

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

affine.owin | Apply Affine Transformation To Window | |

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

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

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

Finhom | Inhomogeneous Empty Space Function | |

FmultiInhom | Inhomogeneous Marked F-Function | |

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

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

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

areaLoss | Difference of Disc Areas | |

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

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

Extract.im | Extract Subset of Image | |

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

Hardcore | The Hard Core Point Process Model | |

discpartarea | Area of Part of Disc | |

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

Extract.quad | Subset of Quadrature Scheme | |

distmap | Distance Map | |

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

fasp.object | Function Arrays for Spatial Patterns | |

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

Fiksel | The Fiksel Interaction | |

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

Hest | Spherical Contact Distribution Function | |

envelope.envelope | Recompute Envelopes | |

dppPowerExp | Power Exponential Spectral Determinantal Point Process Model | |

as.fv | Convert Data To Class fv | |

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

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

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

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

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

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

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

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

Geyer | Geyer's Saturation Point Process Model | |

edges | Extract Boundary Edges of a Window. | |

as.tess | Convert Data To Tessellation | |

as.im | Convert to Pixel Image | |

Gfox | Foxall's Distance Functions | |

GmultiInhom | Inhomogeneous Marked G-Function | |

as.interact | Extract Interaction Structure | |

Gres | Residual G Function | |

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

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

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

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

Iest | Estimate the I-function | |

envelope | Simulation Envelopes of Summary Function | |

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

Jinhom | Inhomogeneous J-function | |

Jmulti | Marked J Function | |

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

Kmeasure | Reduced Second Moment Measure | |

edge.Trans | Translation Edge Correction | |

as.psp | Convert Data To Class psp | |

as.rectangle | Window Frame | |

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

bdist.pixels | Distance to Boundary of Window | |

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

bdist.points | Distance to Boundary of Window | |

Hybrid | Hybrid Interaction Point Process Model | |

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

LambertW | Lambert's W Function | |

laslett | Laslett's Transform | |

bind.fv | Combine Function Value Tables | |

imcov | Spatial Covariance of a Pixel Image | |

branchlabelfun | Tree Branch Membership Labelling Function | |

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

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

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

box3 | Three-Dimensional Box | |

bugfixes | List Recent Bug Fixes | |

Ord | Generic Ord Interaction model | |

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

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

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

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

OrdThresh | Ord's Interaction model | |

Poisson | Poisson Point Process Model | |

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

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

colourmap | Colour Lookup Tables | |

Triplets | The Triplet Point Process Model | |

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

harmonise.owin | Make Windows Compatible | |

circdensity | Density Estimation for Circular Data | |

Tstat | Third order summary statistic | |

Lest | L-function | |

clarkevans | Clark and Evans Aggregation Index | |

Linhom | L-function | |

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

closepairs | Close Pairs of Points | |

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

Strauss | The Strauss Point Process Model | |

concatxy | Concatenate x,y Coordinate Vectors | |

affine.tess | Apply Geometrical Transformation To Tessellation | |

kppm | Fit Cluster or Cox Point Process Model | |

connected | Connected components | |

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

closetriples | Close Triples of Points | |

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

closing | Morphological Closing | |

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

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

grow.rectangle | Add margins to rectangle | |

covering | Cover Region with Discs | |

addvar | Added Variable Plot for Point Process Model | |

crossdist | Pairwise distances | |

harmonise.msr | Make Measures Compatible | |

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

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

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

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

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

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

compareFit | Residual Diagnostics for Multiple Fitted Models | |

affine | Apply Affine Transformation | |

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

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

area.owin | Area of a Window | |

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

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

deriv.fv | Calculate Derivative of Function Values | |

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

im | Create a Pixel Image Object | |

lixellate | Subdivide Segments of a Network | |

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

angles.psp | Orientation Angles of Line Segments | |

im.object | Class of Images | |

areaGain | Difference of Disc Areas | |

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

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

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

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

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

integral.im | Integral of a Pixel Image | |

as.layered | Convert Data To Layered Object | |

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

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

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

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

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

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

dirichlet | Dirichlet Tessellation of Point Pattern | |

dirichletAreas | Compute Areas of Tiles in Dirichlet Tessellation | |

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

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

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

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

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

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

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

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

localKinhom | Inhomogeneous Neighbourhood Density Function | |

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

delaunay | Delaunay Triangulation of Point Pattern | |

gridweights | Compute Quadrature Weights Based on Grid Counts | |

lengths.psp | Lengths of Line Segments | |

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

levelset | Level Set of a Pixel Image | |

border | Border Region of a Window | |

discs | Union of Discs | |

methods.distfun | Geometrical Operations for Distance Functions | |

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

methods.linnet | Methods for Linear Networks | |

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

markvario | Mark Variogram | |

nnwhich.ppx | Nearest Neighbours in Any Dimensions | |

dppBessel | Bessel Type Determinantal Point Process Model | |

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

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

delaunayDistance | Distance on Delaunay Triangulation | |

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

dppCauchy | Generalized Cauchy Determinantal Point Process Model | |

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

deltametric | Delta Metric | |

as.owin | Convert Data To Class owin | |

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

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

add.texture | Fill Plot With Texture | |

nnclean | Nearest Neighbour Clutter Removal | |

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

gridcentres | Rectangular grid of points | |

dppapproxkernel | Approximate Determinantal Point Process Kernel | |

localK | Neighbourhood density function | |

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

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

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

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

clarkevans.test | Clark and Evans Test | |

dppGauss | Gaussian Determinantal Point Process Model | |

clickbox | Interactively Define a Rectangle | |

endpoints.psp | Endpoints of Line Segment Pattern | |

dppm | Fit Determinantal Point Process Model | |

midpoints.psp | Midpoints of Line Segment Pattern | |

localpcf | Local pair correlation function | |

beginner | Print Introduction For Beginners | |

clusterkernel | Extract Cluster Offspring Kernel | |

begins | Check Start of Character String | |

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

foo | Foo is Not a Real Name | |

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

boundingcircle | Smallest Enclosing Circle | |

lurking | Lurking Variable Plot | |

kernel.factor | Scale factor for density kernel | |

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

lut | Lookup Tables | |

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

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

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

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

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

centroid.owin | Centroid of a window | |

markconnect | Mark Connection Function | |

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

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

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

hyperframe | Hyper Data Frame | |

mincontrast | Method of Minimum Contrast | |

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

colourtools | Convert and Compare Colours in Different Formats | |

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

bdist.tiles | Distance to Boundary of Window | |

clickdist | Interactively Measure Distance | |

eem | Exponential Energy Marks | |

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

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

clickjoin | Interactively join vertices on a plot | |

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

clusterfield | Field of clusters | |

convexify | Weil's Convexifying Operation | |

compatible | Test Whether Objects Are Compatible | |

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

pairdist.pp3 | Pairwise distances in Three Dimensions | |

convolve.im | Convolution of Pixel Images | |

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

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

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

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

dfbetas.ppm | Parameter Influence Measure | |

intensity | Intensity of a Dataset or a Model | |

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

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

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

complement.owin | Take Complement of a Window | |

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

clusterset | Allard-Fraley Estimator of Cluster Feature | |

boxx | Multi-Dimensional Box | |

clickppp | Interactively Add Points | |

eroded.areas | Areas of Morphological Erosions | |

nestsplit | Nested Split | |

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

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

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

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

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

convexhull | Convex Hull | |

eval.im | Evaluate Expression Involving Pixel Images | |

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

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

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

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

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

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

convexhull.xy | Convex Hull of Points | |

ellipse | Elliptical Window. | |

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

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

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

dilation | Morphological Dilation | |

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

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

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

dimhat | Estimate Dimension of Central Subspace | |

emend | Force Model to be Valid | |

envelopeArray | Array of Simulation Envelopes of Summary Function | |

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

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

distmap.owin | Distance Map of Window | |

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

distmap.ppp | Distance Map of Point Pattern | |

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

dkernel | Kernel distributions and random generation | |

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

eval.fv | Evaluate Expression Involving Functions | |

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

plot.ssf | Plot a Spatially Sampled Function | |

pp3 | Three Dimensional Point Pattern | |

insertVertices | Insert New Vertices in a Linear Network | |

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

dilated.areas | Areas of Morphological Dilations | |

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

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

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

diameter.owin | Diameter of a Window | |

linearKinhom | Inhomogeneous Linear K Function | |

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

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

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

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

dmixpois | Mixed Poisson Distribution | |

dppeigen | Internal function calculating eig and index | |

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

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

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

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

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

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

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

hybrid.family | Hybrid Interaction Family | |

linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |

nnwhich.pp3 | Nearest neighbours in three dimensions | |

erosionAny | Morphological Erosion of Windows | |

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

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

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

harmonise.fv | Make Function Tables Compatible | |

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

edges2triangles | List Triangles in a Graph | |

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

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

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

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

infline | Infinite Straight Lines | |

edges2vees | List Dihedral Triples in a Graph | |

edit.hyperframe | Invoke Text Editor on Hyperframe | |

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

intersect.tess | Intersection of Two Tessellations | |

npoints | Number of Points in a Point Pattern | |

kernel.moment | Moment of Smoothing Kernel | |

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

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

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

harmonise.im | Make Pixel Images Compatible | |

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

corners | Corners of a rectangle | |

eval.fasp | Evaluate Expression Involving Function Arrays | |

rat | Ratio object | |

plot.listof | Plot a List of Things | |

intensity.quadratcount | Intensity Estimates Using Quadrat Counts | |

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

expand.owin | Apply Expansion Rule | |

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

methods.fii | Methods for Fitted Interactions | |

hopskel | Hopkins-Skellam Test | |

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

is.marked | Test Whether Marks Are Present | |

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

marks | Marks of a Point Pattern | |

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

is.rectangle | Determine Type of Window | |

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

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

fourierbasis | Fourier Basis Functions | |

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

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

increment.fv | Increments of a Function | |

plot.im | Plot a Pixel Image | |

pairwise.family | Pairwise Interaction Process Family | |

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

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

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

markcrosscorr | Mark Cross-Correlation Function | |

fardist | Farthest Distance to Boundary of Window | |

pixelquad | Quadrature Scheme Based on Pixel Grid | |

linearK | Linear K Function | |

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

harmonic | Basis for Harmonic Functions | |

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

linnet | Create a Linear Network | |

dirichletVertices | Vertices and Edges of Dirichlet Tessellation | |

msr | Signed or Vector-Valued Measure | |

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

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

plot.hyperframe | Plot Entries in a Hyperframe | |

diameter | Diameter of an Object | |

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

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

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

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

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

methods.zclustermodel | Methods for Cluster Models | |

flipxy | Exchange X and Y Coordinates | |

rPoissonCluster | Simulate Poisson Cluster Process | |

plot.tess | Plot a Tessellation | |

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

erosion | Morphological Erosion by a Disc | |

fv | Create a Function Value Table | |

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

markcorr | Mark Correlation Function | |

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

fryplot | Fry Plot of Point Pattern | |

ppm | Fit Point Process Model to Data | |

distcdf | Distribution Function of Interpoint Distance | |

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

methods.funxy | Methods for Spatial Functions | |

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

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

plot.textstring | Plot a Text String | |

intensity.ppp | Empirical Intensity of Point Pattern | |

plot.ppp | plot a Spatial Point Pattern | |

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

fv.object | Function Value Table | |

dirichletWeights | Compute Quadrature Weights Based on Dirichlet Tessellation | |

project2segment | Move Point To Nearest Line | |

kernel.squint | Integral of Squared Kernel | |

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

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

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

rags | Alternating Gibbs Sampler for Multitype Point Processes | |

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

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

opening | Morphological Opening | |

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

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

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

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

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

hextess | Hexagonal Grid or Tessellation | |

pcf | Pair Correlation Function | |

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

domain | Extract the Domain of any Spatial Object | |

hierpair.family | Hierarchical Pairwise Interaction Process Family | |

distfun | Distance Map as a Function | |

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

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

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

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

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

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

matrixpower | Power of a Matrix | |

layered | Create List of Plotting Layers | |

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

interp.im | Interpolate a Pixel Image | |

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

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

is.multitype | Test whether Object is Multitype | |

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

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

incircle | Find Largest Circle Inside Window | |

linim | Create Pixel Image on Linear Network | |

nnmap | K-th Nearest Point Map | |

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

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

plot.laslett | Plot Laslett Transform | |

quantile.density | Quantiles of a Density Estimate | |

interp.colourmap | Interpolate smoothly between specified colours | |

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

ewcdf | Weighted Empirical Cumulative Distribution Function | |

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

lintess | Tessellation on a Linear Network | |

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

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

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

joinVertices | Join Vertices in a Network | |

nnmark | Mark of Nearest Neighbour | |

lpp | Create Point Pattern on Linear Network | |

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

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

project2set | Find Nearest Point in a Region | |

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

linequad | Quadrature Scheme on a Linear Network | |

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

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

rotate.infline | Rotate or Shift Infinite Lines | |

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

parres | Partial Residuals for Point Process Model | |

model.images | Compute Images of Constructed Covariates | |

funxy | Spatial Function Class | |

lineardirichlet | Dirichlet Tessellation on a Linear Network | |

nnwhich | Nearest neighbour | |

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

perimeter | Perimeter Length of Window | |

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

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

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

linfun | Function on a Linear Network | |

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

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

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

mergeLevels | Merge Levels of a Factor | |

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

harmonise | Make Objects Compatible | |

periodify | Make Periodic Copies of a Spatial Pattern | |

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

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

ord.family | Ord Interaction Process Family | |

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

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

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

rHardcore | Perfect Simulation of the Hardcore Process | |

integral.linim | Integral on a Linear Network | |

plot.cdftest | Plot a Spatial Distribution Test | |

pairs.im | Scatterplot Matrix for Pixel Images | |

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

owin | Create a Window | |

plot.envelope | Plot a Simulation Envelope | |

rPenttinen | Perfect Simulation of the Penttinen Process | |

matchingdist | Distance for a Point Pattern Matching | |

rmpoint | Generate N Random Multitype Points | |

rlpp | Random Points on a Linear Network | |

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

nvertices | Count Number of Vertices | |

shift.owin | Apply Vector Translation To Window | |

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

relrisk | Estimate of Spatially-Varying Relative Risk | |

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

pairdist.psp | Pairwise distances between line segments | |

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

pairdist.default | Pairwise distances | |

lohboot | Bootstrap Confidence Bands for Summary Function | |

rotate.owin | Rotate a Window | |

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

polynom | Polynomial in One or Two Variables | |

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

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

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

methods.layered | Methods for Layered Objects | |

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

rthin | Random Thinning | |

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

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

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

methods.unitname | Methods for Units | |

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

rounding | Detect Numerical Rounding | |

rGaussPoisson | Simulate Gauss-Poisson Process | |

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

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

nndist | Nearest neighbour distances | |

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

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

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

rlabel | Random Re-Labelling of Point Pattern | |

plot.symbolmap | Plot a Graphics Symbol Map | |

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

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

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

pixelcentres | Extract Pixel Centres as Point Pattern | |

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

logLik.slrm | Loglikelihood of Spatial Logistic Regression | |

pool.quadrattest | Pool Several Quadrat Tests | |

inforder.family | Infinite Order Interaction Family | |

methods.ssf | Methods for Spatially Sampled Functions | |

rNeymanScott | Simulate Neyman-Scott Process | |

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

plot.colourmap | Plot a Colour Map | |

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

npfun | Dummy Function Returns Number of Points | |

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

nnfun | Nearest Neighbour Index Map as a Function | |

pixellate.owin | Convert Window to Pixel Image | |

pairdist | Pairwise distances | |

rLGCP | Simulate Log-Gaussian Cox Process | |

plot.layered | Layered Plot | |

rMosaicSet | Mosaic Random Set | |

integral.msr | Integral of a Measure | |

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

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

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

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

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

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

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

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

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

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

nnorient | Nearest Neighbour Orientation Distribution | |

padimage | Pad the Border of a Pixel Image | |

owin.object | Class owin | |

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

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

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

plot.leverage.ppm | Plot Leverage Function | |

plot.texturemap | Plot a Texture Map | |

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

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

quad.object | Class of Quadrature Schemes | |

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

ppx | Multidimensional Space-Time Point Pattern | |

plot.studpermutest | Plot a Studentised Permutation Test | |

persp.im | Perspective Plot of Pixel Image | |

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

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

psp.object | Class of Line Segment Patterns | |

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

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

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

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

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

rotate.ppp | Rotate a Point Pattern | |

psp | Create a Line Segment Pattern | |

pool | Pool Data | |

quasirandom | Quasirandom Patterns | |

plot.linnet | Plot a linear network | |

rectdistmap | Distance Map Using Rectangular Distance Metric | |

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

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

quantile.im | Sample Quantiles of Pixel Image | |

linearpcf | Linear Pair Correlation Function | |

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

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

print.quad | Print a Quadrature Scheme | |

psib | Sibling Probability of Cluster Point Process | |

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

pppmatching | Create a Point Matching | |

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

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

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

rcell | Simulate Baddeley-Silverman Cell Process | |

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

nncross | Nearest Neighbours Between Two Patterns | |

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

rpoisline | Generate Poisson Random Line Process | |

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

rSSI | Simulate Simple Sequential Inhibition | |

ppp | Create a Point Pattern | |

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

requireversion | Require a Specific Version of a Package | |

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

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

rpoislinetess | Poisson Line Tessellation | |

measureContinuous | Discrete and Continuous Components of a Measure | |

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

overlap.owin | Compute Area of Overlap | |

pppmatching.object | Class of Point Matchings | |

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

rpoint | Generate N Random Points | |

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

rThomas | Simulate Thomas Process | |

pairorient | Point Pair Orientation Distribution | |

pcfinhom | Inhomogeneous Pair Correlation Function | |

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

ppp.object | Class of Point Patterns | |

marks.tess | Marks of a Tessellation | |

nearestsegment | Find Line Segment Nearest to Each Point | |

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

plot.fasp | Plot a Function Array | |

objsurf | Objective Function Surface | |

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

pairdist.ppp | Pairwise distances | |

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

plot.onearrow | Plot an Arrow | |

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

pcfmulti | Marked pair correlation function | |

quadrats | Divide Region into Quadrats | |

miplot | Morisita Index Plot | |

points.lpp | Draw Points on Existing Plot | |

pixellate | Convert Spatial Object to Pixel Image | |

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

rQuasi | Generate Quasirandom Point Pattern in Given Window | |

roc | Receiver Operating Characteristic | |

methods.objsurf | Methods for Objective Function Surfaces | |

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

rmpoispp | Generate Multitype Poisson Point Pattern | |

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

rescale | Convert dataset to another unit of length | |

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

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

rectcontact | Contact Distribution Function using Rectangular Structuring Element | |

rknn | Theoretical Distribution of Nearest Neighbour Distance | |

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

rjitter | Random Perturbation of a Point Pattern | |

rex | Richardson Extrapolation | |

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

rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |

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

plot.fv | Plot Function Values | |

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

rmhexpand | Specify Simulation Window or Expansion Rule | |

rotate.psp | Rotate a Line Segment Pattern | |

plot.quad | Plot a Spatial Quadrature Scheme | |

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

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

rose | Rose Diagram | |

rppm | Recursively Partitioned Point Process Model | |

pool.envelope | Pool Data from Several Envelopes | |

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

solist | List of Two-Dimensional Spatial Objects | |

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

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

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

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

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

plot.imlist | Plot a List of Images | |

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

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

pairdist.ppx | Pairwise Distances in Any Dimensions | |

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

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

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

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

pppdist | Distance Between Two Point Patterns | |

scalardilate | Apply Scalar Dilation | |

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

plot.owin | Plot a Spatial Window | |

shift | Apply Vector Translation | |

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

parameters | Extract Model Parameters in Understandable Form | |

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

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

rMaternII | Simulate Matern Model II | |

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

plot.bermantest | Plot Result of Berman Test | |

plot.anylist | Plot a List of Things | |

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

range.fv | Range of Function Values | |

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

regularpolygon | Create A Regular Polygon | |

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

rnoise | Random Pixel Noise | |

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

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

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

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

rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |

rStrauss | Perfect Simulation of the Strauss Process | |

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

rgbim | Create Colour-Valued Pixel Image | |

plot.influence.ppm | Plot Influence Measure | |

sdr | Sufficient Dimension Reduction | |

plot.quadratcount | Plot Quadrat Counts | |

spatialcdf | Spatial Cumulative Distribution Function | |

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

runiflpp | Uniform Random Points on a Linear Network | |

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

runifpoint | Generate N Uniform Random Points | |

pool.fv | Pool Several Functions | |

spatdim | Spatial Dimension of a Dataset | |

sdrPredict | Compute Predictors from Sufficient Dimension Reduction | |

rMosaicField | Mosaic Random Field | |

quadratcount | Quadrat counting for a point pattern | |

progressreport | Print Progress Reports | |

pointsOnLines | Place Points Evenly Along Specified Lines | |

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

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

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

reflect | Reflect In Origin | |

rstrat | Simulate Stratified Random Point Pattern | |

rMatClust | Simulate Matern Cluster Process | |

quantess | Quantile Tessellation | |

rotate | Rotate | |

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

reach | Interaction Distance of a Point Process | |

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

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

rdpp | Simulation of a Determinantal Point Process | |

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

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

setcov | Set Covariance of a Window | |

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

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

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

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

scaletointerval | Rescale Data to Lie Between Specified Limits | |

rpoislpp | Poisson Point Process on a Linear Network | |

rMaternI | Simulate Matern Model I | |

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

rshift | Random Shift | |

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

rotate.im | Rotate a Pixel Image | |

rescue.rectangle | Convert Window Back To Rectangle | |

rotmean | Rotational Average of a Pixel Image | |

slrm | Spatial Logistic Regression | |

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

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

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

ripras | Estimate window from points alone | |

rshift.ppp | Randomly Shift a Point Pattern | |

scan.test | Spatial Scan Test | |

sharpen | Data Sharpening of Point Pattern | |

rsyst | Simulate systematic random point pattern | |

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

scanLRTS | Likelihood Ratio Test Statistic for Scan Test | |

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

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

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

rpoispp | Generate Poisson Point Pattern | |

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

scanpp | Read Point Pattern From Data File | |

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

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

simulate.slrm | Simulate a Fitted Spatial Logistic Regression 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 | 2018-11-03 |

License | GPL (>= 2) |

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

LazyData | true |

NeedsCompilation | yes |

ByteCompile | true |

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

Packaged | 2018-11-03 04:19:28 UTC; adrian |

Repository | CRAN |

Date/Publication | 2018-11-04 17:10:03 UTC |

imports | abind , deldir (>= 0.0-21) , goftest , Matrix , mgcv , polyclip (>= 1.5-0) , 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

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