# spatstat v1.45-0

Monthly downloads

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

Comprehensive open-source toolbox for analysing spatial data, mainly Spatial Point Patterns, including multi-type/marked points and spatial covariates, in any two-dimensional spatial region. Also supports three-dimensional point patterns, space-time point patterns in any number of dimensions, and point patterns on a linear network.
Contains 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, Diggle-Cressie-Loosmore-Ford, Dao-Genton) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov) are also supported.
Parametric models can be fitted to point pattern data using the functions ppm(), kppm(), slrm(), 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()). 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.hyperframe | Extract or Replace Subset of Hyperframe | |

Extract.im | Extract Subset of Image | |

Gcom | Model Compensator of Nearest Neighbour Function | |

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

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

Penttinen | Penttinen Interaction | |

Hybrid | Hybrid Interaction Point Process Model | |

AreaInter | The Area Interaction Point Process Model | |

Kmeasure | Reduced Second Moment Measure | |

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

Geyer | Geyer's Saturation Point Process Model | |

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

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

Finhom | Inhomogeneous Empty Space Function | |

Strauss | The Strauss Point Process Model | |

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

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

Concom | The Connected Component Process Model | |

Gres | Residual G Function | |

Jest | Estimate the J-function | |

Extract.fasp | Extract Subset of Function Array | |

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

BadGey | Hybrid Geyer Point Process Model | |

areaLoss | Difference of Disc Areas | |

CDF | Cumulative Distribution Function From Kernel Density Estimate | |

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

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

Hardcore | The Hard Core Point Process Model | |

Gest | Nearest Neighbour Distance Function G | |

Emark | Diagnostics for random marking | |

Gfox | Foxall's Distance Functions | |

Kovesi | Colour Sequences with Uniform Perceptual Contrast | |

Ord | Generic Ord Interaction model | |

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

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

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

Fiksel | The Fiksel Interaction | |

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

areaGain | Difference of Disc Areas | |

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

DiggleGratton | Diggle-Gratton model | |

MultiHard | The Multitype Hard Core Point Process Model | |

Kcross.inhom | Inhomogeneous Cross K Function | |

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

Extract.linnet | Extract Subset of Linear Network | |

Kcom | Model Compensator of K Function | |

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

Jinhom | Inhomogeneous J-function | |

Iest | Estimate the I-function | |

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

Lcross.inhom | Inhomogeneous Cross Type L Function | |

as.layered | Convert Data To Layered Object | |

Ginhom | Inhomogeneous Nearest Neighbour Function | |

Linhom | L-function | |

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

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

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

LambertW | Lambert's W Function | |

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

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

WindowOnly | Extract Window of Spatial Object | |

Softcore | The Soft Core Point Process Model | |

Ksector | Sector K-function | |

Kmulti.inhom | Inhomogeneous Marked K-Function | |

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

affine.tess | Apply Geometrical Transformation To Tessellation | |

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

Kest | K-function | |

Smooth.fv | Apply Smoothing to Function Values | |

HierStrauss | The Hierarchical Strauss Point Process Model | |

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

addvar | Added Variable Plot for Point Process Model | |

Extract.owin | Extract Subset of Window | |

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

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

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

Jmulti | Marked J Function | |

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

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

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

Extract.quad | Subset of Quadrature Scheme | |

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

Ldot.inhom | Inhomogeneous Multitype L Dot Function | |

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

affine.owin | Apply Affine Transformation To Window | |

Gmulti | Marked Nearest Neighbour Distance Function | |

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

copyExampleFiles | Copy Data Files for Example | |

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

Hest | Spherical Contact Distribution Function | |

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

angles.psp | Orientation Angles of Line Segments | |

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

bramblecanes | Hutchings' Bramble Canes data | |

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

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

Pairwise | Generic Pairwise Interaction model | |

area.owin | Area of a Window | |

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

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

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

Saturated | Saturated Pairwise Interaction model | |

Kmulti | Marked K-Function | |

LennardJones | The Lennard-Jones Potential | |

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

OrdThresh | Ord's Interaction model | |

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

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

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

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

Tstat | Third order summary statistic | |

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

bronzefilter | Bronze gradient filter data | |

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

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

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

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

amacrine | Hughes' Amacrine Cell Data | |

clusterkernel | Extract Cluster Offspring Kernel | |

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

as.psp | Convert Data To Class psp | |

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

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

Kest.fft | K-function using FFT | |

anemones | Beadlet Anemones Data | |

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

Smooth | Spatial smoothing of data | |

as.tess | Convert Data To Tessellation | |

Kinhom | Inhomogeneous K-function | |

bdist.points | Distance to Boundary of Window | |

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

betacells | Beta Ganglion Cells in Cat Retina | |

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

chorley | Chorley-Ribble Cancer Data | |

ants | Harkness-Isham ants' nests data | |

Kscaled | Locally Scaled K-function | |

as.ppp | Convert Data To Class ppp | |

as.interact | Extract Interaction Structure | |

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

Kres | Residual K Function | |

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

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

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

add.texture | Fill Plot With Texture | |

finpines | Pine saplings in Finland. | |

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

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

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

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

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

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

bei | Tropical rain forest trees | |

border | Border Region of a Window | |

hierpair.family | Hierarchical Pairwise Interaction Process Family | |

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

begins | Check Start of Character String | |

deriv.fv | Calculate Derivative of Function Values | |

bdspots | Breakdown Spots in Microelectronic Materials | |

clarkevans.test | Clark and Evans Test | |

as.owin | Convert Data To Class owin | |

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

circdensity | Density Estimation for Circular Data | |

beginner | Print Introduction For Beginners | |

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

delaunayDistance | Distance on Delaunay Triangulation | |

bind.fv | Combine Function Value Tables | |

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

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

endpoints.psp | Endpoints of Line Segment Pattern | |

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

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

auc | Area Under ROC Curve | |

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

chicago | Chicago Street Crime Data | |

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

Poisson | Poisson Point Process Model | |

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

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

as.ppm | Extract Fitted Point Process Model | |

centroid.owin | Centroid of a window | |

as.im | Convert to Pixel Image | |

clusterfield | Field of clusters | |

append.psp | Combine Two Line Segment Patterns | |

affine | Apply Affine Transformation | |

as.hyperframe | Convert Data to Hyperframe | |

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

as.rectangle | Window Frame | |

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

edges2triangles | List Triangles in a Graph | |

intensity.ppp | Empirical Intensity of Point Pattern | |

insertVertices | Insert New Vertices in a Linear Network | |

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

dppPowerExp | Power Exponential Spectral Determinantal Point Process Model | |

clickppp | Interactively Add Points | |

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

letterR | Window in Shape of Letter R | |

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

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

anylist | List of Objects | |

contour.imlist | Array of Contour Plots | |

clickbox | Interactively Define a Rectangle | |

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

austates | Australian States and Mainland Territories | |

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

boxx | Multi-Dimensional Box | |

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

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

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

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

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

clusterset | Allard-Fraley Estimator of Cluster Feature | |

convexify | Weil's Convexifying Operation | |

japanesepines | Japanese Pines Point Pattern | |

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

circumradius | Circumradius of a Window | |

corners | Corners of a rectangle | |

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

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

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

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

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

convolve.im | Convolution of Pixel Images | |

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

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

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

blur | Apply Gaussian Blur to a Pixel Image | |

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

as.fv | Convert Data To Class fv | |

Kmark | Mark-Weighted K Function | |

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

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

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

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

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

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

logLik.slrm | Loglikelihood of Spatial Logistic Regression | |

dirichlet | Dirichlet Tessellation of Point Pattern | |

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

complement.owin | Take Complement of a Window | |

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

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

closing | Morphological Closing | |

markconnect | Mark Connection Function | |

dilated.areas | Areas of Morphological Dilations | |

intensity | Intensity of a Dataset or a Model | |

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

lut | Lookup Tables | |

contour.im | Contour plot of pixel image | |

colourmap | Colour Lookup Tables | |

concatxy | Concatenate x,y Coordinate Vectors | |

deltametric | Delta Metric | |

branchlabelfun | Tree Branch Membership Labelling Function | |

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

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

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

diameter | Diameter of an Object | |

convexhull.xy | Convex Hull of Points | |

distmap | Distance Map | |

delaunay | Delaunay Triangulation of Point Pattern | |

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

dppapproxkernel | Approximate Determinantal Point Process Kernel | |

dendrite | Dendritic Spines Data | |

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

clarkevans | Clark and Evans Aggregation Index | |

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

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

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

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

dirichletVertices | Vertices and Edges of Dirichlet Tessellation | |

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

lixellate | Subdivide Segments of a Network | |

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

dirichletAreas | Compute Areas of Tiles in Dirichlet Tessellation | |

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

clmfires | Castilla-La Mancha Forest Fires | |

demohyper | Demonstration Example of Hyperframe of Spatial Data | |

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

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

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

connected | Connected components | |

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

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

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

distfun | Distance Map as a Function | |

distmap.ppp | Distance Map of Point Pattern | |

discpartarea | Area of Part of Disc | |

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

HierHard | The Hierarchical Hard Core Point Process Model | |

MultiStrauss | The Multitype Strauss Point Process Model | |

nestsplit | Nested Split | |

compareFit | Residual Diagnostics for Multiple Fitted Models | |

dppm | Fit Determinantal Point Process Model | |

closepairs | Close Pairs of Points | |

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

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

nnmap | K-th Nearest Point Map | |

pairdist.ppx | Pairwise Distances in Any Dimensions | |

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

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

copper | Berman-Huntington points and lines data | |

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

hextess | Hexagonal Grid or Tessellation | |

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

demopat | Artificial Data Point Pattern | |

funxy | Spatial Function Class | |

dfbetas.ppm | Parameter influence measure | |

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

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

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

im.object | Class of Images | |

gridcentres | Rectangular grid of points | |

crossdist | Pairwise distances | |

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

dppeigen | Internal function calculating eig and index | |

dirichletWeights | Compute Quadrature Weights Based on Dirichlet Tessellation | |

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

compatible | Test Whether Objects Are Compatible | |

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

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

colourtools | Convert and Compare Colours in Different Formats | |

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

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

distfun.lpp | Distance Map on Linear Network | |

dppMatern | Whittle-Matern Determinantal Point Process Model | |

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

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

harmonise.fv | Make Function Tables Compatible | |

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

convexhull | Convex Hull | |

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

nbfires | Point Patterns of New Brunswick Forest Fires | |

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

dilation | Morphological Dilation | |

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

edit.hyperframe | Invoke Text Editor on Hyperframe | |

methods.funxy | Methods for Spatial Functions | |

flipxy | Exchange X and Y Coordinates | |

hopskel | Hopkins-Skellam Test | |

opening | Morphological Opening | |

domain | Extract the Domain of any Spatial Object | |

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

linfun | Function on a Linear Network | |

eem | Exponential Energy Marks | |

dkernel | Kernel distributions and random generation | |

gordon | People in Gordon Square | |

edges2vees | List Dihedral Triples in a Graph | |

nndist | Nearest neighbour distances | |

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

discs | Union of Discs | |

ewcdf | Weighted Empirical Cumulative Distribution Function | |

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

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

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

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

fv.object | Function Value Table | |

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

flu | Influenza Virus Proteins | |

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

gorillas | Gorilla Nesting Sites | |

clickjoin | Interactively join vertices on a plot | |

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

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

nnfun | Nearest Neighbour Index Map as a Function | |

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

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

fryplot | Fry Plot of Point Pattern | |

distcdf | Distribution Function of Interpoint Distance | |

eroded.areas | Areas of Morphological Erosions | |

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

harmonic | Basis for Harmonic Functions | |

hyytiala | Scots pines and other trees at Hyytiala | |

eval.im | Evaluate Expression Involving Pixel Images | |

distmap.owin | Distance Map of Window | |

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

pairdist | Pairwise distances | |

envelope.envelope | Recompute Envelopes | |

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

pairdist.psp | Pairwise distances between line segments | |

objsurf | Objective Function Surface | |

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

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

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

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

imcov | Spatial Covariance of a Pixel Image | |

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

intensity.quadratcount | Intensity Estimates Using Quadrat Counts | |

heather | Diggle's Heather Data | |

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

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

bdist.tiles | Distance to Boundary of Window | |

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

diameter.owin | Diameter of a Window | |

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

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

pairorient | Point Pair Orientation Distribution | |

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

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

dppCauchy | Generalized Cauchy Determinantal Point Process Model | |

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

emend | Force Model to be Valid | |

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

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

interp.im | Interpolate a Pixel Image | |

eval.fv | Evaluate Expression Involving Functions | |

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

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

box3 | Three-Dimensional Box | |

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

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

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

lpp | Create Point Pattern on Linear Network | |

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

is.marked | Test Whether Marks Are Present | |

erosion | Morphological Erosion | |

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

fasp.object | Function Arrays for Spatial Patterns | |

levelset | Level Set of a Pixel Image | |

kernel.factor | Scale factor for density kernel | |

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

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

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

disc | Circular Window | |

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

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

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

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

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

cells | Biological Cells Point Pattern | |

longleaf | Longleaf Pines Point Pattern | |

fourierbasis | Fourier Basis Functions | |

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

harmonise | Make Objects Compatible | |

persp.im | Perspective Plot of Pixel Image | |

plot.quadratcount | Plot Quadrat Counts | |

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

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

im | Create a Pixel Image Object | |

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

plot.ppp | plot a Spatial Point Pattern | |

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

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

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

pixelcentres | Extract Pixel Centres as Point Pattern | |

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

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

pool.envelope | Pool Data from Several Envelopes | |

linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |

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

gridweights | Compute Quadrature Weights Based on Grid Counts | |

Triplets | The Triplet Point Process Model | |

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

incircle | Find Largest Circle Inside Window | |

hybrid.family | Hybrid Interaction Family | |

lansing | Lansing Woods Point Pattern | |

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

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

expand.owin | Apply Expansion Rule | |

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

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

mergeLevels | Merge Levels of a Factor | |

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

marks.tess | Marks of a Tessellation | |

dmixpois | Mixed Poisson Distribution | |

edges | Extract Boundary Edges of a Window. | |

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

nvertices | Count Number of Vertices | |

methods.zclustermodel | Methods for Cluster Models | |

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

integral.msr | Integral of a Measure | |

ellipse | Elliptical Window. | |

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

parres | Partial Residuals for Point Process Model | |

plot.anylist | Plot a List of Things | |

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

envelope | Simulation Envelopes of Summary Function | |

bdist.pixels | Distance to Boundary of Window | |

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

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

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

plot.textstring | Plot a Text String | |

padimage | Pad the Border of a Pixel Image | |

markcrosscorr | Mark Cross-Correlation Function | |

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

pyramidal | Pyramidal Neurons in Cingulate Cortex | |

print.quad | Print a Quadrature Scheme | |

integral.im | Integral of a Pixel Image | |

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

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

infline | Infinite Straight Lines | |

range.fv | Range of Function Values | |

inforder.family | Infinite Order Interaction Family | |

interp.colourmap | Interpolate smoothly between specified colours | |

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

grow.rectangle | Add margins to rectangle | |

lurking | Lurking variable plot | |

pp3 | Three Dimensional Point Pattern | |

plot.fv | Plot Function Values | |

fv | Create a Function Value Table | |

rLGCP | Simulate Log-Gaussian Cox Process | |

lengths.psp | Lengths of Line Segments | |

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

kppm | Fit Cluster or Cox Point Process Model | |

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

pcfinhom | Inhomogeneous Pair Correlation Function | |

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

clickpoly | Interactively Define a Polygon | |

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

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

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

linearKinhom | Inhomogeneous Linear K Function | |

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

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

hyperframe | Hyper Data Frame | |

lintess | Tessellation on a Linear Network | |

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

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

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

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

ord.family | Ord Interaction Process Family | |

plot.cdftest | Plot a Spatial Distribution Test | |

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

model.images | Compute Images of Constructed Covariates | |

mincontrast | Method of Minimum Contrast | |

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

dppBessel | Bessel Type Determinantal Point Process Model | |

msr | Signed or Vector-Valued Measure | |

linearK | Linear K Function | |

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

pairwise.family | Pairwise Interaction Process Family | |

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

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

npoints | Number of Points in a Point Pattern | |

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

plot.envelope | Plot a Simulation Envelope | |

linearpcf | Linear Pair Correlation Function | |

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

edge.Trans | Translation Edge Correction | |

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

linim | Create Pixel Image on Linear Network | |

methods.linnet | Methods for Linear Networks | |

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

nnclean | Nearest Neighbour Clutter Removal | |

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

foo | Foo is Not a Real Name | |

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

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

project2segment | Move Point To Nearest Line | |

rotate.owin | Rotate a Window | |

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

methods.layered | Methods for Layered Objects | |

plot.fasp | Plot a Function Array | |

sumouter | Compute Quadratic Forms | |

plot.colourmap | Plot a Colour Map | |

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

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

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

dppGauss | Gaussian Determinantal Point Process Model | |

pcfmulti | Marked pair correlation function | |

eval.fasp | Evaluate Expression Involving Function Arrays | |

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

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

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

plot.hyperframe | Plot Entries in a Hyperframe | |

intersect.tess | Intersection of Two Tessellations | |

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

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

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

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

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

npfun | Dummy Function Returns Number of Points | |

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

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

plot.listof | Plot a List of Things | |

integral.linim | Integral on a Linear Network | |

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

ppp | Create a Point Pattern | |

rcell | Simulate Baddeley-Silverman Cell Process | |

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

rQuasi | Generate Quasirandom Point Pattern in Given Window | |

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

owin.object | Class owin | |

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

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

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

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

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

plot.layered | Layered Plot | |

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

valid.detpointprocfamily | Check Validity of a Determinantal Point Process Model | |

pairdist.default | Pairwise distances | |

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

matchingdist | Distance for a Point Pattern Matching | |

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

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

methods.fii | Methods for Fitted Interactions | |

plot.onearrow | Plot an Arrow | |

markvario | Mark Variogram | |

miplot | Morisita Index Plot | |

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

perimeter | Perimeter Length of Window | |

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

rmpoint | Generate N Random Multitype Points | |

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

rotate.psp | Rotate a Line Segment Pattern | |

fardist | Farthest Distance to Boundary of Window | |

laslett | Laslett's Transform | |

rmpoispp | Generate Multitype Poisson Point Pattern | |

marks | Marks of a Point Pattern | |

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

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

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

nnmark | Mark of Nearest Neighbour | |

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

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

rThomas | Simulate Thomas Process | |

rMosaicField | Mosaic Random Field | |

rdpp | Simulation of a Determinantal Point Process | |

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

layered | Create List of Plotting Layers | |

localKinhom | Inhomogeneous Neighbourhood Density Function | |

pppmatching | Create a Point Matching | |

rpoispp | Generate Poisson Point Pattern | |

rthin | Random Thinning | |

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

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

methods.objsurf | Methods for Objective Function Surfaces | |

rat | Ratio object | |

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

midpoints.psp | Midpoints of Line Segment Pattern | |

nztrees | New Zealand Trees Point Pattern | |

pppdist | Distance Between Two Point Patterns | |

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

owin | Create a Window | |

nearestsegment | Find Line Segment Nearest to Each Point | |

rMaternII | Simulate Matern Model II | |

roc | Receiver Operating Characteristic | |

murchison | Murchison gold deposits | |

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

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

pairs.im | Scatterplot Matrix for Pixel Images | |

rpoint | Generate N Random Points | |

plot.texturemap | Plot a Texture Map | |

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

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

is.rectangle | Determine Type of Window | |

scanpp | Read Point Pattern From Data File | |

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

hamster | Aherne's hamster tumour data | |

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

methods.units | Methods for Units | |

moribund | Outdated Functions | |

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

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

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

ponderosa | Ponderosa Pine Tree Point Pattern | |

harmonise.im | Make Pixel Images Compatible | |

plot.imlist | Plot a List of Images | |

pool.fv | Pool Several Functions | |

parameters | Extract Model Parameters in Understandable Form | |

simdat | Simulated Point Pattern | |

rshift.ppp | Randomly Shift a Point Pattern | |

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

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

quantile.density | Quantiles of a Density Estimate | |

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

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

relrisk | Estimate of Spatially-Varying Relative Risk | |

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

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

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

pppmatching.object | Class of Point Matchings | |

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

markcorr | Mark Correlation Function | |

pool.quadrattest | Pool Several Quadrat Tests | |

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

nnorient | Nearest Neighbour Orientation Distribution | |

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

nncross | Nearest Neighbours Between Two Patterns | |

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

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

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

rpoislpp | Poisson Point Process on a Linear Network | |

rmhexpand | Specify Simulation Window or Expansion Rule | |

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

pcf | Pair Correlation Function | |

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

rPoissonCluster | Simulate Poisson Cluster Process | |

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

shift.owin | Apply Vector Translation To Window | |

is.multitype | Test whether Object is Multitype | |

mucosa | Cells in Gastric Mucosa | |

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

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

sharpen | Data Sharpening of Point Pattern | |

unitname | Name for Unit of Length | |

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

rPenttinen | Perfect Simulation of the Penttinen Process | |

nnwhich.pp3 | Nearest neighbours in three dimensions | |

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

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

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

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

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

pixellate.owin | Convert Window to Pixel Image | |

psp | Create a Line Segment Pattern | |

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

periodify | Make Periodic Copies of a Spatial Pattern | |

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

rMatClust | Simulate Matern Cluster Process | |

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

plot.tess | Plot a tessellation | |

spatdim | Spatial Dimension of a Dataset | |

rotmean | Rotational Average of a Pixel Image | |

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

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

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

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

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

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

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

pairdist.pp3 | Pairwise distances in Three Dimensions | |

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

rpoislinetess | Poisson Line Tessellation | |

nnwhich | Nearest neighbour | |

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

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

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

spatstat.options | Internal Options in Spatstat Package | |

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

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

harmonise.owin | Make Windows Compatible | |

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

nnwhich.ppx | Nearest Neighbours in Any Dimensions | |

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

localpcf | Local pair correlation function | |

ppp.object | Class of Point Patterns | |

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

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

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

profilepl | Profile Maximum Pseudolikelihood or AIC | |

transect.im | Pixel Values Along a Transect | |

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

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

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

Lest | L-function | |

project2set | Find Nearest Point in a Region | |

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

pixellate | Convert Spatial Object to Pixel Image | |

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

scalardilate | Apply Scalar Dilation | |

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

rpoisline | Generate Poisson Random Line Process | |

vesicles | Vesicles Data | |

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

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

rGaussPoisson | Simulate Gauss-Poisson Process | |

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

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

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

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

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

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

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

rHardcore | Perfect Simulation of the Hardcore Process | |

psp.object | Class of Line Segment Patterns | |

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

textureplot | Plot Image or Tessellation Using Texture Fill | |

plot.influence.ppm | Plot Influence Measure | |

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

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

tess | Create a Tessellation | |

progressreport | Print Progress Reports | |

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

rstrat | Simulate Stratified Random Point Pattern | |

rnoise | Random Pixel Noise | |

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

quad.object | Class of Quadrature Schemes | |

unmark | Remove Marks | |

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

tiles.empty | Check For Empty Tiles in a Tessellation | |

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

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

plot.quad | Plot a Spatial Quadrature Scheme | |

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

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

plot.laslett | Plot Laslett Transform | |

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

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

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

localK | Neighbourhood density function | |

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

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

rSSI | Simulate Simple Sequential Inhibition | |

quantess | Quantile Tessellation | |

rMosaicSet | Mosaic Random Set | |

paracou | Kimboto trees at Paracou, French Guiana | |

lohboot | Bootstrap Confidence Bands for Summary Function | |

spatstat-package | The Spatstat Package | |

quadratcount | Quadrat counting for a point pattern | |

plot.owin | Plot a Spatial Window | |

rescue.rectangle | Convert Window Back To Rectangle | |

varcount | Predicted Variance of the Number of Points | |

linnet | Create a Linear Network | |

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

quantile.im | Sample Quantiles of Pixel Image | |

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

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

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

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

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

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

rgbim | Create Colour-Valued Pixel Image | |

pointsOnLines | Place Points Evenly Along Specified Lines | |

rotate | Rotate | |

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

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

rNeymanScott | Simulate Neyman-Scott Process | |

rjitter | Random Perturbation of a Point Pattern | |

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

ppx | Multidimensional Space-Time Point Pattern | |

reflect | Reflect In Origin | |

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

ppm | Fit Point Process Model to Data | |

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

rose | Rose Diagram | |

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

rshift | Random Shift | |

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

square | Square Window | |

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

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

solist | List of Two-Dimensional Spatial Objects | |

overlap.owin | Compute Area of Overlap | |

pairdist.ppp | Pairwise distances | |

shapley | Galaxies in the Shapley Supercluster | |

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

scanLRTS | Likelihood Ratio Test Statistic for Scan Test | |

zapsmall.im | Rounding of Pixel Values | |

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

spruces | Spruces Point Pattern | |

slrm | Spatial Logistic Regression | |

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

reach | Interaction Distance of a Point Process | |

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

pixelquad | Quadrature Scheme Based on Pixel Grid | |

runifpoint | Generate N Uniform Random Points | |

thinNetwork | Remove Vertices or Segments from a Linear Network | |

subfits | Extract List of Individual Point Process Models | |

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

tileindex | Determine Which Tile Contains Each Given Point | |

rotate.ppp | Rotate a Point Pattern | |

swedishpines | Swedish Pines Point Pattern | |

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

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

setcov | Set Covariance of a Window | |

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

rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |

summary.owin | Summary of a Spatial Window | |

whist | Weighted Histogram | |

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

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

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

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

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

requireversion | Require a Specific Version of a Package | |

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

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

timed | Record the Computation Time | |

plot.bermantest | Plot Result of Berman Test | |

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

scaletointerval | Rescale Data to Lie Between Specified Limits | |

stienen | Stienen Diagram | |

scan.test | Spatial Scan Test | |

spatstat-deprecated | Deprecated spatstat functions | |

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

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

runiflpp | Uniform Random Points on a Linear Network | |

plot.leverage.ppm | Plot Leverage Function | |

plot.im | Plot a Pixel Image | |

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

plot.linnet | Plot a linear network | |

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

rescale | Convert dataset to another unit of length | |

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

spatstat-internal | Internal spatstat functions | |

rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |

tiles | Extract List of Tiles in a Tessellation | |

sporophores | Sporophores Data | |

symbolmap | Graphics Symbol Map | |

triangulate.owin | Decompose Window into Triangles | |

summary.im | Summarizing a Pixel Image | |

spatialcdf | Spatial Cumulative Distribution Function | |

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

texturemap | Texture Map | |

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

triplet.family | Triplet Interaction Family | |

pool | Pool Data | |

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

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

tilenames | Names of Tiles in a Tessellation | |

treeprune | Prune Tree to Given Level | |

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

rsyst | Simulate systematic random point pattern | |

quasirandom | Quasirandom Patterns | |

transmat | Convert Pixel Array Between Different Conventions | |

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

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

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

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

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

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

vertices | Vertices of a Window | |

rotate.im | Rotate a Pixel Image | |

stratrand | Stratified random point pattern | |

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

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

waka | Trees in Waka national park | |

suffstat | Sufficient Statistic of Point Process Model | |

plot.symbolmap | Plot a Graphics Symbol Map | |

rMaternI | Simulate Matern Model I | |

trim.rectangle | Cut margins from rectangle | |

rStrauss | Perfect Simulation of the Strauss Process | |

quadrats | Divide Region into Quadrats | |

summary.quad | Summarizing a Quadrature Scheme | |

unnormdensity | Weighted kernel smoother | |

update.detpointprocfamily | Set Parameter Values in a Determinantal Point Process Model | |

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

will.expand | Test Expansion Rule | |

ripras | Estimate window from points alone | |

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

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

rknn | Theoretical Distribution of Nearest Neighbour Distance | |

superimpose | Superimpose Several Geometric Patterns | |

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

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

urkiola | Urkiola Woods Point Pattern | |

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

studpermu.test | Studentised Permutation Test | |

spokes | Spokes pattern of dummy points | |

rlabel | Random Re-Labelling of Point Pattern | |

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

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

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

zclustermodel | Cluster Point Process Model | |

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

clickdist | Interactively Measure Distance | |

rounding | Detect Numerical Rounding | |

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

stieltjes | Compute Integral of Function Against Cumulative Distribution | |

shift | Apply Vector Translation | |

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

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

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

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

varblock | Estimate Variance of Summary Statistic by Subdivision | |

valid | Check Whether Point Process Model is Valid | |

simplenet | Simple Example of Linear Network | |

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

volume | Volume of an Object | |

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

increment.fv | Increments of a Function | |

No Results! |

## Last month downloads

## Details

Nickname | One Lakh |

Date | 2016-03-10 |

License | GPL (>= 2) |

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

LazyData | true |

NeedsCompilation | yes |

ByteCompile | true |

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

Packaged | 2016-03-10 08:47:18 UTC; adrian |

Repository | CRAN |

Date/Publication | 2016-03-10 17:55:24 |

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

depends | base (>= 3.2.2) , graphics , grDevices , methods , nlme , R (>= 3.2.2) , stats , utils |

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

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)
```