spatstat v1.38-0
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Spatial Point Pattern analysis, model-fitting, simulation, tests
A package for analysing spatial data, mainly Spatial Point Patterns, including multitype/marked points and spatial covariates, in any two-dimensional spatial region. Also supports three-dimensional point patterns, space-time point patterns in any number of dimensions, and point patterns on a linear network.
Contains about 2000 functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference.
Data types include point patterns, line segment patterns, spatial windows, pixel images, tessellations, and linear networks.
Exploratory methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Diggle-Cressie-Loosmore-Ford, Dao-Genton) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov) are also supported.
Parametric models can be fitted to point pattern data using the functions ppm, kppm, slrm similar to glm. Types of models include Poisson, Gibbs, Cox and cluster point processes. Models may involve dependence on covariates, interpoint interaction, cluster formation and dependence on marks. Models are fitted by maximum likelihood, logistic regression, minimum contrast, and composite likelihood methods.
Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise, AIC). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots.
Functions in spatstat
| Name | Description | |
| im.object | Class of Images | |
| intensity.lpp | Empirical Intensity of Point Pattern on Linear Network | |
| inside.owin | Test Whether Points Are Inside A Window | |
| is.empty | Test Whether An Object Is Empty | |
| lengths.psp | Lengths of Line Segments | |
| linearpcfdot | Multitype Pair Correlation Function (Dot-type) for Linear Point Pattern | |
| rMaternI | Simulate Matern Model I | |
| simplify.owin | Approximate a Polygon by a Simpler Polygon | |
| linearpcf | Linear Pair Correlation Function | |
| spatstat.options | Internal Options in Spatstat Package | |
| simba | Simulated data from a two-group experiment with replication within each group. | |
| imcov | Spatial Covariance of a Pixel Image | |
| summary.listof | Summary of a List of Things | |
| improve.kppm | Improve Intensity Estimate of Fitted Cluster Point Process Model | |
| split.ppp | Divide Point Pattern into Sub-patterns | |
| raster.x | Cartesian Coordinates for a Pixel Raster | |
| rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |
| rMaternII | Simulate Matern Model II | |
| scalardilate | Apply Scalar Dilation | |
| runifpointOnLines | Generate N Uniform Random Points On Line Segments | |
| rotate.im | Rotate a Pixel Image | |
| solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
| rNeymanScott | Simulate Neyman-Scott Process | |
| texturemap | Texture Map | |
| square | Square Window | |
| addvar | Added Variable Plot for Point Process Model | |
| as.im | Convert to Pixel Image | |
| rSSI | Simulate Simple Sequential Inhibition | |
| reflect | Reflect In Origin | |
| intensity.ppp | Empirical Intensity of Point Pattern | |
| rjitter | Random Perturbation of a Point Pattern | |
| urkiola | Urkiola Woods Point Pattern | |
| Triplets | The Triplet Point Process Model | |
| Kdot | Multitype K Function (i-to-any) | |
| intersect.owin | Intersection, Union or Set Subtraction of Two Windows | |
| integral.msr | Integral of a Measure | |
| unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
| scanpp | Read Point Pattern From Data File | |
| letterR | Window in Shape of Letter R | |
| rcell | Simulate Baddeley-Silverman Cell Process | |
| rlabel | Random Re-Labelling of Point Pattern | |
| linearmarkconnect | Mark Connection Function for Multitype Point Pattern on Linear Network | |
| infline | Infinite Straight Lines | |
| suffstat | Sufficient Statistic of Point Process Model | |
| sessionLibs | Print Names and Version Numbers of Libraries Loaded | |
| lineardisc | Compute Disc of Given Radius in Linear Network | |
| linearmarkequal | Mark Connection Function for Multitype Point Pattern on Linear Network | |
| rmpoispp | Generate Multitype Poisson Point Pattern | |
| is.dppm | Recognise Fitted Determinantal Point Process Models | |
| im.apply | Apply Function Pixelwise to List of Images | |
| valid.ppm | Check Whether Point Process Model is Valid | |
| rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
| Jest | Estimate the J-function | |
| superimpose | Superimpose Several Geometric Patterns | |
| invoke.symbolmap | Plot Data Using Graphics Symbol Map | |
| leverage.ppm | Leverage Measure for Spatial Point Process Model | |
| unitname | Name for Unit of Length | |
| intensity.quadratcount | Intensity Estimates Using Quadrat Counts | |
| Gfox | Foxall's Distance Functions | |
| is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
| selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
| integral.im | Integral of a Pixel Image | |
| model.images | Compute Images of Constructed Covariates | |
| rstrat | Simulate Stratified Random Point Pattern | |
| Extract.fv | Extract Subset of Function Values | |
| nndist.pp3 | Nearest neighbour distances in three dimensions | |
| im | Create a Pixel Image Object | |
| murchison | Murchison gold deposits | |
| linim | Create Pixel Image on Linear Network | |
| mppm | Fit Point Process Model to Several Point Patterns | |
| Extract.quad | Subset of Quadrature Scheme | |
| rVarGamma | Simulate Neyman-Scott Point Process with Variance Gamma cluster kernel | |
| Extract.ppx | Extract Subset of Multidimensional Point Pattern | |
| chorley | Chorley-Ribble Cancer Data | |
| is.hybrid | Test Whether Object is a Hybrid | |
| rho2hat | Smoothed Relative Density of Pairs of Covariate Values | |
| Gmulti | Marked Nearest Neighbour Distance Function | |
| pairdist.psp | Pairwise distances between line segments | |
| model.depends | Identify Covariates Involved in each Model Term | |
| domain | Extract the Domain of any Spatial Object | |
| intensity.ppm | Intensity of Fitted Point Process Model | |
| iplot | Point and Click Interface for Displaying Spatial Data | |
| affine.tess | Apply Geometrical Transformation To Tessellation | |
| influence.ppm | Influence Measure for Spatial Point Process Model | |
| is.multitype | Test whether Object is Multitype | |
| lpp | Create Point Pattern on Linear Network | |
| ord.family | Ord Interaction Process Family | |
| localK | Neighbourhood density function | |
| nearest.raster.point | Find Pixel Nearest to a Given Point | |
| km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
| methods.slrm | Methods for Spatial Logistic Regression Models | |
| paracou | Kimboto trees at Paracou, French Guiana | |
| midpoints.psp | Midpoints of Line Segment Pattern | |
| nnwhich.pp3 | Nearest neighbours in three dimensions | |
| simulate.kppm | Simulate a Fitted Cluster Point Process Model | |
| shapley | Galaxies in the Shapley Supercluster | |
| Extract.ppp | Extract or Replace Subset of Point Pattern | |
| SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model | |
| reload.or.compute | Compute Unless Previously Saved | |
| is.ppp | Test Whether An Object Is A Point Pattern | |
| Ldot | Multitype L-function (i-to-any) | |
| is.marked.ppm | Test Whether A Point Process Model is Marked | |
| is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
| residuals.ppm | Residuals for Fitted Point Process Model | |
| scanLRTS | Likelihood Ratio Test Statistic for Scan Test | |
| Extract.leverage.ppm | Extract Subset of Leverage Object | |
| marks.psp | Marks of a Line Segment Pattern | |
| nnwhich | Nearest neighbour | |
| duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
| interp.im | Interpolate a Pixel Image | |
| swedishpines | Swedish Pines Point Pattern | |
| methods.linfun | Methods for Functions on Linear Network | |
| nndist.lpp | Nearest neighbour distances on a linear network | |
| nsegments | Number of Line Segments in a Line Segment Pattern | |
| fv | Create a Function Value Table | |
| matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
| intersect.tess | Intersection of Two Tessellations | |
| logLik.ppm | Log Likelihood and AIC for Point Process Model | |
| rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |
| affine.owin | Apply Affine Transformation To Window | |
| bdist.tiles | Distance to Boundary of Window | |
| simulate.ppm | Simulate a Fitted Gibbs Point Process Model | |
| intensity | Intensity of a Dataset or a Model | |
| linfun | Function on a Linear Network | |
| rLGCP | Simulate Log-Gaussian Cox Process | |
| tiles | Extract List of Tiles in a Tessellation | |
| bind.fv | Combine Function Value Tables | |
| Extract.fasp | Extract Subset of Function Array | |
| methods.lpp | Methods for Point Patterns on a Linear Network | |
| rPoissonCluster | Simulate Poisson Cluster Process | |
| rat | Ratio object | |
| Lcross.inhom | Inhomogeneous Cross Type L Function | |
| istat | Point and Click Interface for Exploratory Analysis of Point Pattern | |
| Lcross | Multitype L-function (cross-type) | |
| superimpose.lpp | Superimpose Several Point Patterns on Linear Network | |
| eval.im | Evaluate Expression Involving Pixel Images | |
| rMosaicSet | Mosaic Random Set | |
| rmh.ppm | Simulate from a Fitted Point Process Model | |
| shift.ppp | Apply Vector Translation To Point Pattern | |
| tess | Create a Tessellation | |
| cells | Biological Cells Point Pattern | |
| with.fv | Evaluate an Expression in a Function Table | |
| nnfun.lpp | Nearest Neighbour Map on Linear Network | |
| rQuasi | Generate Quasirandom Point Pattern in Given Window | |
| Tstat | Third order summary statistic | |
| symbolmap | Graphics Symbol Map | |
| rMatClust | Simulate Matern Cluster Process | |
| as.matrix.im | Convert Pixel Image to Matrix or Array | |
| rlinegrid | Generate grid of parallel lines with random displacement | |
| as.ppp | Convert Data To Class ppp | |
| rsyst | Simulate systematic random point pattern | |
| rescale.ppp | Convert Point Pattern to Another Unit of Length | |
| subset.ppp | Subset of Point Pattern Satisfying A Condition | |
| spatialcdf | Spatial Cumulative Distribution Function | |
| areaLoss | Difference of Disc Areas | |
| residuals.mppm | Residuals for Point Process Model Fitted to Multiple Point Patterns | |
| ants | Harkness-Isham ants' nests data | |
| crossdist.ppp | Pairwise distances between two different point patterns | |
| shift.owin | Apply Vector Translation To Window | |
| as.ppm | Extract Fitted Point Process Model | |
| split.im | Divide Image Into Sub-images | |
| simulate.lppm | Simulate a Fitted Point Process Model on a Linear Network | |
| Extract.hyperframe | Extract or Replace Subset of Hyperframe | |
| markcorrint | Mark Correlation Integral | |
| ippm | Fit Point Process Model Involving Irregular Trend Parameters | |
| runifpointx | Generate N Uniform Random Points in Any Dimensions | |
| rpoispp | Generate Poisson Point Pattern | |
| rotate.ppp | Rotate a Point Pattern | |
| applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
| split.ppx | Divide Multidimensional Point Pattern into Sub-patterns | |
| summary.quad | Summarizing a Quadrature Scheme | |
| rescale.im | Convert Pixel Image to Another Unit of Length | |
| rescue.rectangle | Convert Window Back To Rectangle | |
| summary.im | Summarizing a Pixel Image | |
| runifpoint | Generate N Uniform Random Points | |
| nncorr | Nearest-Neighbour Correlation Indices of Marked Point Pattern | |
| as.interact | Extract Interaction Structure | |
| redwood | California Redwoods Point Pattern (Ripley's Subset) | |
| update.ppm | Update a Fitted Point Process Model | |
| Ginhom | Inhomogeneous Nearest Neighbour Function | |
| vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
| linearpcfcross | Multitype Pair Correlation Function (Cross-type) for Linear Point Pattern | |
| Kmodel | K Function or Pair Correlation Function of a Point Process Model | |
| clickpoly | Interactively Define a Polygon | |
| shift.im | Apply Vector Translation To Pixel Image | |
| complement.owin | Take Complement of a Window | |
| rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |
| nztrees | New Zealand Trees Point Pattern | |
| timed | Record the Computation Time | |
| WindowOnly | Extract Window of Spatial Object | |
| summary.splitppp | Summary of a Split Point Pattern | |
| stratrand | Stratified random point pattern | |
| rgbim | Create Colour-Valued Pixel Image | |
| vcov.kppm | Variance-Covariance Matrix for a Fitted Cluster Point Process Model | |
| methods.pp3 | Methods for three-dimensional point patterns | |
| trim.rectangle | Cut margins from rectangle | |
| rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
| rmpoint | Generate N Random Multitype Points | |
| zapsmall.im | Rounding of Pixel Values | |
| textureplot | Plot Image Using Texture Fill | |
| Extract.influence.ppm | Extract Subset of Influence Object | |
| rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |
| border | Border Region of a Window | |
| anova.lppm | ANOVA for Fitted Point Process Models on Linear Network | |
| ripras | Estimate window from points alone | |
| convolve.im | Convolution of Pixel Images | |
| collapse.fv | Collapse Several Function Tables into One | |
| run.simplepanel | Run Point-and-Click Interface | |
| hamster | Aherne's hamster tumour data | |
| Smoothfun.ppp | Smooth Interpolation of Marks as a Spatial Function | |
| Extract.psp | Extract Subset of Line Segment Pattern | |
| edges | Extract Boundary Edges of a Window. | |
| pairdist.ppp | Pairwise distances | |
| Geyer | Geyer's Saturation Point Process Model | |
| plot.quad | Plot a Spatial Quadrature Scheme | |
| relrisk | Nonparametric Estimate of Spatially-Varying Relative Risk | |
| spokes | Spokes pattern of dummy points | |
| thomas.estpcf | Fit the Thomas Point Process by Minimum Contrast | |
| bramblecanes | Hutchings' Bramble Canes data | |
| Smooth.fv | Apply Smoothing to Function Values | |
| pixellate | Convert Spatial Object to Pixel Image | |
| PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
| rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
| diameter.owin | Diameter of a Window | |
| sharpen | Data Sharpening of Point Pattern | |
| volume | Volume of an Object | |
| update.kppm | Update a Fitted Cluster Point Process Model | |
| Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
| envelope.envelope | Recompute Envelopes | |
| runifpoint3 | Generate N Uniform Random Points in Three Dimensions | |
| betacells | Beta Ganglion Cells in Cat Retina | |
| summary.owin | Summary of a Spatial Window | |
| envelope | Simulation Envelopes of Summary Function | |
| is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
| F3est | Empty Space Function of a Three-Dimensional Point Pattern | |
| contour.listof | Plot a List of Things | |
| rStrauss | Perfect Simulation of the Strauss Process | |
| rknn | Theoretical Distribution of Nearest Neighbour Distance | |
| Finhom | Inhomogeneous Empty Space Function | |
| fasp.object | Function Arrays for Spatial Patterns | |
| grow.rectangle | Add margins to rectangle | |
| methods.lppm | Methods for Fitted Point Process Models on a Linear Network | |
| marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern | |
| edge.Trans | Translation Edge Correction | |
| Gest | Nearest Neighbour Distance Function G | |
| kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
| Strauss | The Strauss Point Process Model | |
| Pairwise | Generic Pairwise Interaction model | |
| harmonise.fv | Make Function Tables Compatible | |
| closing | Morphological Closing | |
| affine.im | Apply Affine Transformation To Pixel Image | |
| default.dummy | Generate a Default Pattern of Dummy Points | |
| vcov.slrm | Variance-Covariance Matrix for a Fitted Spatial Logistic Regression | |
| transect.im | Pixel Values Along a Transect | |
| affine | Apply Affine Transformation | |
| rThomas | Simulate Thomas Process | |
| Extract.layered | Extract Subset of a Layered Object | |
| waka | Trees in Waka national park | |
| Replace.im | Reset Values in Subset of Image | |
| Ldot.inhom | Inhomogeneous Multitype L Dot Function | |
| slrm | Spatial Logistic Regression | |
| diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
| Hybrid | Hybrid Interaction Point Process Model | |
| latest.news | Print News About Latest Version of Package | |
| methods.objsurf | Methods for Objective Function Surfaces | |
| MultiStrauss | The Multitype Strauss Point Process Model | |
| methods.rhohat | Methods for Intensity Functions of Spatial Covariate | |
| bw.ppl | Likelihood Cross Validation Bandwidth Selection for Kernel Density | |
| scan.test | Spatial Scan Test | |
| rshift | Random Shift | |
| Extract.im | Extract Subset of Image | |
| centroid.owin | Centroid of a window | |
| is.rectangle | Determine Type of Window | |
| vargamma.estK | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |
| spatstat-package | The Spatstat Package | |
| split.hyperframe | Divide Hyperframe Into Subsets and Reassemble | |
| harmonic | Basis for Harmonic Functions | |
| rthin | Random Thinning | |
| Extract.msr | Extract Subset of Signed or Vector Measure | |
| distmap | Distance Map | |
| spatstat-internal | Internal spatstat functions | |
| MultiHard | The Multitype Hard Core Point Process Model | |
| Jinhom | Inhomogeneous J-function | |
| rpoislinetess | Poisson Line Tessellation | |
| stieltjes | Compute Integral of Function Against Cumulative Distribution | |
| Jmulti | Marked J Function | |
| methods.box3 | Methods for Three-Dimensional Box | |
| rounding | Detect Numerical Rounding | |
| rescale.owin | Convert Window to Another Unit of Length | |
| rMosaicField | Mosaic Random Field | |
| rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |
| LambertW | Lambert's W Function | |
| boundingbox | Bounding Box of a Window, Image, or Point Pattern | |
| Kmodel.ppm | K Function or Pair Correlation Function of Gibbs Point Process model | |
| Kinhom | Inhomogeneous K-function | |
| linearpcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-type) for Linear Point Pattern | |
| as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |
| Concom | The Connected Component Process Model | |
| as.data.frame.im | Convert Pixel Image to Data Frame | |
| affine.linnet | Apply Geometrical Transformations to a Linear Network | |
| disc | Circular Window | |
| bdist.points | Distance to Boundary of Window | |
| density.ppp | Kernel Smoothed Intensity of Point Pattern | |
| Smooth | Spatial smoothing of data | |
| rDiggleGratton | Perfect Simulation of the Diggle-Gratton Process | |
| density.psp | Kernel Smoothing of Line Segment Pattern | |
| Extract.splitppp | Extract or Replace Sub-Patterns | |
| linearKdot.inhom | Inhomogeneous multitype K Function (Dot-type) for Linear Point Pattern | |
| nncross | Nearest Neighbours Between Two Patterns | |
| sporophores | Sporophores Data | |
| summary.psp | Summary of a Line Segment Pattern Dataset | |
| plot.layered | Layered Plot | |
| quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
| as.rectangle | Window Frame | |
| redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
| by.ppp | Apply a Function to a Point Pattern Broken Down by Factor | |
| clip.infline | Intersect Infinite Straight Lines with a Window | |
| profilepl | Profile Maximum Pseudolikelihood | |
| plot.splitppp | Plot a List of Point Patterns | |
| rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
| as.matrix.owin | Convert Pixel Image to Matrix | |
| rGaussPoisson | Simulate Gauss-Poisson Process | |
| cdf.test | Spatial Distribution Test for Point Pattern or Point Process Model | |
| distcdf | Distribution Function of Interpoint Distance | |
| Lest | L-function | |
| pcfdot | Multitype pair correlation function (i-to-any) | |
| Kscaled | Locally Scaled K-function | |
| vertices | Vertices of a Window | |
| rotate | Rotate | |
| pairs.im | Scatterplot Matrix for Pixel Images | |
| tile.areas | Compute Areas of Tiles in a Tessellation | |
| pool.fasp | Pool Data from Several Function Arrays | |
| model.matrix.ppm | Extract Design Matrix from Point Process Model | |
| spruces | Spruces Point Pattern | |
| Gcom | Model Compensator of Nearest Neighbour Function | |
| osteo | Osteocyte Lacunae Data: Replicated Three-Dimensional Point Patterns | |
| area.owin | Area of a Window | |
| Kcom | Model Compensator of K Function | |
| DiggleGatesStibbard | Diggle-Gates-Stibbard Point Process Model | |
| pcfinhom | Inhomogeneous Pair Correlation Function | |
| Extract.lpp | Extract Subset of Point Pattern on Linear Network | |
| nearestsegment | Find Line Segment Nearest to Each Point | |
| plot.im | Plot a Pixel Image | |
| pcfcross | Multitype pair correlation function (cross-type) | |
| plot.symbolmap | Plot a Graphics Symbol Map | |
| plot.tess | Plot a tessellation | |
| layerplotargs | Extract or Replace the Plot Arguments of a Layered Object | |
| rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
| plot.ppm | plot a Fitted Point Process Model | |
| progressreport | Print Progress Reports | |
| AreaInter | The Area Interaction Point Process Model | |
| boxx | Multi-Dimensional Box | |
| Emark | Diagnostics for random marking | |
| sidelengths.owin | Side Lengths of Enclosing Rectangle of a Window | |
| hybrid.family | Hybrid Interaction Family | |
| Kmulti | Marked K-Function | |
| mucosa | Cells in Gastric Mucosa | |
| quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
| rDGS | Perfect Simulation of the Diggle-Gates-Stibbard Process | |
| edges2vees | List Dihedral Triples in a Graph | |
| by.im | Apply Function to Image Broken Down by Factor | |
| bei | Tropical rain forest trees | |
| inforder.family | Infinite Order Interaction Family | |
| Kcross.inhom | Inhomogeneous Cross K Function | |
| Smooth.ppp | Spatial smoothing of observations at irregular points | |
| rotate.owin | Rotate a Window | |
| japanesepines | Japanese Pines Point Pattern | |
| StraussHard | The Strauss / Hard Core Point Process Model | |
| dummify | Convert Data to Numeric Values by Constructing Dummy Variables | |
| plot.hyperframe | Plot Entries in a Hyperframe | |
| rcellnumber | Generate Random Numbers of Points for Cell Process | |
| Jdot | Multitype J Function (i-to-any) | |
| deltametric | Delta Metric | |
| adaptive.density | Intensity Estimate of Point Pattern Using Tessellation | |
| beginner | Print Introduction For Beginners | |
| Saturated | Saturated Pairwise Interaction model | |
| envelope.lpp | Envelope for Point Patterns on Linear Network | |
| anemones | Beadlet Anemones Data | |
| distmap.psp | Distance Map of Line Segment Pattern | |
| plot.quadratcount | Plot Quadrat Counts | |
| dilation | Morphological Dilation | |
| tweak.colourmap | Change Colour Values in a Colour Map | |
| as.polygonal | Convert a Window to a Polygonal Window | |
| Ord | Generic Ord Interaction model | |
| pairdist | Pairwise distances | |
| sumouter | Compute Quadratic Forms | |
| as.function.fv | Convert Function Value Table to Function | |
| logLik.slrm | Loglikelihood of Spatial Logistic Regression | |
| simplenet | Simple Example of Linear Network | |
| dclf.test | Diggle-Cressie-Loosmore-Ford and Maximum Absolute Deviation Tests | |
| fvnames | Abbreviations for Groups of Columns in Function Value Table | |
| MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
| rotate.psp | Rotate a Line Segment Pattern | |
| Window | Extract or Change the Window of a Spatial Object | |
| allstats | Calculate four standard summary functions of a point pattern. | |
| Kres | Residual K Function | |
| distmap.ppp | Distance Map of Point Pattern | |
| eroded.areas | Areas of Morphological Erosions | |
| gauss.hermite | Gauss-Hermite Quadrature Approximation to Expectation for Normal Distribution | |
| LennardJones | The Lennard-Jones Potential | |
| as.data.frame.psp | Coerce Line Segment Pattern to a Data Frame | |
| blur | Apply Gaussian Blur to a Pixel Image | |
| Fiksel | The Fiksel Interaction | |
| plot.mppm | plot a Fitted Multiple Point Process Model | |
| nbfires | Point Patterns of New Brunswick Forest Fires | |
| longleaf | Longleaf Pines Point Pattern | |
| dmixpois | Mixed Poisson Distribution | |
| alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern | |
| erosion | Morphological Erosion | |
| identify.ppp | Identify Points in a Point Pattern | |
| Hardcore | The Hard Core Point Process Model | |
| cut.im | Convert Pixel Image from Numeric to Factor | |
| simplepanel | Simple Point-and-Click Interface Panels | |
| connected | Connected components | |
| nndist.ppx | Nearest Neighbour Distances in Any Dimensions | |
| plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
| as.psp | Convert Data To Class psp | |
| plot.texturemap | Plot a Texture Map | |
| endpoints.psp | Endpoints of Line Segment Pattern | |
| Softcore | The Soft Core Point Process Model | |
| localpcf | Local pair correlation function | |
| linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |
| subfits | Extract List of Individual Point Process Models | |
| pairorient | Point Pair Orientation Distribution | |
| nndist | Nearest neighbour distances | |
| ponderosa | Ponderosa Pine Tree Point Pattern | |
| crossdist | Pairwise distances | |
| concatxy | Concatenate x,y Coordinate Vectors | |
| bw.relrisk | Cross Validated Bandwidth Selection for Relative Risk Estimation | |
| markcorr | Mark Correlation Function | |
| clickppp | Interactively Add Points | |
| idw | Inverse-distance weighted smoothing of observations at irregular points | |
| quadrat.test.splitppp | Dispersion Test of CSR for Split Point Pattern Based on Quadrat Counts | |
| angles.psp | Orientation Angles of Line Segments | |
| will.expand | Test Expansion Rule | |
| rescale | Convert dataset to another unit of length | |
| pairdist.default | Pairwise distances | |
| Kmeasure | Reduced Second Moment Measure | |
| plot.kppm | Plot a fitted cluster point process | |
| methods.linnet | Methods for Linear Networks | |
| ppp.object | Class of Point Patterns | |
| plot.msr | Plot a Signed or Vector-Valued Measure | |
| pool.rat | Pool Data from Several Ratio Objects | |
| linearpcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Dot-type) for Linear Point Pattern | |
| pppmatching.object | Class of Point Matchings | |
| cbind.hyperframe | Combine Hyperframes by Rows or by Columns | |
| fv.object | Function Value Table | |
| contour.im | Contour plot of pixel image | |
| pixellate.psp | Convert Line Segment Pattern to Pixel Image | |
| chop.tess | Subdivide a Window or Tessellation using a Set of Lines | |
| ewcdf | Weighted Empirical Cumulative Distribution Function | |
| fryplot | Fry Plot of Point Pattern | |
| dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
| triplet.family | Triplet Interaction Family | |
| DiggleGratton | Diggle-Gratton model | |
| pool.envelope | Pool Data from Several Envelopes | |
| dilated.areas | Areas of Morphological Dilations | |
| compareFit | Residual Diagnostics for Multiple Fitted Models | |
| layout.boxes | Generate a Row or Column Arrangement of Rectangles. | |
| as.linim | Convert to Pixel Image on Linear Network | |
| connected.ppp | Connected components of a point pattern | |
| Extract.linnet | Extract Subset of Linear Network | |
| areaGain | Difference of Disc Areas | |
| bdist.pixels | Distance to Boundary of Window | |
| K3est | K-function of a Three-Dimensional Point Pattern | |
| data.ppm | Extract Original Data from a Fitted Point Process Model | |
| closepairs | Close Pairs of Points | |
| circumradius | Circumradius and Diameter of a Linear Network | |
| whist | Weighted Histogram | |
| exactMPLEstrauss | Exact Maximum Pseudolikelihood Estimate for Stationary Strauss Process | |
| predict.slrm | Predicted or Fitted Values from Spatial Logistic Regression | |
| plot.linnet | Plot a linear network | |
| rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |
| edges2triangles | List Triangles in a Graph | |
| as.owin | Convert Data To Class owin | |
| dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
| miplot | Morisita Index Plot | |
| Ksector | Sector K-function | |
| rshift.splitppp | Randomly Shift a List of Point Patterns | |
| closepairs.pp3 | Close Pairs of Points in 3 Dimensions | |
| effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model | |
| bw.scott | Scott's Rule for Bandwidth Selection for Kernel Density | |
| envelope.pp3 | Simulation Envelopes of Summary Function for 3D Point Pattern | |
| crossdist.default | Pairwise distances between two different sets of points | |
| plot.influence.ppm | Plot Influence Measure | |
| plot.slrm | Plot a Fitted Spatial Logistic Regression | |
| gordon | People in Gordon Square | |
| compatible.fasp | Test Whether Function Arrays Are Compatible | |
| quantile.im | Sample Quantiles of Pixel Image | |
| bw.diggle | Cross Validated Bandwidth Selection for Kernel Density | |
| delaunay.distance | Distance on Delaunay Triangulation | |
| methods.ppx | Methods for Multidimensional Space-Time Point Patterns | |
| matclust.estpcf | Fit the Matern Cluster Point Process by Minimum Contrast Using Pair Correlation | |
| eem | Exponential Energy Marks | |
| compatible.im | Test Whether Pixel Images Are Compatible | |
| box3 | Three-Dimensional Box | |
| predict.mppm | Prediction for Fitted Multiple Point Process Model | |
| psstA | Pseudoscore Diagnostic For Fitted Model against Area-Interaction Alternative | |
| project2segment | Move Point To Nearest Line | |
| distfun.lpp | Distance Map on Linear Network | |
| clmfires | Castilla-La Mancha Forest Fires | |
| clarkevans.test | Clark and Evans Test | |
| vcov.mppm | Calculate Variance-Covariance Matrix for Fitted Multiple Point Process Model | |
| hyytiala | Scots pines and other trees at Hyytiala | |
| demopat | Artificial Data Point Pattern | |
| linearKcross.inhom | Inhomogeneous multitype K Function (Cross-type) for Linear Point Pattern | |
| convexhull | Convex Hull | |
| overlap.owin | Compute Area of Overlap | |
| plot.owin | Plot a Spatial Window | |
| cauchy.estK | Fit the Neyman-Scott cluster process with Cauchy kernel | |
| bw.stoyan | Stoyan's Rule of Thumb for Bandwidth Selection | |
| Jcross | Multitype J Function (i-to-j) | |
| varblock | Estimate Variance of Summary Statistic by Subdivision | |
| harmonise.im | Make Pixel Images Compatible | |
| formula.fv | Extract or Change the Plot Formula for a Function Value Table | |
| mincontrast | Method of Minimum Contrast | |
| rpoisline | Generate Poisson Random Line Process | |
| levelset | Level Set of a Pixel Image | |
| pool.quadrattest | Pool Several Quadrat Tests | |
| add.texture | Fill Plot With Texture | |
| update.rmhcontrol | Update Control Parameters of Metropolis-Hastings Algorithm | |
| predict.lppm | Predict Point Process Model on Linear Network | |
| density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
| as.lpp | Convert Data to a Point Pattern on a Linear Network | |
| anova.ppm | ANOVA for Fitted Point Process Models | |
| pcf.fv | Pair Correlation Function obtained from K Function | |
| compatible | Test Whether Objects Are Compatible | |
| corners | Corners of a rectangle | |
| fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
| plot.fv | Plot Function Values | |
| Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
| flipxy | Exchange X and Y Coordinates | |
| Linhom | L-function | |
| lgcp.estpcf | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| crossdist.lpp | Pairwise distances between two point patterns on a linear network | |
| copper | Berman-Huntington points and lines data | |
| finpines | Pine saplings in Finland. | |
| Kest.fft | K-function using FFT | |
| plot.scan.test | Plot Result of Scan Test | |
| quadrat.test | Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
| lut | Lookup Tables | |
| quadscheme.logi | Generate a Logistic Regression Quadrature Scheme from a Point Pattern | |
| unmark | Remove Marks | |
| nnmark | Mark of Nearest Neighbour | |
| humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
| dirichlet | Dirichlet Tessellation of Point Pattern | |
| plot.cdftest | Plot a Spatial Distribution Test | |
| spatstat-deprecated | Deprecated spatstat functions | |
| delaunay | Delaunay Triangulation of Point Pattern | |
| chicago | Chicago Street Crime Data | |
| lohboot | Bootstrap Confidence Bands for Summary Function | |
| print.quad | Print a Quadrature Scheme | |
| nnwhich.lpp | Identify Nearest Neighbours on a Linear Network | |
| plot.fasp | Plot a Function Array | |
| msr | Signed or Vector-Valued Measure | |
| pcf3est | Pair Correlation Function of a Three-Dimensional Point Pattern | |
| affine.lpp | Apply Geometrical Transformations to Point Pattern on a Linear Network | |
| Fest | Estimate the empty space function F | |
| npoints | Number of Points in a Point Pattern | |
| cauchy.estpcf | Fit the Neyman-Scott cluster process with Cauchy kernel | |
| pairdist.ppx | Pairwise Distances in Any Dimensions | |
| plot.envelope | Plot a Simulation Envelope | |
| foo | Foo is Not a Variable | |
| demohyper | Demonstration Example of Hyperframe of Spatial Data | |
| coords | Extract or Change Coordinates of a Spatial or Spatiotemporal Point Pattern | |
| owin.object | Class owin | |
| gridcentres | Rectangular grid of points | |
| hyperframe | Hyper Data Frame | |
| psp | Create a Line Segment Pattern | |
| methods.layered | Methods for Layered Objects | |
| formula.ppm | Model Formulae for Gibbs Point Process Models | |
| plot.listof | Plot a List of Things | |
| pairwise.family | Pairwise Interaction Process Family | |
| ellipse | Elliptical Window. | |
| eval.fasp | Evaluate Expression Involving Function Arrays | |
| waterstriders | Waterstriders data. Three independent replications of a point pattern formed by insects. | |
| pppdist | Distance Between Two Point Patterns | |
| bw.smoothppp | Cross Validated Bandwidth Selection for Spatial Smoothing | |
| is.convex | Test Whether a Window is Convex | |
| print.owin | Print Brief Details of a Spatial Window | |
| opening | Morphological Opening | |
| compatible.fv | Test Whether Function Objects Are Compatible | |
| interp.colourmap | Interpolate smoothly between specified colours | |
| Extract.tess | Extract or Replace Subset of Tessellation | |
| lansing | Lansing Woods Point Pattern | |
| discretise | Safely Convert Point Pattern Window to Binary Mask | |
| pixelquad | Quadrature Scheme Based on Pixel Grid | |
| dclf.progress | Progress Plot of Test of Spatial Pattern | |
| amacrine | Hughes' Amacrine Cell Data | |
| pixellate.ppp | Convert Point Pattern to Pixel Image | |
| nncross.pp3 | Nearest Neighbours Between Two Patterns in 3D | |
| Hest | Spherical Contact Distribution Function | |
| colourtools | Convert and Compare Colours in Different Formats | |
| is.subset.owin | Determine Whether One Window is Contained In Another | |
| pixelcentres | Extract Pixel Centres as Point Pattern | |
| coef.ppm | Coefficients of Fitted Point Process Model | |
| plot.ppp | plot a Spatial Point Pattern | |
| plot.linim | Plot Pixel Image on Linear Network | |
| Kmulti.inhom | Inhomogeneous Marked K-Function | |
| project.ppm | Force Point Process Model to be Valid | |
| padimage | Pad the Border of a Pixel Image | |
| OrdThresh | Ord's Interaction model | |
| affine.ppp | Apply Affine Transformation To Point Pattern | |
| berman.test | Berman's Tests for Point Process Model | |
| clarkevans | Clark and Evans Aggregation Index | |
| diameter | Diameter of an Object | |
| eval.fv | Evaluate Expression Involving Functions | |
| methods.boxx | Methods for Multi-Dimensional Box | |
| owin | Create a Window | |
| as.hyperframe | Convert Data to Hyperframe | |
| coef.slrm | Coefficients of Fitted Spatial Logistic Regression Model | |
| default.rmhcontrol | Set Default Control Parameters for Metropolis-Hastings Algorithm. | |
| quadratresample | Resample a Point Pattern by Resampling Quadrats | |
| pcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Type-i-To-Any-Type) | |
| model.frame.ppm | Extract the Variables in a Point Process Model | |
| pcf.fasp | Pair Correlation Function obtained from array of K functions | |
| print.im | Print Brief Details of an Image | |
| eval.linim | Evaluate Expression Involving Pixel Images on Linear Network | |
| is.owin | Test Whether An Object Is A Window | |
| localKinhom | Inhomogeneous Neighbourhood Density Function | |
| flu | Influenza Virus Proteins | |
| pppmatching | Create a Point Matching | |
| plot.psp | plot a Spatial Line Segment Pattern | |
| nnmap | K-th Nearest Point Map | |
| perimeter | Perimeter Length of Window | |
| plot.pp3 | Plot a three-dimensional point pattern | |
| affine.psp | Apply Affine Transformation To Line Segment Pattern | |
| fitted.slrm | Fitted Probabilities for Spatial Logistic Regression | |
| nnfun | Nearest Neighbour Index Map as a Function | |
| coef.mppm | Coefficients of Point Process Model Fitted to Multiple Point Patterns | |
| model.matrix.slrm | Extract Design Matrix from Spatial Logistic Regression Model | |
| distmap.owin | Distance Map of Window | |
| rHardcore | Perfect Simulation of the Hardcore Process | |
| as.tess | Convert Data To Tessellation | |
| anova.slrm | Analysis of Deviance for Spatial Logistic Regression Models | |
| is.lpp | Test Whether An Object Is A Point Pattern on a Linear Network | |
| objsurf | Objective Function Surface | |
| funxy | Spatial Function Class | |
| quadrat.test.mppm | Chi-Squared Test for Multiple Point Process Model Based on Quadrat Counts | |
| cut.ppp | Classify Points in a Point Pattern | |
| print.ppp | Print Brief Details of a Point Pattern Dataset | |
| is.im | Test Whether An Object Is A Pixel Image | |
| pcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-Type) | |
| nnclean | Nearest Neighbour Clutter Removal | |
| quadratcount | Quadrat counting for a point pattern | |
| methods.rho2hat | Methods for Intensity Functions of Two Spatial Covariates | |
| psp.object | Class of Line Segment Patterns | |
| hextess | Hexagonal Grid or Tessellation | |
| Iest | Estimate the I-function | |
| edge.Ripley | Ripley's Isotropic Edge Correction | |
| methods.fii | Methods for Fitted Interactions | |
| ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
| as.mask | Pixel Image Approximation of a Window | |
| linnet | Create a Linear Network | |
| pool | Pool Data | |
| bw.frac | Bandwidth Selection Based on Window Geometry | |
| predict.ppm | Prediction from a Fitted Point Process Model | |
| periodify | Make Periodic Copies of a Spatial Pattern | |
| lurking | Lurking variable plot | |
| crossing.psp | Crossing Points of Two Line Segment Patterns | |
| diameter.box3 | Geometrical Calculations for Three-Dimensional Box | |
| ppp | Create a Point Pattern | |
| methods.units | Methods for Units | |
| quadrats | Divide Region into Quadrats | |
| identify.psp | Identify Segments in a Line Segment Pattern | |
| plot.lppm | Plot a Fitted Point Process Model on a Linear Network | |
| clickjoin | Interactively join vertices on a plot | |
| nncross.lpp | Nearest Neighbours on a Linear Network | |
| pixellate.owin | Convert Window to Pixel Image | |
| heather | Diggle's Heather Data | |
| pairsat.family | Saturated Pairwise Interaction Point Process Family | |
| linearKinhom | Inhomogeneous Linear K Function | |
| predict.kppm | Prediction from a Fitted Cluster Point Process Model | |
| lppm | Fit Point Process Model to Point Pattern on Linear Network | |
| ppm | Fit Point Process Model to Data | |
| pcfmulti | Marked pair correlation function | |
| print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
| pairdist.lpp | Pairwise shortest-path distances between points on a linear network | |
| distfun | Distance Map as a Function | |
| plot.lpp | Plot Point Pattern on Linear Network | |
| cdf.test.mppm | Spatial Distribution Test for Multiple Point Process Model | |
| crossdist.psp | Pairwise distances between two different line segment patterns | |
| print.ppm | Print a Fitted Point Process Model | |
| clusterset | Allard-Fraley Estimator of Cluster Feature | |
| as.data.frame.hyperframe | Coerce Hyperframe to Data Frame | |
| nnwhich.ppx | Nearest Neighbours in Any Dimensions | |
| crossdist.pp3 | Pairwise distances between two different three-dimensional point patterns | |
| gridweights | Compute Quadrature Weights Based on Grid Counts | |
| Poisson | Poisson Point Process Model | |
| ppx | Multidimensional Space-Time Point Pattern | |
| pairdist.pp3 | Pairwise distances in Three Dimensions | |
| methods.kppm | Methods for Cluster Point Process Models | |
| markconnect | Mark Connection Function | |
| hist.im | Histogram of Pixel Values in an Image | |
| is.marked.ppp | Test Whether A Point Pattern is Marked | |
| anova.mppm | ANOVA for Fitted Multiple Point Process Models | |
| logLik.mppm | Log Likelihood for Poisson Point Process Model | |
| parres | Partial Residuals for Point Process Model | |
| nndensity.ppp | Estimate Intensity of Point Pattern Using Nearest Neighbour Distances | |
| pointsOnLines | Place Points Evenly Along Specified Lines | |
| ppm.ppp | Fit Point Process Model to Point Pattern Data | |
| bounding.box.xy | Convex Hull of Points | |
| pcf.ppp | Pair Correlation Function of Point Pattern | |
| quantile.ewcdf | Quantiles of Weighted Empirical Cumulative Distribution Function | |
| plot.colourmap | Plot a Colour Map | |
| layered | Create List of Plotting Layers | |
| marks | Marks of a Point Pattern | |
| moribund | Outdated Functions | |
| pcf | Pair Correlation Function | |
| npfun | Dummy Function Returns Number of Points | |
| Extract.owin | Extract Subset of Window | |
| persp.im | Perspective Plot of Pixel Image | |
| kppm | Fit Cluster or Cox Point Process Model | |
| qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
| mean.im | Maximum, Minimum, Mean, Median, Range or Sum of Pixel Values in an Image | |
| matchingdist | Distance for a Point Pattern Matching | |
| is.marked | Test Whether Marks Are Present | |
| linearK | Linear K Function | |
| runifdisc | Generate N Uniform Random Points in a Disc | |
| reduced.sample | Reduced Sample Estimator using Histogram Data | |
| simulate.slrm | Simulate a Fitted Spatial Logistic Regression Model | |
| Extract.listof | Extract or Replace Subset of a List of Things | |
| rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |
| rshift.psp | Randomly Shift a Line Segment Pattern | |
| vargamma.estpcf | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |
| convexhull.xy | Convex Hull of Points | |
| Gres | Residual G Function | |
| union.quad | Union of Data and Dummy Points | |
| dfbetas.ppm | Parameter influence measure | |
| diameter.boxx | Geometrical Calculations for Multi-Dimensional Box | |
| default.expand | Default Expansion Rule for Simulation of Model | |
| expand.owin | Apply Expansion Rule | |
| rCauchy | Simulate Neyman-Scott Point Process with Cauchy cluster kernel | |
| plot.quadrattest | Display the result of a quadrat counting test. | |
| psstG | Pseudoscore Diagnostic For Fitted Model against Saturation Alternative | |
| quasirandom | Quasirandom Patterns | |
| Kest | K-function | |
| markvario | Mark Variogram | |
| is.stationary | Recognise Stationary and Poisson Point Process Models | |
| reach | Interaction Distance of a Point Process | |
| pp3 | Three Dimensional Point Pattern | |
| methods.funxy | Methods for Spatial Functions | |
| maxnndist | Compute Minimum or Maximum Nearest-Neighbour Distance | |
| incircle | Find Largest Circle Inside Window | |
| markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
| rpoislpp | Poisson Point Process on a Linear Network | |
| summary.ppp | Summary of a Point Pattern Dataset | |
| rmhexpand | Specify Simulation Window or Expansion Rule | |
| rhohat | Smoothing Estimate of Covariate Transformation | |
| unnormdensity | Weighted kernel smoother | |
| rshift.ppp | Randomly Shift a Point Pattern | |
| BadGey | Hybrid Geyer Point Process Model | |
| residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
| update.symbolmap | Update a Graphics Symbol Map. | |
| G3est | Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern | |
| with.hyperframe | Evaluate an Expression in Each Row of a Hyperframe | |
| summary.ppm | Summarizing a Fitted Point Process Model | |
| thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
| rStraussHard | Perfect Simulation of the Strauss-Hardcore Process | |
| Kcross | Multitype K Function (Cross-type) | |
| as.mask.psp | Convert Line Segment Pattern to Binary Pixel Mask | |
| as.fv | Convert Data To Class fv | |
| as.box3 | Convert Data to Three-Dimensional Box | |
| as.layered | Convert Data To Layered Object | |
| bronzefilter | Bronze gradient filter data | |
| discpartarea | Area of Part of Disc | |
| colourmap | Colour Lookup Tables | |
| fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |
| tilenames | Names of Tiles in a Tessellation | |
| deriv.fv | Calculate Derivative of Function Values | |
| plot.leverage.ppm | Plot Leverage Function | |
| quad.object | Class of Quadrature Schemes | |
| multiplicity.ppp | Count Multiplicity of Duplicate Points | |
| ppm.object | Class of Fitted Point Process Models | |
| plot.bermantest | Plot Result of Berman Test | |
| linearKdot | Multitype K Function (Dot-type) for Linear Point Pattern | |
| psst | Pseudoscore Diagnostic For Fitted Model against General Alternative | |
| clickbox | Interactively Define a Rectangle | |
| lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| nndist.psp | Nearest neighbour distances between line segments | |
| rpoint | Generate N Random Points | |
| shift | Apply Vector Translation | |
| range.fv | Range of Function Values | |
| simdat | Simulated Point Pattern | |
| setcov | Set Covariance of a Window | |
| runiflpp | Uniform Random Points on a Linear Network | |
| Frame | Extract or Change the Containing Rectangle of a Spatial Object | |
| Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
| scaletointerval | Rescale Data to Lie Between Specified Limits | |
| round.ppp | Apply Numerical Rounding to Spatial Coordinates | |
| Kmodel.kppm | K Function or Pair Correlation Function of Cluster Model or Cox model | |
| Smooth.msr | Smooth a Signed or Vector-Valued Measure | |
| as.hyperframe.ppx | Extract coordinates and marks of multidimensional point pattern | |
| beachcolours | Create Colour Scheme for a Range of Numbers | |
| append.psp | Combine Two Line Segment Patterns | |
| shift.psp | Apply Vector Translation To Line Segment Pattern | |
| crossdist.ppx | Pairwise Distances Between Two Different Multi-Dimensional Point Patterns | |
| fitted.mppm | Fitted Conditional Intensity for Multiple Point Process Model | |
| commonGrid | Determine A Common Spatial Domain And Pixel Resolution | |
| pyramidal | Pyramidal Neurons in Cingulate Cortex | |
| gorillas | Gorilla Nesting Sites | |
| linearKcross | Multitype K Function (Cross-type) for Linear Point Pattern | |
| panel.contour | Panel Plots using Colour Image or Contour Lines | |
| No Results! | ||
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Details
| Nickname | Wicked Plot |
| Date | 2014-08-15 |
| License | GPL (>= 2) |
| URL | http://www.spatstat.org |
| LazyData | true |
| NeedsCompilation | yes |
| ByteCompile | true |
| Packaged | 2014-08-15 10:58:26 UTC; adrian |
| Repository | CRAN |
| Date/Publication | 2014-08-15 17:39:22 |
| imports | abind , deldir (>= 0.0-21) , goftest , mgcv , polyclip (>= 1.3-0) , tensor |
| depends | base (>= 3.0.2) , graphics , grDevices , R (>= 3.0.2) , stats , utils |
| suggests | gsl , locfit , maptools , Matrix , RandomFields (>= 3.0.0) , rpanel , scatterplot3d , sm , spatial , tkrplot |
| Contributors | Rolf Turner, Adrian Baddeley, Ege Rubak |
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