spatstat v1.34-0
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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, and space-time point patterns in any number of dimensions.
Contains over 1000 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 and tessellations.
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, Dao-Genton) are also supported.
Point process models can be fitted to point pattern data using the functions ppm, kppm, slrm similar to glm. 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 various composite likelihood methods.
Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported. Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, and leverage and influence diagnostics.
Functions in spatstat
| Name | Description | |
| as.mask.psp | Convert Line Segment Pattern to Binary Pixel Mask | |
| as.ppm | Extract Fitted Point Process Model | |
| compareFit | Residual Diagnostics for Multiple Fitted Models | |
| diameter | Diameter of an Object | |
| eval.im | Evaluate Expression Involving Pixel Images | |
| distfun | Distance Map as a Function | |
| bdist.tiles | Distance to Boundary of Window | |
| box3 | Three-Dimensional Box | |
| intersect.tess | Intersection of Two Tessellations | |
| as.fv | Convert Data To Class fv | |
| bounding.box | Bounding Box of a Window or Point Pattern | |
| border | Border Region of a Window | |
| layerplotargs | Extract or Replace the Plot Arguments of a Layered Object | |
| as.psp | Convert Data To Class psp | |
| diameter.owin | Diameter of a Window | |
| distfun.lpp | Distance Map on Linear Network | |
| fv | Create a Function Value Table | |
| contour.im | Contour plot of pixel image | |
| matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
| lineardisc | Compute Disc of Given Radius in Linear Network | |
| as.polygonal | Convert a Window to a Polygonal Window | |
| as.matrix.owin | Convert Pixel Image to Matrix | |
| cbind.hyperframe | Combine Hyperframes by Rows or by Columns | |
| idw | Inverse-distance weighted smoothing of observations at irregular points | |
| bermantest | Berman's Tests for Point Process Model | |
| ppm.object | Class of Fitted Point Process Models | |
| as.matrix.im | Convert Pixel Image to Matrix or Array | |
| default.expand | Default Expansion Rule for Simulation of Model | |
| linearKdot.inhom | Inhomogeneous multitype K Function (Dot-type) for Linear Point Pattern | |
| bdist.pixels | Distance to Boundary of Window | |
| formula.ppm | Model Formulae for Gibbs Point Process Models | |
| bind.fv | Combine Function Value Tables | |
| contour.listof | Plot a List of Things | |
| cut.im | Convert Pixel Image from Numeric to Factor | |
| gridweights | Compute Quadrature Weights Based on Grid Counts | |
| coords | Extract or Change Coordinates of a Spatial or Spatiotemporal Point Pattern | |
| compatible.fv | Test Whether Function Objects Are Compatible | |
| bramblecanes | Hutchings' Bramble Canes data | |
| reduced.sample | Reduced Sample Estimator using Histogram Data | |
| ewcdf | Weighted Empirical Cumulative Distribution Function | |
| bw.scott | Scott's Rule for Bandwidth Selection for Kernel Density | |
| rlinegrid | Generate grid of parallel lines with random displacement | |
| dfbetas.ppm | Parameter influence measure | |
| compatible | Test Whether Objects Are Compatible | |
| rMosaicSet | Mosaic Random Set | |
| crossdist.lpp | Pairwise distances between two point patterns on a linear network | |
| rVarGamma | Simulate Neyman-Scott Point Process with Variance Gamma cluster kernel | |
| rStraussHard | Perfect Simulation of the Strauss-Hardcore Process | |
| methods.pp3 | Methods for three-dimensional point patterns | |
| discpartarea | Area of Part of Disc | |
| crossdist.psp | Pairwise distances between two different line segment patterns | |
| dclf.progress | Progress Plot of Test of Spatial Pattern | |
| is.marked | Test Whether Marks Are Present | |
| model.images | Compute Images of Constructed Covariates | |
| commonGrid | Determine A Common Spatial Domain And Pixel Resolution | |
| as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |
| as.interact | Extract Interaction Structure | |
| coef.ppm | Coefficients of Fitted Point Process Model | |
| bw.ppl | Likelihood Cross Validation Bandwidth Selection for Kernel Density | |
| lengths.psp | Lengths of Line Segments | |
| edge.Trans | Translation Edge Correction | |
| tess | Create a Tessellation | |
| cauchy.estK | Fit the Neyman-Scott cluster process with Cauchy kernel | |
| summary.splitppp | Summary of a Split Point Pattern | |
| bei | Tropical rain forest trees | |
| reach | Interaction Distance of a Point Process | |
| delaunay | Delaunay Triangulation of Point Pattern | |
| as.data.frame.psp | Coerce Line Segment Pattern to a Data Frame | |
| delaunay.distance | Distance on Delaunay Triangulation | |
| ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
| dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
| circumradius | Circumradius and Diameter of a Linear Network | |
| gorillas | Gorilla Nesting Sites | |
| fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |
| dilation | Morphological Dilation | |
| markvario | Mark Variogram | |
| colourmap | Colour Lookup Tables | |
| nnwhich.pp3 | Nearest neighbours in three dimensions | |
| disc | Circular Window | |
| is.im | Test Whether An Object Is A Pixel Image | |
| tiles | Extract List of Tiles in a Tessellation | |
| ripras | Estimate window from points alone | |
| as.tess | Convert Data To Tessellation | |
| data.ppm | Extract Original Data from a Fitted Point Process Model | |
| distmap | Distance Map | |
| interp.colourmap | Interpolate smoothly between specified colours | |
| clarkevans.test | Clark and Evans Test | |
| as.box3 | Convert Data to Three-Dimensional Box | |
| hybrid.family | Hybrid Interaction Family | |
| iplot | Point and Click Interface for Displaying Spatial Data | |
| by.im | Apply Function to Image Broken Down by Factor | |
| is.stationary | Recognise Stationary and Poisson Point Process Models | |
| chop.tess | Subdivide a Window or Tessellation using a Set of Lines | |
| lurking | Lurking variable plot | |
| erosion | Morphological Erosion | |
| is.marked.ppp | Test Whether A Point Pattern is Marked | |
| bw.frac | Bandwidth Selection Based on Window Geometry | |
| lut | Lookup Tables | |
| with.hyperframe | Evaluate an Expression in Each Row of a Hyperframe | |
| coef.slrm | Coefficients of Fitted Spatial Logistic Regression Model | |
| copper | Berman-Huntington points and lines data | |
| layered | Create List of Plotting Layers | |
| simulate.ppm | Simulate a Fitted Gibbs Point Process Model | |
| hyytiala | Scots pines and other trees at Hyytiala | |
| plot.slrm | Plot a Fitted Spatial Logistic Regression | |
| rescale.ppp | Convert Point Pattern to Another Unit of Length | |
| edge.Ripley | Ripley's Isotropic Edge Correction | |
| deltametric | Delta Metric | |
| effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model | |
| chicago | Chicago Street Crime Data | |
| linearKinhom | Inhomogeneous Linear K Function | |
| intensity.lpp | Empirical Intensity of Point Pattern on Linear Network | |
| intensity.ppm | Intensity of Fitted Point Process Model | |
| as.hyperframe | Convert Data to Hyperframe | |
| is.rectangle | Determine Type of Window | |
| km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
| clarkevans | Clark and Evans Aggregation Index | |
| vcov.kppm | Variance-Covariance Matrix for a Fitted Cluster Point Process Model | |
| rescue.rectangle | Convert Window Back To Rectangle | |
| rat | Ratio object | |
| envelope.envelope | Recompute Envelopes | |
| pppdist | Distance Between Two Point Patterns | |
| density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
| dirichlet | Dirichlet Tessellation of Point Pattern | |
| edges2vees | List Dihedral Triples in a Graph | |
| clusterset | Allard-Fraley Estimator of Cluster Feature | |
| quadrat.test.splitppp | Dispersion Test of CSR for Split Point Pattern Based on Quadrat Counts | |
| markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
| as.hyperframe.ppx | Extract coordinates and marks of multidimensional point pattern | |
| methods.layered | Methods for Layered Objects | |
| pairdist.lpp | Pairwise shortest-path distances between points on a linear network | |
| rounding | Detect Numerical Rounding | |
| linearpcfdot | Multitype Pair Correlation Function (Dot-type) for Linear Point Pattern | |
| methods.rho2hat | Methods for Intensity Functions of Two Spatial Covariates | |
| envelope | Simulation Envelopes of Summary Function | |
| osteo | Osteocyte Lacunae Data: Replicated Three-Dimensional Point Patterns | |
| envelope.pp3 | Simulation Envelopes of Summary Function for 3D Point Pattern | |
| suffstat | Sufficient Statistic of Point Process Model | |
| rjitter | Random Perturbation of a Point Pattern | |
| crossing.psp | Crossing Points of Two Line Segment Patterns | |
| diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
| linearKcross.inhom | Inhomogeneous multitype K Function (Cross-type) for Linear Point Pattern | |
| bronzefilter | Bronze gradient filter data | |
| imcov | Spatial Covariance of a Pixel Image | |
| is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
| timed | Record the Computation Time | |
| endpoints.psp | Endpoints of Line Segment Pattern | |
| rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
| nnmark | Mark of Nearest Neighbour | |
| methods.box3 | Methods for Three-Dimensional Box | |
| quad.object | Class of Quadrature Schemes | |
| reflect | Reflect In Origin | |
| predict.ppm | Prediction from a Fitted Point Process Model | |
| harmonise.im | Make Pixel Images Compatible | |
| inside.owin | Test Whether Points Are Inside A Window | |
| runifdisc | Generate N Uniform Random Points in a Disc | |
| rho2hat | Smoothed Relative Density of Pairs of Covariate Values | |
| msr | Signed or Vector-Valued Measure | |
| expand.owin | Apply Expansion Rule | |
| ponderosa | Ponderosa Pine Tree Point Pattern | |
| pool | Pool Data | |
| triplet.family | Triplet Interaction Family | |
| quadrats | Divide Region into Quadrats | |
| is.multitype | Test whether Object is Multitype | |
| superimpose | Superimpose Several Geometric Patterns | |
| cells | Biological Cells Point Pattern | |
| rescale.im | Convert Pixel Image to Another Unit of Length | |
| centroid.owin | Centroid of a window | |
| pointsOnLines | Place Points Evenly Along Specified Lines | |
| pool.rat | Pool Data from Several Ratio Objects | |
| scanpp | Read Point Pattern From Data File | |
| as.im | Convert to Pixel Image | |
| unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
| compatible.im | Test Whether Pixel Images Are Compatible | |
| spatstat-deprecated | Deprecated spatstat functions | |
| formula.fv | Extract or Change the Plot Formula for a Function Value Table | |
| ppm | Fit Point Process Model to Data | |
| duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
| kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
| linearmarkconnect | Mark Connection Function for Multitype Point Pattern on Linear Network | |
| rSSI | Simulate Simple Sequential Inhibition | |
| crossdist.pp3 | Pairwise distances between two different three-dimensional point patterns | |
| exactMPLEstrauss | Exact Maximum Pseudolikelihood Estimate for Stationary Strauss Process | |
| scalardilate | Apply Scalar Dilation | |
| quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
| mean.im | Maximum, Minimum, Mean, Median, Range or Sum of Pixel Values in an Image | |
| integral.im | Integral of a Pixel Image | |
| nearest.raster.point | Find Pixel Nearest to a Given Point | |
| crossdist.ppp | Pairwise distances between two different point patterns | |
| simulate.kppm | Simulate a Fitted Cluster Point Process Model | |
| vertices | Vertices of a Window | |
| colourtools | Convert and Compare Colours in Different Formats | |
| summary.im | Summarizing a Pixel Image | |
| scaletointerval | Rescale Data to Lie Between Specified Limits | |
| funxy | Spatial Function Class | |
| distmap.ppp | Distance Map of Point Pattern | |
| ippm | Optimise Irregular Trend Parameters in Point Process Model | |
| compatible.fasp | Test Whether Function Arrays Are Compatible | |
| union.quad | Union of Data and Dummy Points | |
| is.hybrid | Test Whether Object is a Hybrid | |
| pool.quadrattest | Pool Several Quadrat Tests | |
| envelope.lpp | Envelope for Point Patterns on Linear Network | |
| rNeymanScott | Simulate Neyman-Scott Process | |
| rcell | Simulate Baddeley-Silverman Cell Process | |
| smooth.ppp | Spatial smoothing of observations at irregular points | |
| concatxy | Concatenate x,y Coordinate Vectors | |
| pool.fasp | Pool Data from Several Function Arrays | |
| lansing | Lansing Woods Point Pattern | |
| rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
| residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
| vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
| quadscheme.logi | Generate a Logistic Regression Quadrature Scheme from a Point Pattern | |
| rescale.owin | Convert Window to Another Unit of Length | |
| profilepl | Profile Maximum Pseudolikelihood | |
| lpp | Create Point Pattern on Linear Network | |
| simdat | Simulated Point Pattern | |
| rmpoint | Generate N Random Multitype Points | |
| print.ppm | Print a Fitted Point Process Model | |
| quadratresample | Resample a Point Pattern by Resampling Quadrats | |
| clickppp | Interactively Add Points | |
| quadrat.test | Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
| rstrat | Simulate Stratified Random Point Pattern | |
| setcov | Set Covariance of a Window | |
| connected | Connected components | |
| summary.quad | Summarizing a Quadrature Scheme | |
| psstA | Pseudoscore Diagnostic For Fitted Model against Area-Interaction Alternative | |
| corners | Corners of a rectangle | |
| is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
| runiflpp | Uniform Random Points on a Linear Network | |
| tile.areas | Compute Areas of Tiles in a Tessellation | |
| as.linim | Convert to Pixel Image on Linear Network | |
| pairdist.psp | Pairwise distances between line segments | |
| rshift.ppp | Randomly Shift a Point Pattern | |
| simplify.owin | Approximate a Polygon by a Simpler Polygon | |
| update.kppm | Update a Fitted Cluster Point Process Model | |
| as.mask | Pixel Image Approximation of a Window | |
| spatstat-internal | Internal spatstat functions | |
| relrisk | Nonparametric Estimate of Spatially-Varying Relative Risk | |
| rlabel | Random Re-Labelling of Point Pattern | |
| as.lpp | Convert Data to a Point Pattern on a Linear Network | |
| rotate | Rotate | |
| rcellnumber | Generate Random Numbers of Points for Cell Process | |
| sidelengths.owin | Side Lengths of Enclosing Rectangle of a Window | |
| qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
| spatstat-package | The Spatstat Package | |
| default.dummy | Generate a Default Pattern of Dummy Points | |
| beginner | Print Introduction For Beginners | |
| rpoisline | Generate Poisson Random Line Process | |
| as.data.frame.im | Convert Pixel Image to Data Frame | |
| shift.im | Apply Vector Translation To Pixel Image | |
| rPoissonCluster | Simulate Poisson Cluster Process | |
| rpoislinetess | Poisson Line Tessellation | |
| round.ppp | Apply Numerical Rounding to Spatial Coordinates | |
| dilated.areas | Areas of Morphological Dilations | |
| dummify | Convert Data to Numeric Values by Constructing Dummy Variables | |
| print.im | Print Brief Details of an Image | |
| rshift.psp | Randomly Shift a Line Segment Pattern | |
| summary.psp | Summary of a Line Segment Pattern Dataset | |
| density.ppp | Kernel Smoothed Intensity of Point Pattern | |
| summary.ppp | Summary of a Point Pattern Dataset | |
| progressreport | Print Progress Reports | |
| simulate.slrm | Simulate a Fitted Spatial Logistic Regression Model | |
| rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |
| diameter.boxx | Geometrical Calculations for Multi-Dimensional Box | |
| rCauchy | Simulate Neyman-Scott Point Process with Cauchy cluster kernel | |
| bounding.box.xy | Convex Hull of Points | |
| blur | Apply Gaussian Blur to a Pixel Image | |
| vcov.slrm | Variance-Covariance Matrix for a Fitted Spatial Logistic Regression | |
| im.object | Class of Images | |
| scan.test | Spatial Scan Test | |
| spokes | Spokes pattern of dummy points | |
| connected.ppp | Connected components of a point pattern | |
| spruces | Spruces Point Pattern | |
| beachcolours | Create Colour Scheme for a Range of Numbers | |
| rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |
| chorley | Chorley-Ribble Cancer Data | |
| as.ppp | Convert Data To Class ppp | |
| clmfires | Castilla-La Mancha Forest Fires | |
| predict.lppm | Predict Point Process Model on Linear Network | |
| eval.linim | Evaluate Expression Involving Pixel Images on Linear Network | |
| rotate.ppp | Rotate a Point Pattern | |
| convolve.im | Convolution of Pixel Images | |
| psp | Create a Line Segment Pattern | |
| ppx | Multidimensional Space-Time Point Pattern | |
| eval.fasp | Evaluate Expression Involving Function Arrays | |
| influence.ppm | Influence Measure for Spatial Point Process Model | |
| plot.splitppp | Plot a List of Point Patterns | |
| fv.object | Function Value Table | |
| volume | Volume of an Object | |
| residuals.ppm | Residuals for Fitted Point Process Model | |
| crossdist.ppx | Pairwise Distances Between Two Different Multi-Dimensional Point Patterns | |
| crossdist.default | Pairwise distances between two different sets of points | |
| smooth.fv | Apply Smoothing to Function Values | |
| diameter.box3 | Geometrical Calculations for Three-Dimensional Box | |
| Iest | Estimate the I-function | |
| will.expand | Test Expansion Rule | |
| shift.psp | Apply Vector Translation To Line Segment Pattern | |
| unitname | Name for Unit of Length | |
| rGaussPoisson | Simulate Gauss-Poisson Process | |
| eroded.areas | Areas of Morphological Erosions | |
| cauchy.estpcf | Fit the Neyman-Scott cluster process with Cauchy kernel | |
| harmonic | Basis for Harmonic Functions | |
| rmpoispp | Generate Multitype Poisson Point Pattern | |
| Saturated | Saturated Pairwise Interaction model | |
| crossdist | Pairwise distances | |
| rknn | Theoretical Distribution of Nearest Neighbour Distance | |
| distcdf | Distribution Function of Interpoint Distance | |
| methods.linfun | Methods for Functions on Linear Network | |
| as.rectangle | Window Frame | |
| methods.linnet | Methods for Linear Networks | |
| fasp.object | Function Arrays for Spatial Patterns | |
| Smooth | Spatial smoothing of data | |
| nnfun.lpp | Nearest Neighbour Map on Linear Network | |
| distmap.owin | Distance Map of Window | |
| tilenames | Names of Tiles in a Tessellation | |
| rescale | Convert dataset to another unit of length | |
| bw.relrisk | Cross Validated Bandwidth Selection for Relative Risk Estimation | |
| gridcentres | Rectangular grid of points | |
| intensity | Intensity of a Dataset or a Model | |
| ppp.object | Class of Point Patterns | |
| psst | Pseudoscore Diagnostic For Fitted Model against General Alternative | |
| clickpoly | Interactively Define a Polygon | |
| collapse.fv | Collapse Several Function Tables into One | |
| rotate.psp | Rotate a Line Segment Pattern | |
| plot.psp | plot a Spatial Line Segment Pattern | |
| identify.ppp | Identify Points in a Point Pattern | |
| nndist.lpp | Nearest neighbour distances on a linear network | |
| plot.tess | Plot a tessellation | |
| rMosaicField | Mosaic Random Field | |
| inforder.family | Infinite Order Interaction Family | |
| complement.owin | Take Complement of a Window | |
| Jdot | Multitype J Function (i-to-any) | |
| cut.ppp | Classify Points in a Point Pattern | |
| is.convex | Test Whether a Window is Convex | |
| localpcf | Local pair correlation function | |
| clickjoin | Interactively join vertices on a plot | |
| eem | Exponential Energy Marks | |
| nnwhich.lpp | Identify Nearest Neighbours on a Linear Network | |
| rThomas | Simulate Thomas Process | |
| print.quad | Print a Quadrature Scheme | |
| rmhexpand | Specify Simulation Window or Expansion Rule | |
| thomas.estpcf | Fit the Thomas Point Process by Minimum Contrast | |
| convexhull | Convex Hull | |
| rhohat | Smoothing Estimate of Covariate Transformation | |
| quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
| gordon | People in Gordon Square | |
| fitted.slrm | Fitted Probabilities for Spatial Logistic Regression | |
| default.rmhcontrol | Set Default Control Parameters for Metropolis-Hastings Algorithm. | |
| rStrauss | Perfect Simulation of the Strauss Process | |
| BadGey | Hybrid Geyer Point Process Model | |
| ppp | Create a Point Pattern | |
| sessionLibs | Print Names and Version Numbers of Libraries Loaded | |
| deriv.fv | Calculate Derivative of Function Values | |
| valid.ppm | Check Whether Point Process Model is Valid | |
| rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |
| thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
| trim.rectangle | Cut margins from rectangle | |
| rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |
| rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
| eval.fv | Evaluate Expression Involving Functions | |
| flu | Influenza Virus Proteins | |
| identify.psp | Identify Segments in a Line Segment Pattern | |
| plot.ppp | plot a Spatial Point Pattern | |
| marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern | |
| hyperframe | Hyper Data Frame | |
| quantile.im | Sample Quantiles of Pixel Image | |
| raster.x | Cartesian Coordinates for a Pixel Raster | |
| discretise | Safely Convert Point Pattern Window to Binary Mask | |
| tweak.colourmap | Change Colour Values in a Colour Map | |
| linearKdot | Multitype K Function (Dot-type) for Linear Point Pattern | |
| redwood | California Redwoods Point Pattern (Ripley's Subset) | |
| varblock | Estimate Variance of Summary Statistic by Subdivision | |
| pool.envelope | Pool Data from Several Envelopes | |
| shapley | Galaxies in the Shapley Supercluster | |
| pp3 | Three Dimensional Point Pattern | |
| is.owin | Test Whether An Object Is A Window | |
| pixellate.ppp | Convert Point Pattern to Pixel Image | |
| rotate.owin | Rotate a Window | |
| pppmatching | Create a Point Matching | |
| rMatClust | Simulate Matern Cluster Process | |
| levelset | Level Set of a Pixel Image | |
| matchingdist | Distance for a Point Pattern Matching | |
| rHardcore | Perfect Simulation of the Hardcore Process | |
| urkiola | Urkiola Woods Point Pattern | |
| print.owin | Print Brief Details of a Spatial Window | |
| rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |
| as.function.fv | Convert Function Value Table to Function | |
| shift | Apply Vector Translation | |
| project2segment | Move Point To Nearest Line | |
| logLik.slrm | Loglikelihood of Spatial Logistic Regression | |
| Extract.owin | Extract Subset of Window | |
| predict.slrm | Predicted or Fitted Values from Spatial Logistic Regression | |
| as.data.frame.hyperframe | Coerce Hyperframe to Data Frame | |
| rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |
| rgbim | Create Colour-Valued Pixel Image | |
| transect.im | Pixel Values Along a Transect | |
| runifpoint3 | Generate N Uniform Random Points in Three Dimensions | |
| MultiHard | The Multitype Hard Core Point Process Model | |
| selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
| split.im | Divide Image Into Sub-images | |
| shift.owin | Apply Vector Translation To Window | |
| Extract.psp | Extract Subset of Line Segment Pattern | |
| rpoint | Generate N Random Points | |
| redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
| rLGCP | Simulate Log-Gaussian Cox Process | |
| whist | Weighted Histogram | |
| betacells | Beta Ganglion Cells in Cat Retina | |
| sumouter | Compute Quadratic Forms | |
| summary.owin | Summary of a Spatial Window | |
| rshift.splitppp | Randomly Shift a List of Point Patterns | |
| vargamma.estK | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |
| convexhull.xy | Convex Hull of Points | |
| rthin | Random Thinning | |
| project.ppm | Force Point Process Model to be Valid | |
| shift.ppp | Apply Vector Translation To Point Pattern | |
| Extract.splitppp | Extract or Replace Sub-Patterns | |
| areaLoss | Difference of Disc Areas | |
| update.ppm | Update a Fitted Point Process Model | |
| swedishpines | Swedish Pines Point Pattern | |
| anova.lppm | ANOVA for Fitted Point Process Models on Linear Network | |
| zapsmall.im | Rounding of Pixel Values | |
| solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
| Kcross.inhom | Inhomogeneous Cross K Function | |
| lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| Extract.ppx | Extract Subset of Multidimensional Point Pattern | |
| rpoispp | Generate Poisson Point Pattern | |
| dclf.test | Diggle-Cressie-Loosmore-Ford and Maximum Absolute Deviation Tests | |
| boxx | Multi-Dimensional Box | |
| interp.im | Interpolate a Pixel Image | |
| Jinhom | Inhomogeneous J-function | |
| flipxy | Exchange X and Y Coordinates | |
| rMaternII | Simulate Matern Model II | |
| plot.quad | plot a Spatial Quadrature Scheme | |
| Ginhom | Inhomogeneous Nearest Neighbour Function | |
| Ldot | Multitype L-function (i-to-any) | |
| print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
| methods.units | Methods for Units | |
| bw.smoothppp | Cross Validated Bandwidth Selection for Spatial Smoothing | |
| bdist.points | Distance to Boundary of Window | |
| Kmodel | K function of a model | |
| angles.psp | Orientation Angles of Line Segments | |
| simplenet | Simple Example of Linear Network | |
| infline | Infinite Straight Lines | |
| Emark | Diagnostics for random marking | |
| rMaternI | Simulate Matern Model I | |
| rpoislpp | Poisson Point Process on a Linear Network | |
| linfun | Function on a Linear Network | |
| rotate.im | Rotate a Pixel Image | |
| is.empty | Test Whether An Object Is Empty | |
| Softcore | The Soft Core Point Process Model | |
| psp.object | Class of Line Segment Patterns | |
| with.fv | Evaluate an Expression in a Function Table | |
| linearKcross | Multitype K Function (Cross-type) for Linear Point Pattern | |
| smooth.msr | Smooth a Signed or Vector-Valued Measure | |
| PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
| Kmeasure | Reduced Second Moment Measure | |
| kppm | Fit Cluster or Cox Point Process Model | |
| rsyst | Simulate systematic random point pattern | |
| linearpcfcross | Multitype Pair Correlation Function (Cross-type) for Linear Point Pattern | |
| rmh.ppm | Simulate from a Fitted Point Process Model | |
| LambertW | Lambert's W Function | |
| Poisson | Poisson Point Process Model | |
| Replace.im | Reset Values in Subset of Image | |
| plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
| Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
| is.ppp | Test Whether An Object Is A Point Pattern | |
| nnmap | K-th Nearest Point Map | |
| plot.listof | Plot a List of Things | |
| Kcom | Model Compensator of K Function | |
| split.ppx | Divide Multidimensional Point Pattern into Sub-patterns | |
| Ord | Generic Ord Interaction model | |
| Lest | L-function | |
| Kres | Residual K Function | |
| unmark | Remove Marks | |
| quadratcount | Quadrat counting for a point pattern | |
| anemones | Beadlet Anemones Data | |
| anova.ppm | ANOVA for Fitted Point Process Models | |
| stieltjes | Compute Integral of Function Against Cumulative Distribution | |
| pcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Type-i-To-Any-Type) | |
| npfun | Dummy Function Returns Number of Points | |
| Kscaled | Locally Scaled K-function | |
| summary.listof | Summary of a List of Things | |
| owin.object | Class owin | |
| heather | Diggle's Heather Data | |
| pcfcross | Multitype pair correlation function (cross-type) | |
| rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |
| plot.layered | Layered Plot | |
| plot.im | Plot a Pixel Image | |
| print.ppp | Print Brief Details of a Point Pattern Dataset | |
| Concom | The Connected Component Process Model | |
| stratrand | Stratified random point pattern | |
| Kdot | Multitype K Function (i-to-any) | |
| SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model | |
| sharpen | Data Sharpening of Point Pattern | |
| methods.funxy | Methods for Spatial Functions | |
| Lcross.inhom | Inhomogeneous Cross Type L Function | |
| plot.linnet | Plot a linear network | |
| areaGain | Difference of Disc Areas | |
| lohboot | Bootstrap Confidence Bands for Summary Function | |
| matclust.estpcf | Fit the Matern Cluster Point Process by Minimum Contrast Using Pair Correlation | |
| Kmulti | Marked K-Function | |
| markcorr | Mark Correlation Function | |
| square | Square Window | |
| Extract.tess | Extract or Replace Subset of Tessellation | |
| Kcross | Multitype K Function (Cross-type) | |
| linearpcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-type) for Linear Point Pattern | |
| rDGS | Perfect Simulation of the Diggle-Gates-Stibbard Process | |
| Finhom | Inhomogeneous Empty Space Function | |
| pairsat.family | Saturated Pairwise Interaction Point Process Family | |
| Extract.fasp | Extract Subset of Function Array | |
| split.ppp | Divide Point Pattern into Sub-patterns | |
| nncross.lpp | Nearest Neighbours on a Linear Network | |
| mucosa | Cells in Gastric Mucosa | |
| model.matrix.slrm | Extract Design Matrix from Spatial Logistic Regression Model | |
| K3est | K-function of a Three-Dimensional Point Pattern | |
| pcf.fv | Pair Correlation Function obtained from K Function | |
| npoints | Number of Points in a Point Pattern | |
| pairdist.default | Pairwise distances | |
| which.max.im | Identify Pixelwise Maximum of Several Pixel Images | |
| plot.fv | Plot Function Values | |
| plot.bermantest | Plot Result of Berman Test | |
| pairwise.family | Pairwise Interaction Process Family | |
| MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
| spatstat.options | Internal Options in Spatstat Package | |
| im | Create a Pixel Image Object | |
| Kmulti.inhom | Inhomogeneous Marked K-Function | |
| OrdThresh | Ord's Interaction model | |
| Gres | Residual G Function | |
| F3est | Empty Space Function of a Three-Dimensional Point Pattern | |
| affine.im | Apply Affine Transformation To Pixel Image | |
| overlap.owin | Compute Area of Overlap | |
| Jmulti | Marked J Function | |
| allstats | Calculate four standard summary functions of a point pattern. | |
| by.ppp | Apply a Function to a Point Pattern Broken Down by Factor | |
| alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern | |
| plot.colourmap | Plot a Colour Map | |
| runifpointx | Generate N Uniform Random Points in Any Dimensions | |
| waka | Trees in Waka national park | |
| unnormdensity | Weighted kernel smoother | |
| closing | Morphological Closing | |
| marks.psp | Marks of a Line Segment Pattern | |
| is.subset.owin | Determine Whether One Window is Contained In Another | |
| Gcom | Model Compensator of Nearest Neighbour Function | |
| localK | Neighbourhood density function | |
| owin | Create a Window | |
| methods.rhohat | Methods for Intensity Functions of Spatial Covariate | |
| DiggleGatesStibbard | Diggle-Gates-Stibbard Point Process Model | |
| paracou | Kimboto trees at Paracou, French Guiana | |
| hist.im | Histogram of Pixel Values in an Image | |
| bw.diggle | Cross Validated Bandwidth Selection for Kernel Density | |
| is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
| nztrees | New Zealand Trees Point Pattern | |
| periodify | Make Periodic Copies of a Spatial Pattern | |
| Extract.linnet | Extract Subset of Linear Network | |
| Hybrid | Hybrid Interaction Point Process Model | |
| linim | Create Pixel Image on Linear Network | |
| model.matrix.ppm | Extract Design Matrix from Point Process Model | |
| is.marked.ppm | Test Whether A Point Process Model is Marked | |
| intersect.owin | Intersection, Union or Set Subtraction of Two Windows | |
| pairs.im | Scatterplot Matrix for Pixel Images | |
| Fest | Estimate the empty space function F | |
| runifpoint | Generate N Uniform Random Points | |
| affine.linnet | Apply Geometrical Transformations to a Linear Network | |
| midpoints.psp | Midpoints of Line Segment Pattern | |
| Linhom | L-function | |
| localKinhom | Inhomogeneous Neighbourhood Density Function | |
| append.psp | Combine Two Line Segment Patterns | |
| Gfox | Foxall's Distance Functions | |
| kstest.ppm | Kolmogorov-Smirnov Test for Point Pattern or Point Process Model | |
| pairdist.pp3 | Pairwise distances in Three Dimensions | |
| rshift | Random Shift | |
| Lcross | Multitype L-function (cross-type) | |
| adaptive.density | Intensity Estimate of Point Pattern Using Tessellation | |
| psstG | Pseudoscore Diagnostic For Fitted Model against Saturation Alternative | |
| methods.ppx | Methods for Multidimensional Space-Time Point Patterns | |
| affine | Apply Affine Transformation | |
| plot.lppm | Plot a Fitted Point Process Model on a Linear Network | |
| Tstat | Third order summary statistic | |
| plot.pp3 | Plot a three-dimensional point pattern | |
| Extract.im | Extract Subset of Image | |
| logLik.ppm | Log Likelihood and AIC for Point Process Model | |
| leverage.ppm | Leverage Measure for Spatial Point Process Model | |
| fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
| rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
| murchison | Murchison gold deposits | |
| Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
| nsegments | Number of Line Segments in a Line Segment Pattern | |
| area.owin | Area of a Window | |
| nnclean | Nearest Neighbour Clutter Removal | |
| slrm | Spatial Logistic Regression | |
| methods.boxx | Methods for Multi-Dimensional Box | |
| nndist.ppx | Nearest Neighbour Distances in Any Dimensions | |
| summary.ppm | Summarizing a Fitted Point Process Model | |
| Kinhom | Inhomogeneous K-function | |
| mincontrast | Method of Minimum Contrast | |
| linnet | Create a Linear Network | |
| markcorrint | Mark Correlation Integral | |
| plot.hyperframe | Plot Entries in a Hyperframe | |
| plot.owin | Plot a Spatial Window | |
| vargamma.estpcf | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |
| opening | Morphological Opening | |
| predict.kppm | Prediction from a Fitted Cluster Point Process Model | |
| nearestsegment | Find Line Segment Nearest to Each Point | |
| pixellate.psp | Convert Line Segment Pattern to Pixel Image | |
| AreaInter | The Area Interaction Point Process Model | |
| anova.slrm | Analysis of Deviance for Spatial Logistic Regression Models | |
| rDiggleGratton | Perfect Simulation of the Diggle-Gratton Process | |
| pppmatching.object | Class of Point Matchings | |
| perimeter | Perimeter Length of Window | |
| affine.owin | Apply Affine Transformation To Window | |
| Kest.fft | K-function using FFT | |
| density.psp | Kernel Smoothing of Line Segment Pattern | |
| model.depends | Identify Covariates Involved in each Model Term | |
| Ldot.inhom | Inhomogeneous Multitype L Dot Function | |
| dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
| methods.lppm | Methods for Fitted Point Process Models on a Linear Network | |
| ants | Harkness-Isham ants' nests data | |
| G3est | Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern | |
| markconnect | Mark Connection Function | |
| humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
| linearpcf | Linear Pair Correlation Function | |
| pixelquad | Quadrature Scheme Based on Pixel Grid | |
| update.rmhcontrol | Update Control Parameters of Metropolis-Hastings Algorithm | |
| as.owin | Convert Data To Class owin | |
| runifpointOnLines | Generate N Uniform Random Points On Line Segments | |
| Hardcore | The Hard Core Point Process Model | |
| methods.slrm | Methods for Spatial Logistic Regression Models | |
| Triplets | The Triplet Point Process Model | |
| Hest | Spherical Contact Distribution Function | |
| edges2triangles | List Triangles in a Graph | |
| nnfun | Nearest Neighbour Map as a Function | |
| plot.kppm | Plot a fitted cluster point process | |
| pcfinhom | Inhomogeneous Pair Correlation Function | |
| Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
| japanesepines | Japanese Pines Point Pattern | |
| Geyer | Geyer's Saturation Point Process Model | |
| Extract.msr | Extract Subset of Signed or Vector Measure | |
| plot.msr | Plot a Signed or Vector-Valued Measure | |
| Pairwise | Generic Pairwise Interaction model | |
| Extract.ppp | Extract or Replace Subset of Point Pattern | |
| applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
| affine.psp | Apply Affine Transformation To Line Segment Pattern | |
| bw.stoyan | Stoyan's Rule of Thumb for Bandwidth Selection | |
| StraussHard | The Strauss / Hard Core Point Process Model | |
| Strauss | The Strauss Point Process Model | |
| Extract.fv | Extract Subset of Function Values | |
| nndist.psp | Nearest neighbour distances between line segments | |
| pcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-Type) | |
| Fiksel | The Fiksel Interaction | |
| Gest | Nearest Neighbour Distance Function G | |
| nnwhich | Nearest neighbour | |
| plot.leverage.ppm | Plot Leverage Function | |
| addvar | Added Variable Plot for Point Process Model | |
| Jest | Estimate the J-function | |
| Extract.lpp | Extract Subset of Point Pattern on Linear Network | |
| DiggleGratton | Diggle-Gratton model | |
| nndist.pp3 | Nearest neighbour distances in three dimensions | |
| is.lpp | Test Whether An Object Is A Point Pattern on a Linear Network | |
| MultiStrauss | The Multitype Strauss Point Process Model | |
| clip.infline | Intersect Infinite Straight Lines with a Window | |
| methods.kppm | Methods for Cluster Point Process Models | |
| distmap.psp | Distance Map of Line Segment Pattern | |
| pcf | Pair Correlation Function | |
| pairdist | Pairwise distances | |
| marks | Marks of a Point Pattern | |
| demopat | Artificial Data Point Pattern | |
| pairdist.ppx | Pairwise Distances in Any Dimensions | |
| plot.kstest | Plot a Spatial Kolmogorov-Smirnov Test | |
| istat | Point and Click Interface for Exploratory Analysis of Point Pattern | |
| longleaf | Longleaf Pines Point Pattern | |
| Gmulti | Marked Nearest Neighbour Distance Function | |
| incircle | Find Largest Circle Inside Window | |
| plot.ppm | plot a Fitted Point Process Model | |
| methods.lpp | Methods for Point Patterns on a Linear Network | |
| pcf.fasp | Pair Correlation Function obtained from array of K functions | |
| pixellate | Convert Spatial Object to Pixel Image | |
| affine.ppp | Apply Affine Transformation To Point Pattern | |
| nncorr | Nearest-Neighbour Correlation Indices of Marked Point Pattern | |
| linearK | Linear K Function | |
| persp.im | Perspective Plot of Pixel Image | |
| hamster | Aherne's hamster tumour data | |
| pcf3est | Pair Correlation Function of a Three-Dimensional Point Pattern | |
| plot.influence.ppm | Plot Influence Measure | |
| multiplicity.ppp | Count Multiplicity of Duplicate Points | |
| nnwhich.ppx | Nearest Neighbours in Any Dimensions | |
| nbfires | Point Patterns of New Brunswick Forest Fires | |
| plot.fasp | Plot a Function Array | |
| latest.news | Print News About Latest Version of Package | |
| Extract.layered | Extract Subset of a Layered Object | |
| miplot | Morishita Index Plot | |
| lppm | Fit Point Process Model to Point Pattern on Linear Network | |
| linearmarkequal | Mark Connection Function for Multitype Point Pattern on Linear Network | |
| Kest | K-function | |
| rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
| Extract.quad | Subset of Quadrature Scheme | |
| nncross.pp3 | Nearest Neighbours Between Two Patterns in 3D | |
| LennardJones | The Lennard-Jones Potential | |
| pixellate.owin | Convert Window to Pixel Image | |
| fryplot | Fry Plot of Point Pattern | |
| model.frame.ppm | Extract the Variables in a Point Process Model | |
| methods.fii | Methods for Fitted Interactions | |
| ord.family | Ord Interaction Process Family | |
| finpines | Pine saplings in Finland. | |
| Extract.listof | Extract or Replace Subset of a List of Things | |
| linearpcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Dot-type) for Linear Point Pattern | |
| plot.linim | Plot Pixel Image on Linear Network | |
| Jcross | Multitype J Function (i-to-j) | |
| amacrine | Hughes' Amacrine Cell Data | |
| affine.lpp | Apply Geometrical Transformations to Point Pattern on a Linear Network | |
| pcf.ppp | Pair Correlation Function of Point Pattern | |
| intensity.ppp | Empirical Intensity of Point Pattern | |
| nncross | Nearest Neighbours Between Two Patterns | |
| nndist | Nearest neighbour distances | |
| lgcp.estpcf | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| parres | Partial Residuals for Point Process Model | |
| linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |
| plot.envelope | Plot a Simulation Envelope | |
| pairdist.ppp | Pairwise distances | |
| pcfdot | Multitype pair correlation function (i-to-any) | |
| letterR | Window in Shape of Letter R | |
| No Results! | ||
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Details
| Date | 2013-10-24 |
| License | GPL (>= 2) |
| URL | http://www.spatstat.org |
| LazyData | true |
| LazyLoad | true |
| ByteCompile | true |
| Packaged | 2013-10-24 08:25:32 UTC; adrian |
| NeedsCompilation | yes |
| Repository | CRAN |
| Date/Publication | 2013-10-24 11:53:07 |
| depends | abind , base (>= 3.0.2) , deldir (>= 0.0-21) , graphics , grDevices , mgcv , polyclip , R (>= 3.0.2) , stats , tensor , utils |
| suggests | gsl , locfit , maptools , RandomFields (>= 2.0.60) , rpanel , scatterplot3d , sm , spatial , tkrplot |
| Contributors | Rolf Turner, Adrian Baddeley |
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