spatstat v1.21-0
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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 K-functions, 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 etc. Point process models can be fitted to point
pattern data using functions ppm, kppm, slrm similar to glm.
Models may include dependence on covariates, interpoint
interaction, cluster formation and dependence on marks. Fitted
models can be simulated automatically. Also provides facilities
for formal inference (such as chi-squared tests) and model
diagnostics (including simulation envelopes, residuals,
residual plots and Q-Q plots).
Functions in spatstat
| Name | Description | |
| Lest | L-function | |
| as.mask | Pixel Image Approximation of a Window | |
| Ldot.inhom | Inhomogeneous Multitype L Dot Function | |
| contour.im | Contour plot of pixel image | |
| as.data.frame.im | Convert Pixel Image to Data Frame | |
| Poisson | Poisson Point Process Model | |
| MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
| blur | Apply Gaussian Blur to a Pixel Image | |
| as.data.frame.psp | Coerce Line Segment Pattern to a Data Frame | |
| anova.ppm | ANOVA for Fitted Point Process Models | |
| bdist.pixels | Distance to Boundary of Window | |
| bounding.box.xy | Convex Hull of Points | |
| coef.ppm | Coefficients of Fitted Point Process Model | |
| eroded.areas | Areas of Morphological Erosions | |
| Saturated | Saturated Pairwise Interaction model | |
| integral.im | Integral of a Pixel Image | |
| PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
| hyperframe | Hyper Data Frame | |
| fryplot | Fry Plot of Point Pattern | |
| bw.relrisk | Cross Validated Bandwidth Selection for Relative Risk Estimation | |
| chop.tess | Subdivide a Window or Tessellation using a Set of Lines | |
| as.matrix.im | Convert Pixel Image to Matrix | |
| Linhom | L-function | |
| discpartarea | Area of Part of Disc | |
| border | Border Region of a Window | |
| LennardJones | The Lennard-Jones Potential | |
| as.im | Convert to Pixel Image | |
| bind.fv | Combine Function Value Tables | |
| areaGain | Difference of Disc Areas | |
| is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
| fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |
| midpoints.psp | Midpoints of Line Segment Pattern | |
| centroid.owin | Centroid of a window | |
| bermantest | Berman's Tests for Point Process Model | |
| complement.owin | Take Complement of a Window | |
| methods.ppx | Methods for Multidimensional Space-Time Point Patterns | |
| cut.ppp | Classify Points in a Point Pattern | |
| fv | Create a Function Value Table | |
| as.tess | Convert Data To Tessellation | |
| density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
| crossing.psp | Crossing Points of Two Line Segment Patterns | |
| ord.family | Ord Interaction Process Family | |
| intersect.tess | Intersection of Two Tessellations | |
| areaLoss | Difference of Disc Areas | |
| colourtools | Convert and Compare Colours in Different Formats | |
| compatible.im | Test Whether Two Pixel Images Are Compatible | |
| anemones | Beadlet Anemones Data | |
| mean.im | Maximum, Minimum, Mean, Median, Range or Sum of Pixel Values in an Image | |
| markcorr | Mark Correlation Function | |
| clip.infline | Intersect Infinite Straight Lines with a Window | |
| methods.distfun | Methods for Distance Functions | |
| amacrine | Hughes' Amacrine Cell Data | |
| crossdist.psp | Pairwise distances between two different line segment patterns | |
| identify.psp | Identify Segments in a Line Segment Pattern | |
| convexhull.xy | Convex Hull of Points | |
| eem | Exponential Energy Marks | |
| is.marked.ppp | Test Whether A Point Pattern is Marked | |
| collapse.fv | Collapse Several Function Tables into One | |
| deltametric | Delta Metric | |
| mincontrast | Method of Minimum Contrast | |
| expand.owin | Expand Window By Factor | |
| boxx | Multi-Dimensional Box | |
| allstats | Calculate four standard summary functions of a point pattern. | |
| density.ppp | Kernel Smoothed Intensity of Point Pattern | |
| Pairwise | Generic Pairwise Interaction model | |
| applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
| bdist.tiles | Distance to Boundary of Window | |
| cbind.hyperframe | Combine Hyperframes by Rows or by Columns | |
| model.frame.ppm | Extract the Environment of a Point Process Model | |
| colourmap | Colour Lookup Tables | |
| Softcore | The Soft Core Point Process Model | |
| bramblecanes | Hutchings' Bramble Canes data | |
| Ldot | Multitype L-function (i-to-any) | |
| as.owin | Convert Data To Class owin | |
| fasp.object | Function Arrays for Spatial Patterns | |
| as.hyperframe.ppx | Extract coordinates and marks of multidimensional point pattern | |
| corners | Corners of a rectangle | |
| harmonic | Basis for Harmonic Functions | |
| crossdist.default | Pairwise distances between two different sets of points | |
| heather | Diggle's Heather Data | |
| gridcentres | Rectangular grid of points | |
| print.im | Print Brief Details of an Image | |
| longleaf | Longleaf Pines Point Pattern | |
| adaptive.density | Intensity Estimate of Point Pattern Using Tessellation | |
| rcell | Simulate Baddeley-Silverman Cell Process | |
| as.hyperframe | Convert Data to Hyperframe | |
| endpoints.psp | Endpoints of Line Segment Pattern | |
| eval.fv | Evaluate Expression Involving Functions | |
| ppp | Create a Point Pattern | |
| hamster | Aherne's hamster tumour data | |
| affine.owin | Apply Affine Transformation To Window | |
| bdist.points | Distance to Boundary of Window | |
| rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |
| pcfinhom | Inhomogeneous Pair Correlation Function | |
| distfun | Distance Map as a Function | |
| spatstat-internal | Internal spatstat functions | |
| matchingdist | Distance for a Point Pattern Matching | |
| periodify | Make Periodic Copies of a Spatial Pattern | |
| crossdist.ppp | Pairwise distances between two different point patterns | |
| distmap.ppp | Distance Map of Point Pattern | |
| pixellate.owin | Convert Window to Pixel Image | |
| km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
| data.ppm | Extract Original Data from a Fitted Point Process Model | |
| persp.im | Perspective Plot of Pixel Image | |
| is.subset.owin | Determine Whether One Window is Contained In Another | |
| disc | Circular Window | |
| marks | Marks of a Point Pattern | |
| ants | Harkness-Isham ants' nests data | |
| levelset | Level Set of a Pixel Image | |
| intersect.owin | Intersection, Union or Set Subtraction of Two Windows | |
| clickpoly | Interactively Define a Polygon | |
| by.ppp | Apply a Function to a Point Pattern Broken Down by Factor | |
| MultiStrauss | The Multitype Strauss Point Process Model | |
| letterR | Window in Shape of Letter R | |
| spatstat-deprecated | Deprecated spatstat functions | |
| diameter.boxx | Geometrical Calculations for Multi-Dimensional Box | |
| fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
| compatible.fv | Test Whether Two Function Objects Are Compatible | |
| compatible.fasp | Test Whether Two Function Arrays Are Compatible | |
| diameter.owin | Diameter of a Window | |
| is.marked.ppm | Test Whether A Point Process Model is Marked | |
| print.owin | Print Brief Details of a Spatial Window | |
| nearest.raster.point | Find Pixel Nearest to a Given Point | |
| gridweights | Compute Quadrature Weights Based on Grid Counts | |
| cut.im | Convert Pixel Image from Numeric to Factor | |
| plot.quad | plot a Spatial Quadrature Scheme | |
| is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
| dirichlet | Dirichlet Tessellation of Point Pattern | |
| ewcdf | Weighted Empirical Cumulative Distribution Function | |
| as.data.frame.hyperframe | Coerce Hyperframe to Data Frame | |
| erosion | Morphological Erosion | |
| kstest.ppm | Kolmogorov-Smirnov Test for Point Process Model | |
| area.owin | Area of a Window | |
| pppdist | Distance Between Two Point Patterns | |
| is.marked | Test Whether Marks Are Present | |
| im.object | Class of Images | |
| localpcf | Local pair correlation function | |
| copper | Berman-Huntington points and lines data | |
| is.ppp | Test Whether An Object Is A Point Pattern | |
| delaunay | Delaunay Triangulation of Point Pattern | |
| clarkevans | Clark and Evans Aggregation Index | |
| quadrat.test | Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
| pixelquad | Quadrature Scheme Based on Pixel Grid | |
| psp.object | Class of Line Segment Patterns | |
| rGaussPoisson | Simulate Gauss-Poisson Process | |
| Lcross.inhom | Inhomogeneous Cross Type L Function | |
| is.convex | Test Whether a Window is Convex | |
| coef.slrm | Coefficients of Fitted Spatial Logistic Regression Model | |
| diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
| diameter.box3 | Geometrical Calculations for Three-Dimensional Box | |
| redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
| inside.owin | Test Whether Points Are Inside A Window | |
| markvario | Mark Variogram | |
| split.ppp | Divide Point Pattern into Sub-patterns | |
| as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |
| murchison | Murchison gold deposits | |
| distmap.owin | Distance Map of Window | |
| hist.im | Histogram of Pixel Values in an Image | |
| pp3 | Three Dimensional Point Pattern | |
| nndist.ppx | Nearest Neighbour Distances in Any Dimensions | |
| inforder.family | Infinite Order Interaction Family | |
| Lcross | Multitype L-function (cross-type) | |
| reach | Interaction Distance of a Point Process | |
| nztrees | New Zealand Trees Point Pattern | |
| quadrat.test.splitppp | Chi-Squared Test of CSR for Split Point Pattern | |
| dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
| nnwhich.pp3 | Nearest neighbours in three dimensions | |
| plot.ppp | plot a Spatial Point Pattern | |
| OrdThresh | Ord's Interaction model | |
| nnclean | Nearest Neighbour Clutter Removal | |
| bei | Tropical rain forest trees | |
| japanesepines | Japanese Pines Point Pattern | |
| rescale.owin | Convert Window to Another Unit of Length | |
| StraussHard | The Strauss / Hard Core Point Process Model | |
| duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
| identify.ppp | Identify Points in a Point Pattern | |
| plot.envelope | Plot a Simulation Envelope | |
| lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| discretise | Safely Convert Point Pattern Window to Binary Mask | |
| pixellate.psp | Convert Line Segment Pattern to Pixel Image | |
| methods.box3 | Methods for Three-Dimensional Box | |
| dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
| nndist.psp | Nearest neighbour distances between line segments | |
| methods.pp3 | Methods for three-dimensional point patterns | |
| crossdist | Pairwise distances | |
| plot.owin | Plot a Spatial Window | |
| is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
| Replace.im | Reset Values in Subset of Image | |
| model.matrix.ppm | Extract Design Matrix from Point Process Model | |
| summary.listof | Summary of a List of Things | |
| pixellate.ppp | Convert Point Pattern to Pixel Image | |
| interp.im | Interpolate a Pixel Image | |
| plot.splitppp | Plot a List of Point Patterns | |
| redwood | California Redwoods Point Pattern (Ripley's Subset) | |
| rescue.rectangle | Convert Window Back To Rectangle | |
| print.ppp | Print Brief Details of a Point Pattern Dataset | |
| rlinegrid | Generate grid of parallel lines with random displacement | |
| affine.ppp | Apply Affine Transformation To Point Pattern | |
| dilated.areas | Areas of Morphological Dilations | |
| owin.object | Class owin | |
| angles.psp | Orientation Angles of Line Segments | |
| eval.fasp | Evaluate Expression Involving Function Arrays | |
| distmap.psp | Distance Map of Line Segment Pattern | |
| as.rectangle | Window Frame | |
| profilepl | Profile Maximum Pseudolikelihood | |
| predict.slrm | Predicted or Fitted Values from Spatial Logistic Regression | |
| vertices | Vertices of a Window | |
| matclust.estpcf | Fit the Matern Cluster Point Process by Minimum Contrast Using Pair Correlation | |
| crossdist.pp3 | Pairwise distances between two different three-dimensional point patterns | |
| pcf | Pair Correlation Function | |
| rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
| lurking | Lurking variable plot | |
| lgcp.estpcf | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| simdat | Simulated Point Pattern | |
| kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
| plot.psp | plot a Spatial Line Segment Pattern | |
| pairdist.pp3 | Pairwise distances in Three Dimensions | |
| summary.owin | Summary of a Spatial Window | |
| lansing | Lansing Woods Point Pattern | |
| latest.news | Print News About Latest Version of Package | |
| spatstat.options | Internal Options in Spatstat Package | |
| rshift.ppp | Randomly Shift a Point Pattern | |
| pcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Type-i-To-Any-Type) | |
| unitname | Name for Unit of Length | |
| miplot | Morishita Index Plot | |
| istat | Point and Click Interface for Exploratory Analysis of Point Pattern | |
| progressreport | Print Progress Reports | |
| ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
| ripras | Estimate window from points alone | |
| eval.im | Evaluate Expression Involving Pixel Images | |
| pixellate | Convert Spatial Object to Pixel Image | |
| plot.fv | Plot Function Values | |
| plot.colourmap | Plot a Colour Map | |
| swedishpines | Swedish Pines Point Pattern | |
| residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
| runifpointOnLines | Generate N Uniform Random Points On Line Segments | |
| envelope.pp3 | Simulation Envelopes of Summary Function for 3D Point Pattern | |
| nnwhich.ppx | Nearest Neighbours in Any Dimensions | |
| print.quad | Print a Quadrature Scheme | |
| nncross | Nearest Neighbours Between Two Patterns | |
| quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
| density.psp | Kernel Smoothing of Line Segment Pattern | |
| as.polygonal | Convert a Window to a Polygonal Window | |
| pairdist.psp | Pairwise distances between line segments | |
| Ord | Generic Ord Interaction model | |
| ppm.object | Class of Fitted Point Process Models | |
| marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern | |
| plot.slrm | Plot a Fitted Spatial Logistic Regression | |
| is.empty | Test Whether An Object Is Empty | |
| fv.object | Data Frames of Function Values | |
| plot.fasp | Plot a Function Array | |
| nndist | Nearest neighbour distances | |
| pcf.fv | Pair Correlation Function obtained from K Function | |
| is.owin | Test Whether An Object Is A Window | |
| summary.quad | Summarizing a Quadrature Scheme | |
| infline | Infinite Straight Lines | |
| spruces | Spruces Point Pattern | |
| rMaternII | Simulate Matern Model II | |
| is.im | Test Whether An Object Is A Pixel Image | |
| anova.slrm | Analysis of Deviance for Spatial Logistic Regression Models | |
| humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
| as.psp | Convert Data To Class psp | |
| rescale | Convert dataset to another unit of length | |
| pairs.im | Scatterplot Matrix for Pixel Images | |
| concatxy | Concatenate x,y Coordinate Vectors | |
| split.im | Divide Image Into Sub-images | |
| simulate.ppm | Simulate a Fitted Gibbs Point Process Model | |
| quadrats | Divide Region into Quadrats | |
| thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
| rknn | Theoretical Distribution of Nearest Neighbour Distance | |
| osteo | Osteocyte Lacunae Data: Replicated Three-Dimensional Point Patterns | |
| cells | Biological Cells Point Pattern | |
| envelope | Simulation Envelopes of Summary Function | |
| nbfires | Point Patterns of New Brunswick Forest Fires | |
| coords | Extract Coordinates of a Spatial or Spatiotemporal Point Pattern | |
| print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
| qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
| rSSI | Simulate Simple Sequential Inhibition | |
| reduced.sample | Reduced Sample Estimator using Histogram Data | |
| pppmatching.object | Class of Point Matchings | |
| urkiola | Urkiola Woods Point Pattern | |
| spatstat-package | The Spatstat Package | |
| trim.rectangle | Cut margins from rectangle | |
| convexhull | Convex Hull | |
| default.expand | Compute Expansion Window for Simulation | |
| rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |
| nearestsegment | Find Line Segment Nearest to Each Point | |
| pcf.fasp | Pair Correlation Function obtained from array of K functions | |
| pcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-Type) | |
| bronzefilter | Bronze gradient filter data | |
| logLik.slrm | Loglikelihood of Spatial Logistic Regression | |
| default.rmhcontrol | Set Default Control Parameters for Metropolis-Hastings Algorithm. | |
| pairsat.family | Saturated Pairwise Interaction Point Process Family | |
| scanpp | Read Point Pattern From Data File | |
| spokes | Spokes pattern of dummy points | |
| suffstat | Sufficient Statistic of Point Process Model | |
| as.ppp | Convert Data To Class ppp | |
| shift.psp | Apply Vector Translation To Line Segment Pattern | |
| SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model | |
| pppmatching | Create a Point Matching | |
| owin | Create a Window | |
| markconnect | Mark Connection Function | |
| superimposePSP | Superimpose Several Line Segment Patterns | |
| quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
| rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |
| sharpen | Data Sharpening of Point Pattern | |
| square | Square Window | |
| model.images | Compute Images of Constructed Covariates | |
| lengths.psp | Lengths of Line Segments | |
| plot.tess | Plot a tessellation | |
| box3 | Three-Dimensional Box | |
| pairdist | Pairwise distances | |
| plot.pp3 | Plot a three-dimensional point pattern | |
| rpoislinetess | Poisson Line Tessellation | |
| runifpointx | Generate N Uniform Random Points in Any Dimensions | |
| betacells | Beta Ganglion Cells in Cat Retina | |
| plot.listof | Plot a List of Things | |
| lut | Lookup Tables | |
| quadratresample | Resample a Point Pattern by Resampling Quadrats | |
| thomas.estpcf | Fit the Thomas Point Process by Minimum Contrast | |
| shapley | Galaxies in the Shapley Supercluster | |
| rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
| predict.ppm | Prediction from a Fitted Point Process Model | |
| nnwhich | Nearest neighbour | |
| rotate.ppp | Rotate a Point Pattern | |
| localK | Neighbourhood density function | |
| multiplicity.ppp | Count Multiplicity of Duplicate Points | |
| rpoint | Generate N Random Points | |
| Strauss | The Strauss Point Process Model | |
| rotate | Rotate | |
| pairwise.family | Pairwise Interaction Process Family | |
| ponderosa | Ponderosa Pine Tree Point Pattern | |
| rescale.ppp | Convert Point Pattern to Another Unit of Length | |
| rmh.ppm | Simulate from a Fitted Point Process Model | |
| im | Create a Pixel Image Object | |
| pcf3est | Pair Correlation Function of a Three-Dimensional Point Pattern | |
| plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
| shift.ppp | Apply Vector Translation To Point Pattern | |
| print.ppm | Print a Fitted Point Process Model | |
| fitted.slrm | Fitted Probabilities for Spatial Logistic Regression | |
| iplot | Point and Click Interface for Displaying a Point Pattern | |
| crossdist.ppx | Pairwise Distances Between Two Different Multi-Dimensional Point Patterns | |
| methods.boxx | Methods for Multi-Dimensional Box | |
| plot.bermantest | Plot Result of Berman Test | |
| rmpoispp | Generate Multitype Poisson Point Pattern | |
| vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
| effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model | |
| affine | Apply Affine Transformation | |
| pointsOnLines | Place Points Evenly Along Specified Lines | |
| diameter | Diameter of an Object | |
| shift.im | Apply Vector Translation To Pixel Image | |
| rotate.owin | Rotate a Window | |
| raster.x | Cartesian Coordinates for a Pixel Raster | |
| summary.ppp | Summary of a Point Pattern Dataset | |
| rsyst | Simulate systematic random point pattern | |
| summary.psp | Summary of a Line Segment Pattern Dataset | |
| rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |
| rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |
| as.mask.psp | Convert Line Segment Pattern to Binary Pixel Mask | |
| quantile.im | Sample Quantiles of Pixel Image | |
| summary.im | Summarizing a Pixel Image | |
| predict.kppm | Prediction from a Fitted Cluster Point Process Model | |
| ppp.object | Class of Point Patterns | |
| rpoispp | Generate Poisson Point Pattern | |
| pairdist.ppx | Pairwise Distances in Any Dimensions | |
| rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |
| shift | Apply Vector Translation | |
| rshift.splitppp | Randomly Shift a List of Point Patterns | |
| affine.psp | Apply Affine Transformation To Line Segment Pattern | |
| simulate.kppm | Simulate a Fitted Cluster Point Process Model | |
| rMaternI | Simulate Matern Model I | |
| superimpose | Superimpose Several Point Patterns | |
| solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
| project2segment | Move Point To Nearest Line | |
| with.hyperframe | Evaluate an Expression in Each Row of a Hyperframe | |
| rotate.psp | Rotate a Line Segment Pattern | |
| chorley | Chorley-Ribble Cancer Data | |
| clickppp | Interactively Add Points | |
| bounding.box | Bounding Box of a Window or Point Pattern | |
| rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
| runifpoint | Generate N Uniform Random Points | |
| update.ppm | Update a Fitted Point Process Model | |
| unmark | Remove Marks | |
| gpc2owin | Convert Polygonal Region into Different Format | |
| rThomas | Simulate Thomas Process | |
| default.dummy | Generate a Default Pattern of Dummy Points | |
| incircle | Find Largest Circle Inside Window | |
| connected | Connected components of an image or window | |
| distmap | Distance Map | |
| rescale.im | Convert Pixel Image to Another Unit of Length | |
| pairdist.ppp | Pairwise distances | |
| rthin | Random Thinning | |
| rMatClust | Simulate Matern Cluster Process | |
| markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
| as.box3 | Convert Data to Three-Dimensional Box | |
| slrm | Spatial Logistic Regression | |
| plot.kppm | Plot a fitted cluster point process | |
| summary.ppm | Summarizing a Fitted Point Process Model | |
| rmpoint | Generate N Random Multitype Points | |
| smooth.ppp | Spatial smoothing of observations at irregular points | |
| is.multitype | Test whether Object is Multitype | |
| rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |
| rMosaicSet | Mosaic Random Set | |
| demopat | Artificial Data Point Pattern | |
| rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
| whist | Weighted Histogram | |
| tess | Create a Tessellation | |
| rNeymanScott | Simulate Neyman-Scott Process | |
| quad.object | Class of Quadrature Schemes | |
| rjitter | Random Perturbation of a Point Pattern | |
| setcov | Set Covariance of a Window | |
| pairdist.default | Pairwise distances | |
| rStrauss | Perfect Simulation of the Strauss Process | |
| unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
| finpines | Pine saplings in Finland. | |
| shift.owin | Apply Vector Translation To Window | |
| kppm | Fit cluster point process model | |
| nndist.pp3 | Nearest neighbour distances in three dimensions | |
| pcfcross | Multitype pair correlation function (cross-type) | |
| relrisk | Nonparametric Estimate of Spatially-Varying Relative Risk | |
| update.kppm | Update a Fitted Cluster Point Process Model | |
| plot.kstest | Plot a Spatial Kolmogorov-Smirnov Test | |
| rstrat | Simulate Stratified Random Point Pattern | |
| perimeter | Perimeter Length of Window | |
| dilation | Morphological Dilation | |
| selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
| closing | Morphological Closing | |
| with.fv | Evaluate an Expression in a Function Table | |
| plot.im | Plot a Pixel Image | |
| rshift.psp | Randomly Shift a Line Segment Pattern | |
| psp | Create a Line Segment Pattern | |
| plot.ppm | plot a Fitted Point Process Model | |
| pcf.ppp | Pair Correlation Function of Point Pattern | |
| npoints | Number of Points in a Point Pattern | |
| Kest | K-function | |
| Jest | Estimate the J-function | |
| opening | Morphological Opening | |
| ppm | Fit Point Process Model to Data | |
| matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
| residuals.ppm | Residuals for Fitted Point Process Model | |
| append.psp | Combine Two Line Segment Patterns | |
| Kcross.inhom | Inhomogeneous Cross K Function | |
| rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
| pcfdot | Multitype pair correlation function (i-to-any) | |
| runifdisc | Generate N Uniform Random Points in a Disc | |
| Fiksel | The Fiksel Interaction | |
| F3est | Empty Space Function of a Three-Dimensional Point Pattern | |
| Gmulti | Marked Nearest Neighbour Distance Function | |
| DiggleGratton | Diggle-Gratton model | |
| quadratcount | Quadrat counting for a point pattern | |
| nncorr | Nearest-Neighbour Correlation Indices of Marked Point Pattern | |
| Jcross | Multitype J Function (i-to-j) | |
| G3est | Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern | |
| ppx | Multidimensional Space-Time Point Pattern | |
| K3est | K-function of a Three-Dimensional Point Pattern | |
| Kdot | Multitype K Function (i-to-any) | |
| by.im | Apply Function to Image Broken Down by Factor | |
| Kmulti | Marked K-Function | |
| Hardcore | The Hard Core Point Process Model | |
| Kcross | Multitype K Function (Cross-type) | |
| alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern | |
| plot.hyperframe | Plot Entries in a Hyperframe | |
| Geyer | Geyer's Saturation Point Process Model | |
| Kest.fft | K-function using FFT | |
| Gfox | Foxall's Distance Functions | |
| Hest | Spherical Contact Distribution Function | |
| DiggleGatesStibbard | Diggle-Gates-Stibbard Point Process Model | |
| rMosaicField | Mosaic Random Field | |
| Extract.splitppp | Extract or Replace Sub-Patterns | |
| rlabel | Random Re-Labelling of Point Pattern | |
| simplify.owin | Approximate a Polygon by a Simpler Polygon | |
| Jmulti | Marked J Function | |
| smooth.fv | Apply Smoothing to Function Values | |
| Extract.listof | Extract or Replace Subset of a List of Things | |
| Extract.fasp | Extract Subset of Function Array | |
| rpoisline | Generate Poisson Random Line Process | |
| Iest | Estimate the I-function | |
| Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
| Kscaled | Locally Scaled K-function | |
| stieltjes | Compute Integral of Function Against Cumulative Distribution | |
| Extract.ppp | Extract or Replace Subset of Point Pattern | |
| rshift | Random Shift | |
| Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
| markcorrint | Mark Correlation Integral | |
| Extract.im | Extract Subset of Image | |
| Extract.psp | Extract Subset of Line Segment Pattern | |
| Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
| AreaInter | The Area Interaction Point Process Model | |
| Kinhom | Inhomogeneous K-function | |
| runifpoint3 | Generate N Uniform Random Points in Three Dimensions | |
| Extract.quad | Subset of Quadrature Scheme | |
| BadGey | Hybrid Geyer Point Process Model | |
| summary.splitppp | Summary of a Split Point Pattern | |
| volume | Volume of an Object | |
| tiles | Extract List of Tiles in a Tessellation | |
| Kmeasure | Reduced Second Moment Measure | |
| Extract.fv | Extract Subset of Function Values | |
| Gest | Nearest Neighbour Distance Function G | |
| union.quad | Union of Data and Dummy Points | |
| Fest | Estimate the empty space function F | |
| Extract.tess | Extract or Replace Subset of Tessellation | |
| Jdot | Multitype J Function (i-to-any) | |
| logLik.ppm | Log Likelihood for Poisson Point Process Model | |
| Emark | Diagnostics for random marking | |
| No Results! | ||
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Details
| Date | 2010-11-05 |
| License | GPL (>= 2) |
| URL | http://www.spatstat.org |
| Packaged | 2010-11-05 02:41:21 UTC; adrian |
| Repository | CRAN |
| Date/Publication | 2010-11-05 20:03:15 |
| depends | base (>= 2.10.0) , deldir (>= 0.0-10) , graphics , mgcv , R (>= 2.10.0) , stats , utils |
| suggests | gpclib , maptools , rpanel , scatterplot3d , sm , tkrplot |
| Contributors | Rolf Turner, Adrian Baddeley |
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