spatstat v1.16-2
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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. Contains
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, and pixel images. Point
process models can be fitted to point pattern data. Cluster
type models are fitted by the method of minimum contrast. Very
general Gibbs point process models can be fitted to point
pattern data using a function ppm similar to lm or glm. Models
may include dependence on covariates, interpoint interaction
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 | |
| convexhull | Convex Hull | |
| crossdist.ppp | Pairwise distances between two different point patterns | |
| distmap | Distance Map | |
| diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
| im | Create a Pixel Image Object | |
| print.quad | Print a Quadrature Scheme | |
| pixellate.owin | Convert Window to Pixel Image | |
| disc | Circular Window | |
| rMaternII | Simulate Matern Model II | |
| density.ppp | Kernel Smoothed Intensity of Point Pattern | |
| copper | Berman-Huntington points and lines data | |
| logLik.ppm | Log Likelihood for Poisson Point Process Model | |
| is.owin | Test Whether An Object Is A Window | |
| intersect.owin | Intersection or Union of Two Windows | |
| markconnect | Mark Connection Function | |
| crossdist | Pairwise distances | |
| pcf.fasp | Pair Correlation Function obtained from array of K functions | |
| shift.owin | Apply Vector Translation To Window | |
| pairdist.default | Pairwise distances | |
| matchingdist | Distance for a Point Pattern Matching | |
| summary.listof | Summary of a List of Things | |
| dilated.areas | Areas of Morphological Dilations | |
| lansing | Lansing Woods Point Pattern | |
| rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
| nndist.psp | Nearest neighbour distances between line segments | |
| nearestsegment | Find Line Segment Nearest to Each Point | |
| is.subset.owin | Determine Whether One Window is Contained In Another | |
| rescale.owin | Convert Window to Another Unit of Length | |
| nncross | Nearest Neighbours Between Two Patterns | |
| rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
| suffstat | Sufficient Statistic of Point Process Model | |
| kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
| plot.im | Plot a Pixel Image | |
| opening | Morphological Opening | |
| ppp.object | Class of Point Patterns | |
| is.marked.ppp | Test Whether A Point Pattern is Marked | |
| plot.quad | plot a Spatial Quadrature Scheme | |
| tess | Create a Tessellation | |
| markcorr | Mark Correlation Function | |
| rescale.im | Convert Pixel Image to Another Unit of Length | |
| concatxy | Concatenate x,y Coordinate Vectors | |
| dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
| plot.psp | plot a Spatial Line Segment Pattern | |
| rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
| ppp | Create a Point Pattern | |
| im.object | Class of Images | |
| pcf.ppp | Pair Correlation Function of Point Pattern | |
| residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
| nearest.raster.point | Find Pixel Nearest to a Given Point | |
| pcfcross | Multitype pair correlation function | |
| quadratresample | Resample a Point Pattern by Resampling Quadrats | |
| rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |
| is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
| is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
| rMosaicField | Mosaic Random Field | |
| rSSI | Simulate Simple Sequential Inhibition | |
| crossing.psp | Crossing Points of Two Line Segment Patterns | |
| marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern | |
| project2segment | Move Point To Nearest Line | |
| solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
| km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
| lut | Lookup Tables | |
| matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
| shift.psp | Apply Vector Translation To Line Segment Pattern | |
| is.convex | Test Whether a Window is Convex | |
| nndist | Nearest neighbour distances | |
| plot.kstest | Plot a Spatial Kolmogorov-Smirnov Test | |
| rMosaicSet | Mosaic Random Set | |
| convexhull.xy | Convex Hull of Points | |
| istat | Point and Click Interface for Exploratory Analysis of Point Pattern | |
| rotate.ppp | Rotate a Point Pattern | |
| markcorrint | Mark Correlation Integral | |
| owin.object | Class owin | |
| compatible.fasp | Test Whether Two Function Arrays Are Compatible | |
| vertices | Vertices of a Window | |
| kppm | Fit cluster point process model | |
| delaunay | Delaunay Triangulation of Point Pattern | |
| clip.infline | Intersect Infinite Straight Lines with a Window | |
| cut.ppp | Classify Points in a Point Pattern | |
| compatible.fv | Test Whether Two Function Objects Are Compatible | |
| pcf.fv | Pair Correlation Function obtained from K Function | |
| reach | Interaction Distance of a Point Process | |
| is.empty | Test Whether An Object Is Empty | |
| redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
| owin | Create a Window | |
| density.psp | Kernel Smoothing of Line Segment Pattern | |
| superimposePSP | Superimpose Several Line Segment Patterns | |
| plot.splitppp | Plot a List of Point Patterns | |
| predict.kppm | Prediction from a Fitted Cluster Point Process Model | |
| is.multitype | Test whether Object is Multitype | |
| plot.kppm | Plot a fitted cluster point process | |
| is.im | Test Whether An Object Is A Pixel Image | |
| lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| plot.fasp | Plot a Function Array | |
| colourmap | Colour Lookup Tables | |
| plot.fv | Plot Function Values | |
| complement.owin | Take Complement of a Window | |
| rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
| rGaussPoisson | Simulate Gauss-Poisson Process | |
| plot.ppp | plot a Spatial Point Pattern | |
| rescale.ppp | Convert Point Pattern to Another Unit of Length | |
| psp.object | Class of Line Segment Patterns | |
| is.marked | Test Whether Marks Are Present | |
| envelope | Simulation envelopes of summary function | |
| miplot | Morishita Index Plot | |
| quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
| rlabel | Random Re-Labelling of Point Pattern | |
| kstest.ppm | Kolmogorov-Smirnov Test for Point Process Model | |
| japanesepines | Japanese Pines Point Pattern | |
| rmpoispp | Generate Multitype Poisson Point Pattern | |
| closing | Morphological Closing | |
| runifpoint | Generate N Uniform Random Points | |
| rthin | Random Thinning | |
| swedishpines | Swedish Pines Point Pattern | |
| plot.bermantest | Plot Result of Berman Test | |
| ppm.object | Class of Fitted Point Process Models | |
| compatible.im | Test Whether Two Pixel Images Are Compatible | |
| inside.owin | Test Whether Points Are Inside A Window | |
| cut.im | Convert Pixel Image from Numeric to Factor | |
| pcf | Pair Correlation Function | |
| print.owin | Print Brief Details of a Spatial Window | |
| redwood | California Redwoods Point Pattern (Ripley's Subset) | |
| is.ppp | Test Whether An Object Is A Point Pattern | |
| quantile.im | Sample Quantiles of Pixel Image | |
| progressreport | Print Progress Reports | |
| pppmatching | Create a Point Matching | |
| rescale | Convert dataset to another unit of length | |
| demopat | Artificial Data Point Pattern | |
| levelset | Level Set of a Pixel Image | |
| simulate.kppm | Simulate a Fitted Cluster Point Process Model | |
| lengths.psp | Lengths of Line Segments | |
| model.matrix.ppm | Extract Design Matrix from Point Process Model | |
| pixellate | Convert Spatial Object to Pixel Image | |
| intersect.tess | Intersection of Two Tessellations | |
| inforder.family | Infinite Order Interaction Family | |
| mincontrast | Method of Minimum Contrast | |
| iplot | Point and Click Interface for Displaying a Point Pattern | |
| pixellate.ppp | Convert Point Pattern to Pixel Image | |
| rjitter | Random Perturbation of a Point Pattern | |
| infline | Infinite Straight Lines | |
| plot.tess | Plot a tessellation | |
| rotate.owin | Rotate a Window | |
| pairdist.psp | Pairwise distances between line segments | |
| rmh.ppm | Simulate from a Fitted Point Process Model | |
| simplify.owin | Approximate a Polygon by a Simpler Polygon | |
| plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
| rshift.ppp | Randomly Shift a Point Pattern | |
| nncorr | Nearest-Neighbour Correlation Indices of Marked Point Pattern | |
| nbfires | Point Patterns of New Brunswick Forest Fires | |
| rshift.splitppp | Randomly Shift a List of Point Patterns | |
| persp.im | Perspective Plot of Pixel Image | |
| rlinegrid | Generate grid of parallel lines with random displacement | |
| dilation | Morphological Dilation | |
| markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
| ripras | Estimate window from points alone | |
| profilepl | Profile Maximum Pseudolikelihood | |
| split.im | Divide Image Into Sub-images | |
| pppmatching.object | Class of Point Matchings | |
| rotate.psp | Rotate a Line Segment Pattern | |
| quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
| rMaternI | Simulate Matern Model I | |
| discpartarea | Area of Part of Disc | |
| scanpp | Read Point Pattern From Data File | |
| rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |
| pixelquad | Quadrature Scheme Based on Pixel Grid | |
| rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |
| ppm | Fit Point Process Model to Data | |
| print.im | Print Brief Details of an Image | |
| nztrees | New Zealand Trees Point Pattern | |
| plot.listof | Plot a List of Things | |
| setcov | Set Covariance of a Window | |
| spatstat-internal | Internal spatstat functions | |
| lurking | Lurking variable plot | |
| shift | Apply Vector Translation | |
| interp.im | Interpolate a Pixel Image | |
| ord.family | Ord Interaction Process Family | |
| plot.ppm | plot a Fitted Point Process Model | |
| summary.splitppp | Summary of a Split Point Pattern | |
| rshift | Random Shift | |
| spruces | Spruces Point Pattern | |
| psp | Create a Line Segment Pattern | |
| rNeymanScott | Simulate Neyman-Scott Process | |
| rpoint | Generate N Random Points | |
| rstrat | Simulate Stratified Random Point Pattern | |
| rMatClust | Simulate Matern Cluster Process | |
| split.ppp | Divide Point Pattern into Sub-patterns | |
| rpoispp | Generate Poisson Point Pattern | |
| discretise | Safely Convert Point Pattern Window to Binary Mask | |
| rshift.psp | Randomly Shift a Line Segment Pattern | |
| rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |
| perimeter | Perimeter Length of Window | |
| qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
| is.marked.ppm | Test Whether A Point Process Model is Marked | |
| summary.quad | Summarizing a Quadrature Scheme | |
| unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
| incircle | Find Largest Circle Inside Window | |
| with.fv | Evaluate an Expression in a Function Table | |
| pppdist | Distance Between Two Point Patterns | |
| pairdist | Pairwise distances | |
| ponderosa | Ponderosa Pine Tree Point Pattern | |
| union.quad | Union of Data and Dummy Points | |
| quadrat.test.splitppp | Chi-Squared Test of CSR for Split Point Pattern | |
| tiles | Extract List of Tiles in a Tessellation | |
| update.kppm | Update a Fitted Cluster Point Process Model | |
| spokes | Spokes pattern of dummy points | |
| summary.owin | Summary of a Spatial Window | |
| superimpose | Superimpose Several Point Patterns | |
| shapley | Galaxies in the Shapley Supercluster | |
| plot.owin | Plot a Spatial Window | |
| model.images | Compute Images of Constructed Covariates | |
| summary.psp | Summary of a Line Segment Pattern Dataset | |
| raster.x | Cartesian Coordinates for a Pixel Raster | |
| unmark | Remove Marks | |
| midpoints.psp | Midpoints of Line Segment Pattern | |
| reduced.sample | Reduced Sample Estimator using Histogram Data | |
| rmpoint | Generate N Random Multitype Points | |
| runifdisc | Generate N Uniform Random Points in a Disc | |
| rStrauss | Perfect Simulation of the Strauss Process | |
| localK | Neighbourhood density function | |
| murchison | Murchison gold deposits | |
| vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
| simdat | Simulated Point Pattern | |
| shift.ppp | Apply Vector Translation To Point Pattern | |
| nnwhich | Nearest neighbour | |
| urkiola | Urkiola Woods Point Pattern | |
| runifpointOnLines | Generate N Uniform Random Points On Line Segments | |
| setmarks | Set or Reset the Marks in a Point Pattern | |
| affine.psp | Apply Affine Transformation To Line Segment Pattern | |
| rThomas | Simulate Thomas Process | |
| blur | Apply Gaussian Blur to a Pixel Image | |
| rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |
| rescue.rectangle | Convert Window Back To Rectangle | |
| shift.im | Apply Vector Translation To Pixel Image | |
| rpoisline | Generate Poisson Random Line Process | |
| Lcross | Multitype L-function (cross-type) | |
| pairsat.family | Saturated Pairwise Interaction Point Process Family | |
| spatstat.options | Internal Options in Spatstat Package | |
| square | Square Window | |
| update.ppm | Update a Fitted Point Process Model | |
| print.ppm | Print a Fitted Point Process Model | |
| Extract.splitppp | Extract or Replace Sub-Patterns | |
| Kcross.inhom | Inhomogeneous Cross K Function | |
| Strauss | The Strauss Point Process Model | |
| unitname | Name for Unit of Length | |
| simulate.ppm | Simulate a Fitted Gibbs Point Process Model | |
| print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
| applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
| spatstat-package | The Spatstat Package | |
| summary.im | Summarizing a Pixel Image | |
| bei | Tropical rain forest trees | |
| affine.ppp | Apply Affine Transformation To Point Pattern | |
| rpoislinetess | Poisson Line Tessellation | |
| selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
| finpines | Pine saplings in Finland. | |
| crossdist.default | Pairwise distances between two different sets of points | |
| as.im | Convert to Pixel Image | |
| smooth.ppp | Spatial smoothing of observations at irregular points | |
| Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
| plot.colourmap | Plot a Colour Map | |
| Pairwise | Generic Pairwise Interaction model | |
| area.owin | Area of a Window | |
| letterR | Window in Shape of Letter R | |
| MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
| quadrat.test | Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
| Replace.im | Reset Values in Subset of Image | |
| Linhom | L-function | |
| rotate | Rotate | |
| Saturated | Saturated Pairwise Interaction model | |
| as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |
| StraussHard | The Strauss / Hard Core Point Process Model | |
| pairdist.ppp | Pairwise distances | |
| eval.fv | Evaluate Expression Involving Functions | |
| multiplicity.ppp | Count Multiplicity of Duplicate Points | |
| Kdot | Multitype K Function (i-to-any) | |
| rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
| stieltjes | Compute Integral of Function Against Cumulative Distribution | |
| gridweights | Compute Quadrature Weights Based on Grid Counts | |
| alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern | |
| Emark | Diagnostics for random marking | |
| Kmeasure | Reduced Second Moment Measure | |
| LennardJones | The Lennard-Jones Potential | |
| MultiStrauss | The Multitype Strauss Point Process Model | |
| quadrats | Divide Region into Quadrats | |
| mean.im | Mean, Median and Range of Pixel Values in an Image | |
| connected | Connected components of an image or window | |
| affine.owin | Apply Affine Transformation To Window | |
| fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |
| eval.fasp | Evaluate Expression Involving Function Arrays | |
| ants | Harkness-Isham ants' nests data | |
| ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
| as.data.frame.psp | Coerce Line Segment Pattern to a Data Frame | |
| residuals.ppm | Residuals for Fitted Point Process Model | |
| humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
| is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
| as.matrix.im | Convert Pixel Image to Matrix | |
| Kest | K-function | |
| as.owin | Convert Data To Class owin | |
| as.psp | Convert Data To Class psp | |
| rcell | Simulate Baddeley-Silverman Cell Process | |
| Iest | Estimate the I-function | |
| AreaInter | The Area Interaction Point Process Model | |
| hyperframe | Hyper Data Frame | |
| SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model | |
| dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
| Extract.psp | Extract Subset of Line Segment Pattern | |
| chop.tess | Subdivide a Window or Tessellation using a Set of Lines | |
| angles.psp | Orientation Angles of Line Segments | |
| allstats | Calculate four standard summary functions of a point pattern. | |
| Jmulti | Marked J Function | |
| areaLoss | Difference of Disc Areas | |
| chorley | Chorley-Ribble Cancer Data | |
| Kinhom | Inhomogeneous K-function | |
| Kmulti | Marked K-Function | |
| distmap.ppp | Distance Map of Point Pattern | |
| adaptive.density | Intensity Estimate of Point Pattern Using Tessellation | |
| Gmulti | Marked Nearest Neighbour Distance Function | |
| bermantest | Berman's Tests for Point Process Model | |
| bounding.box | Bounding Box of a Window or Point Pattern | |
| Extract.im | Extract Subset of Image | |
| bdist.points | Distance to Boundary of Window | |
| Gest | Nearest Neighbour Distance Function G | |
| DiggleGratton | Diggle-Gratton model | |
| bramblecanes | Hutchings' Bramble Canes data | |
| Extract.listof | Extract or Replace Subset of a List of Things | |
| corners | Corners of a rectangle | |
| Jdot | Multitype J Function (i-to-any) | |
| fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
| eval.hyper | Evaluate an Expression in Each Row of a Hyperframe | |
| Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
| Ldot.inhom | Inhomogeneous Multitype L Dot Function | |
| bdist.pixels | Distance to Boundary of Window | |
| contour.im | Contour plot of pixel image | |
| gridcentres | Rectangular grid of points | |
| by.ppp | Apply a Function to a Point Pattern Broken Down by Factor | |
| Extract.fasp | Extract Subset of Function Array | |
| summary.ppp | Summary of a Point Pattern Dataset | |
| identify.ppp | Identify Points in a Point Pattern | |
| default.dummy | Generate a Default Pattern of Dummy Points | |
| append.psp | Combine Two Line Segment Patterns | |
| Extract.ppp | Extract or Replace Subset of Point Pattern | |
| fv.object | Data Frames of Function Values | |
| Jest | Estimate the J-function | |
| Softcore | The Soft Core Point Process Model | |
| eem | Exponential Energy Marks | |
| cells | Biological Cells Point Pattern | |
| crossdist.psp | Pairwise distances between two different line segment patterns | |
| distmap.psp | Distance Map of Line Segment Pattern | |
| quad.object | Class of Quadrature Schemes | |
| duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
| gpc2owin | Convert Polygonal Region into Different Format | |
| fryplot | Fry Plot of Point Pattern | |
| Extract.quad | Subset of Quadrature Scheme | |
| erosion | Morphological Erosion | |
| data.ppm | Extract Original Data from a Fitted Point Process Model | |
| Hest | Spherical Contact Distribution Function | |
| endpoints.psp | Endpoints of Line Segment Pattern | |
| spatstat-deprecated | Deprecated spatstat functions | |
| as.polygonal | Convert a Window to a Polygonal Window | |
| betacells | Beta Ganglion Cells in Cat Retina | |
| Kest.fft | K-function using FFT | |
| Kcross | Multitype K Function (Cross-type) | |
| heather | Diggle's Heather Data | |
| diameter | Diameter of a Window | |
| fasp.object | Function Arrays for Spatial Patterns | |
| dirichlet | Dirichlet Tessellation of Point Pattern | |
| clarkevans | Clark and Evans Aggregation Index | |
| Ord | Generic Ord Interaction model | |
| Lest | L-function | |
| anova.ppm | ANOVA for Fitted Point Process Models | |
| amacrine | Hughes' Amacrine Cell Data | |
| by.im | Apply Function to Image Broken Down by Factor | |
| eroded.areas | Areas of Morphological Erosions | |
| hist.im | Histogram of Pixel Values in an Image | |
| Extract.fv | Extract Subset of Function Values | |
| areaGain | Difference of Disc Areas | |
| eval.im | Evaluate Expression Involving Pixel Images | |
| PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
| OrdThresh | Ord's Interaction model | |
| Poisson | Poisson Point Process Model | |
| Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
| anemones | Beadlet Anemones Data | |
| Fest | Estimate the empty space function F | |
| density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
| Jcross | Multitype J Function (i-to-j) | |
| as.ppp | Convert Data To Class ppp | |
| rsyst | Simulate systematic random point pattern | |
| affine | Apply Affine Transformation | |
| Ldot | Multitype L-function (i-to-any) | |
| coef.ppm | Coefficients of Fitted Point Process Model | |
| harmonic | Basis for Harmonic Functions | |
| expand.owin | Expand Window By Factor | |
| ewcdf | Weighted Empirical Cumulative Distribution Function | |
| Extract.tess | Extract or Replace Subset of Tessellation | |
| BadGey | Hybrid Geyer Point Process Model | |
| hamster | Aherne's hamster tumour data | |
| clickppp | Interactively Add Points | |
| pairwise.family | Pairwise Interaction Process Family | |
| plot.hyperframe | Plot Entries in a Hyperframe | |
| print.ppp | Print Brief Details of a Point Pattern Dataset | |
| pointsOnLines | Place Points Evenly Along Specified Lines | |
| predict.ppm | Prediction from a Fitted Point Process Model | |
| longleaf | Longleaf Pines Point Pattern | |
| quadratcount | Quadrat counting for a point pattern | |
| trim.rectangle | Cut margins from rectangle | |
| thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
| markvario | Mark Variogram | |
| Geyer | Geyer's Saturation Point Process Model | |
| bounding.box.xy | Convex Hull of Points | |
| as.tess | Convert Data To Tessellation | |
| effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model | |
| Lcross.inhom | Inhomogeneous Cross Type L Function | |
| centroid.owin | Centroid of a window | |
| as.rectangle | Window Frame | |
| clickpoly | Interactively Define a Polygon | |
| distmap.owin | Distance Map of Window | |
| as.mask | Pixel Image Approximation of a Window | |
| summary.ppm | Summarizing a Fitted Point Process Model | |
| No Results! | ||
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Details
| Date | 22 August 2009 |
| License | GPL (>= 2) |
| URL | http://www.spatstat.org |
| Packaged | 2009-08-23 22:41:44 UTC; adrian |
| Repository | CRAN |
| Date/Publication | 2009-08-23 15:40:20 |
| depends | base (>= 2.7.0) , deldir (>= 0.0-7) , gpclib , graphics , mgcv , R (>= 2.7.0) , stats , utils |
| suggests | maptools , rpanel , sm , tkrplot |
| Contributors | Rolf Turner, Adrian Baddeley |
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