spatstat v1.21-1
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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 | |
| Iest | Estimate the I-function | |
| Emark | Diagnostics for random marking | |
| Hest | Spherical Contact Distribution Function | |
| Extract.ppp | Extract or Replace Subset of Point Pattern | |
| connected | Connected components of an image or window | |
| as.rectangle | Window Frame | |
| AreaInter | The Area Interaction Point Process Model | |
| Extract.fv | Extract Subset of Function Values | |
| by.im | Apply Function to Image Broken Down by Factor | |
| Poisson | Poisson Point Process Model | |
| anova.ppm | ANOVA for Fitted Point Process Models | |
| Extract.fasp | Extract Subset of Function Array | |
| bdist.points | Distance to Boundary of Window | |
| Jcross | Multitype J Function (i-to-j) | |
| Kcross.inhom | Inhomogeneous Cross K Function | |
| Fest | Estimate the empty space function F | |
| chop.tess | Subdivide a Window or Tessellation using a Set of Lines | |
| K3est | K-function of a Three-Dimensional Point Pattern | |
| Jdot | Multitype J Function (i-to-any) | |
| bdist.tiles | Distance to Boundary of Window | |
| Softcore | The Soft Core Point Process Model | |
| Linhom | L-function | |
| centroid.owin | Centroid of a window | |
| Geyer | Geyer's Saturation Point Process Model | |
| areaGain | Difference of Disc Areas | |
| crossdist.ppp | Pairwise distances between two different point patterns | |
| as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |
| bounding.box.xy | Convex Hull of Points | |
| Saturated | Saturated Pairwise Interaction model | |
| Extract.quad | Subset of Quadrature Scheme | |
| Strauss | The Strauss Point Process Model | |
| Extract.psp | Extract Subset of Line Segment Pattern | |
| Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
| allstats | Calculate four standard summary functions of a point pattern. | |
| LennardJones | The Lennard-Jones Potential | |
| Lcross.inhom | Inhomogeneous Cross Type L Function | |
| default.dummy | Generate a Default Pattern of Dummy Points | |
| DiggleGratton | Diggle-Gratton model | |
| as.im | Convert to Pixel Image | |
| copper | Berman-Huntington points and lines data | |
| as.owin | Convert Data To Class owin | |
| blur | Apply Gaussian Blur to a Pixel Image | |
| data.ppm | Extract Original Data from a Fitted Point Process Model | |
| envelope.pp3 | Simulation Envelopes of Summary Function for 3D Point Pattern | |
| border | Border Region of a Window | |
| Ldot.inhom | Inhomogeneous Multitype L Dot Function | |
| cbind.hyperframe | Combine Hyperframes by Rows or by Columns | |
| MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
| coords | Extract Coordinates of a Spatial or Spatiotemporal Point Pattern | |
| adaptive.density | Intensity Estimate of Point Pattern Using Tessellation | |
| clarkevans | Clark and Evans Aggregation Index | |
| Kmulti | Marked K-Function | |
| append.psp | Combine Two Line Segment Patterns | |
| Kcross | Multitype K Function (Cross-type) | |
| Replace.im | Reset Values in Subset of Image | |
| Jmulti | Marked J Function | |
| as.data.frame.hyperframe | Coerce Hyperframe to Data Frame | |
| concatxy | Concatenate x,y Coordinate Vectors | |
| collapse.fv | Collapse Several Function Tables into One | |
| anemones | Beadlet Anemones Data | |
| coef.slrm | Coefficients of Fitted Spatial Logistic Regression Model | |
| colourtools | Convert and Compare Colours in Different Formats | |
| Kest.fft | K-function using FFT | |
| Extract.tess | Extract or Replace Subset of Tessellation | |
| crossing.psp | Crossing Points of Two Line Segment Patterns | |
| G3est | Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern | |
| PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
| Ord | Generic Ord Interaction model | |
| bramblecanes | Hutchings' Bramble Canes data | |
| box3 | Three-Dimensional Box | |
| clickpoly | Interactively Define a Polygon | |
| Extract.listof | Extract or Replace Subset of a List of Things | |
| compatible.fasp | Test Whether Two Function Arrays Are Compatible | |
| convexhull | Convex Hull | |
| fasp.object | Function Arrays for Spatial Patterns | |
| dirichlet | Dirichlet Tessellation of Point Pattern | |
| Kdot | Multitype K Function (i-to-any) | |
| inside.owin | Test Whether Points Are Inside A Window | |
| cut.ppp | Classify Points in a Point Pattern | |
| as.polygonal | Convert a Window to a Polygonal Window | |
| cut.im | Convert Pixel Image from Numeric to Factor | |
| amacrine | Hughes' Amacrine Cell Data | |
| area.owin | Area of a Window | |
| Extract.im | Extract Subset of Image | |
| dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
| cells | Biological Cells Point Pattern | |
| anova.slrm | Analysis of Deviance for Spatial Logistic Regression Models | |
| distmap | Distance Map | |
| eem | Exponential Energy Marks | |
| bermantest | Berman's Tests for Point Process Model | |
| hyperframe | Hyper Data Frame | |
| Hardcore | The Hard Core Point Process Model | |
| discpartarea | Area of Part of Disc | |
| diameter | Diameter of an Object | |
| bounding.box | Bounding Box of a Window or Point Pattern | |
| Gest | Nearest Neighbour Distance Function G | |
| spatstat-internal | Internal spatstat functions | |
| dilated.areas | Areas of Morphological Dilations | |
| distmap.psp | Distance Map of Line Segment Pattern | |
| distmap.ppp | Distance Map of Point Pattern | |
| distmap.owin | Distance Map of Window | |
| bronzefilter | Bronze gradient filter data | |
| humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
| diameter.owin | Diameter of a Window | |
| clickppp | Interactively Add Points | |
| compatible.fv | Test Whether Two Function Objects Are Compatible | |
| BadGey | Hybrid Geyer Point Process Model | |
| lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| F3est | Empty Space Function of a Three-Dimensional Point Pattern | |
| bdist.pixels | Distance to Boundary of Window | |
| complement.owin | Take Complement of a Window | |
| dilation | Morphological Dilation | |
| dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
| ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
| integral.im | Integral of a Pixel Image | |
| plot.psp | plot a Spatial Line Segment Pattern | |
| as.mask | Pixel Image Approximation of a Window | |
| density.psp | Kernel Smoothing of Line Segment Pattern | |
| demopat | Artificial Data Point Pattern | |
| by.ppp | Apply a Function to a Point Pattern Broken Down by Factor | |
| fv | Create a Function Value Table | |
| OrdThresh | Ord's Interaction model | |
| marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern | |
| istat | Point and Click Interface for Exploratory Analysis of Point Pattern | |
| compatible.im | Test Whether Two Pixel Images Are Compatible | |
| default.rmhcontrol | Set Default Control Parameters for Metropolis-Hastings Algorithm. | |
| finpines | Pine saplings in Finland. | |
| markvario | Mark Variogram | |
| density.ppp | Kernel Smoothed Intensity of Point Pattern | |
| as.hyperframe | Convert Data to Hyperframe | |
| interp.im | Interpolate a Pixel Image | |
| erosion | Morphological Erosion | |
| convexhull.xy | Convex Hull of Points | |
| japanesepines | Japanese Pines Point Pattern | |
| distfun | Distance Map as a Function | |
| kstest.ppm | Kolmogorov-Smirnov Test for Point Process Model | |
| affine.psp | Apply Affine Transformation To Line Segment Pattern | |
| MultiStrauss | The Multitype Strauss Point Process Model | |
| Kscaled | Locally Scaled K-function | |
| ants | Harkness-Isham ants' nests data | |
| Gfox | Foxall's Distance Functions | |
| alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern | |
| Jest | Estimate the J-function | |
| gridcentres | Rectangular grid of points | |
| eval.fasp | Evaluate Expression Involving Function Arrays | |
| lgcp.estpcf | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| bind.fv | Combine Function Value Tables | |
| effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model | |
| is.marked.ppm | Test Whether A Point Process Model is Marked | |
| nearestsegment | Find Line Segment Nearest to Each Point | |
| km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
| markcorrint | Mark Correlation Integral | |
| plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
| fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
| Kinhom | Inhomogeneous K-function | |
| pixellate.owin | Convert Window to Pixel Image | |
| pp3 | Three Dimensional Point Pattern | |
| eroded.areas | Areas of Morphological Erosions | |
| identify.ppp | Identify Points in a Point Pattern | |
| as.hyperframe.ppx | Extract coordinates and marks of multidimensional point pattern | |
| Ldot | Multitype L-function (i-to-any) | |
| Kest | K-function | |
| plot.colourmap | Plot a Colour Map | |
| markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
| spatstat-deprecated | Deprecated spatstat functions | |
| owin | Create a Window | |
| pcfcross | Multitype pair correlation function (cross-type) | |
| localpcf | Local pair correlation function | |
| diameter.boxx | Geometrical Calculations for Multi-Dimensional Box | |
| predict.kppm | Prediction from a Fitted Cluster Point Process Model | |
| pairdist.psp | Pairwise distances between line segments | |
| latest.news | Print News About Latest Version of Package | |
| plot.splitppp | Plot a List of Point Patterns | |
| Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
| nndist.pp3 | Nearest neighbour distances in three dimensions | |
| as.tess | Convert Data To Tessellation | |
| raster.x | Cartesian Coordinates for a Pixel Raster | |
| inforder.family | Infinite Order Interaction Family | |
| methods.pp3 | Methods for three-dimensional point patterns | |
| DiggleGatesStibbard | Diggle-Gates-Stibbard Point Process Model | |
| pairwise.family | Pairwise Interaction Process Family | |
| areaLoss | Difference of Disc Areas | |
| is.empty | Test Whether An Object Is Empty | |
| marks | Marks of a Point Pattern | |
| contour.im | Contour plot of pixel image | |
| is.marked.ppp | Test Whether A Point Pattern is Marked | |
| clip.infline | Intersect Infinite Straight Lines with a Window | |
| rMosaicSet | Mosaic Random Set | |
| applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
| pixellate | Convert Spatial Object to Pixel Image | |
| markcorr | Mark Correlation Function | |
| SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model | |
| letterR | Window in Shape of Letter R | |
| levelset | Level Set of a Pixel Image | |
| quadrat.test.splitppp | Chi-Squared Test of CSR for Split Point Pattern | |
| as.mask.psp | Convert Line Segment Pattern to Binary Pixel Mask | |
| hamster | Aherne's hamster tumour data | |
| is.convex | Test Whether a Window is Convex | |
| multiplicity.ppp | Count Multiplicity of Duplicate Points | |
| nztrees | New Zealand Trees Point Pattern | |
| nnwhich.ppx | Nearest Neighbours in Any Dimensions | |
| longleaf | Longleaf Pines Point Pattern | |
| diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
| matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
| runifpointx | Generate N Uniform Random Points in Any Dimensions | |
| opening | Morphological Opening | |
| lurking | Lurking variable plot | |
| plot.kstest | Plot a Spatial Kolmogorov-Smirnov Test | |
| duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
| is.subset.owin | Determine Whether One Window is Contained In Another | |
| crossdist.pp3 | Pairwise distances between two different three-dimensional point patterns | |
| default.expand | Compute Expansion Window for Simulation | |
| affine.ppp | Apply Affine Transformation To Point Pattern | |
| methods.box3 | Methods for Three-Dimensional Box | |
| owin.object | Class owin | |
| is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
| lut | Lookup Tables | |
| fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |
| localK | Neighbourhood density function | |
| pairdist.ppx | Pairwise Distances in Any Dimensions | |
| is.owin | Test Whether An Object Is A Window | |
| nnclean | Nearest Neighbour Clutter Removal | |
| psp | Create a Line Segment Pattern | |
| pairdist | Pairwise distances | |
| pixellate.ppp | Convert Point Pattern to Pixel Image | |
| pppmatching.object | Class of Point Matchings | |
| model.frame.ppm | Extract the Environment of a Point Process Model | |
| periodify | Make Periodic Copies of a Spatial Pattern | |
| is.marked | Test Whether Marks Are Present | |
| disc | Circular Window | |
| Lest | L-function | |
| rMaternI | Simulate Matern Model I | |
| spatstat.options | Internal Options in Spatstat Package | |
| pcf.fv | Pair Correlation Function obtained from K Function | |
| is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
| plot.tess | Plot a tessellation | |
| pcfdot | Multitype pair correlation function (i-to-any) | |
| pairdist.ppp | Pairwise distances | |
| rThomas | Simulate Thomas Process | |
| plot.ppp | plot a Spatial Point Pattern | |
| print.im | Print Brief Details of an Image | |
| is.multitype | Test whether Object is Multitype | |
| delaunay | Delaunay Triangulation of Point Pattern | |
| Pairwise | Generic Pairwise Interaction model | |
| thomas.estpcf | Fit the Thomas Point Process by Minimum Contrast | |
| is.ppp | Test Whether An Object Is A Point Pattern | |
| pairdist.pp3 | Pairwise distances in Three Dimensions | |
| rGaussPoisson | Simulate Gauss-Poisson Process | |
| spokes | Spokes pattern of dummy points | |
| rshift.splitppp | Randomly Shift a List of Point Patterns | |
| rsyst | Simulate systematic random point pattern | |
| diameter.box3 | Geometrical Calculations for Three-Dimensional Box | |
| rlinegrid | Generate grid of parallel lines with random displacement | |
| with.fv | Evaluate an Expression in a Function Table | |
| rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |
| plot.im | Plot a Pixel Image | |
| nndist.ppx | Nearest Neighbour Distances in Any Dimensions | |
| intersect.tess | Intersection of Two Tessellations | |
| smooth.ppp | Spatial smoothing of observations at irregular points | |
| npoints | Number of Points in a Point Pattern | |
| StraussHard | The Strauss / Hard Core Point Process Model | |
| rpoislinetess | Poisson Line Tessellation | |
| psp.object | Class of Line Segment Patterns | |
| pcf.fasp | Pair Correlation Function obtained from array of K functions | |
| methods.ppx | Methods for Multidimensional Space-Time Point Patterns | |
| nncorr | Nearest-Neighbour Correlation Indices of Marked Point Pattern | |
| rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
| ppm.object | Class of Fitted Point Process Models | |
| summary.splitppp | Summary of a Split Point Pattern | |
| kppm | Fit cluster point process model | |
| rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |
| bw.stoyan | Stoyan's Rule of Thumb for Bandwidth Selection | |
| pcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-Type) | |
| spatstat-package | The Spatstat Package | |
| lansing | Lansing Woods Point Pattern | |
| print.ppm | Print a Fitted Point Process Model | |
| qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
| nnwhich.pp3 | Nearest neighbours in three dimensions | |
| osteo | Osteocyte Lacunae Data: Replicated Three-Dimensional Point Patterns | |
| pixellate.psp | Convert Line Segment Pattern to Pixel Image | |
| ppp.object | Class of Point Patterns | |
| shapley | Galaxies in the Shapley Supercluster | |
| print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
| crossdist | Pairwise distances | |
| pairdist.default | Pairwise distances | |
| markconnect | Mark Connection Function | |
| quadratresample | Resample a Point Pattern by Resampling Quadrats | |
| iplot | Point and Click Interface for Displaying a Point Pattern | |
| summary.quad | Summarizing a Quadrature Scheme | |
| plot.kppm | Plot a fitted cluster point process | |
| matchingdist | Distance for a Point Pattern Matching | |
| quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
| rknn | Theoretical Distribution of Nearest Neighbour Distance | |
| stieltjes | Compute Integral of Function Against Cumulative Distribution | |
| mean.im | Maximum, Minimum, Mean, Median, Range or Sum of Pixel Values in an Image | |
| pcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Type-i-To-Any-Type) | |
| fv.object | Data Frames of Function Values | |
| rcell | Simulate Baddeley-Silverman Cell Process | |
| incircle | Find Largest Circle Inside Window | |
| tess | Create a Tessellation | |
| union.quad | Union of Data and Dummy Points | |
| crossdist.default | Pairwise distances between two different sets of points | |
| project2segment | Move Point To Nearest Line | |
| affine.owin | Apply Affine Transformation To Window | |
| rjitter | Random Perturbation of a Point Pattern | |
| as.psp | Convert Data To Class psp | |
| scanpp | Read Point Pattern From Data File | |
| redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
| nearest.raster.point | Find Pixel Nearest to a Given Point | |
| tiles | Extract List of Tiles in a Tessellation | |
| nndist | Nearest neighbour distances | |
| split.im | Divide Image Into Sub-images | |
| suffstat | Sufficient Statistic of Point Process Model | |
| midpoints.psp | Midpoints of Line Segment Pattern | |
| plot.ppm | plot a Fitted Point Process Model | |
| chorley | Chorley-Ribble Cancer Data | |
| quadrat.test | Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
| rotate.psp | Rotate a Line Segment Pattern | |
| rescale.owin | Convert Window to Another Unit of Length | |
| rshift.ppp | Randomly Shift a Point Pattern | |
| runifpoint | Generate N Uniform Random Points | |
| unmark | Remove Marks | |
| murchison | Murchison gold deposits | |
| gpc2owin | Convert Polygonal Region into Different Format | |
| predict.ppm | Prediction from a Fitted Point Process Model | |
| rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |
| rStrauss | Perfect Simulation of the Strauss Process | |
| persp.im | Perspective Plot of Pixel Image | |
| vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
| relrisk | Nonparametric Estimate of Spatially-Varying Relative Risk | |
| is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
| crossdist.psp | Pairwise distances between two different line segment patterns | |
| update.kppm | Update a Fitted Cluster Point Process Model | |
| im | Create a Pixel Image Object | |
| plot.listof | Plot a List of Things | |
| as.matrix.im | Convert Pixel Image to Matrix or Array | |
| pcf.ppp | Pair Correlation Function of Point Pattern | |
| with.hyperframe | Evaluate an Expression in Each Row of a Hyperframe | |
| unitname | Name for Unit of Length | |
| plot.bermantest | Plot Result of Berman Test | |
| reach | Interaction Distance of a Point Process | |
| plot.fv | Plot Function Values | |
| colourmap | Colour Lookup Tables | |
| nndist.psp | Nearest neighbour distances between line segments | |
| kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
| rshift.psp | Randomly Shift a Line Segment Pattern | |
| shift | Apply Vector Translation | |
| nnwhich | Nearest neighbour | |
| solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
| Fiksel | The Fiksel Interaction | |
| rotate | Rotate | |
| smooth.fv | Apply Smoothing to Function Values | |
| ppm | Fit Point Process Model to Data | |
| rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
| print.quad | Print a Quadrature Scheme | |
| deltametric | Delta Metric | |
| hist.im | Histogram of Pixel Values in an Image | |
| summary.ppp | Summary of a Point Pattern Dataset | |
| rNeymanScott | Simulate Neyman-Scott Process | |
| pppdist | Distance Between Two Point Patterns | |
| rmpoispp | Generate Multitype Poisson Point Pattern | |
| which.max.im | Identify Pixelwise Maximum of Several Pixel Images | |
| predict.slrm | Predicted or Fitted Values from Spatial Logistic Regression | |
| rpoispp | Generate Poisson Point Pattern | |
| plot.pp3 | Plot a three-dimensional point pattern | |
| rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |
| fitted.slrm | Fitted Probabilities for Spatial Logistic Regression | |
| im.object | Class of Images | |
| as.ppp | Convert Data To Class ppp | |
| quantile.im | Sample Quantiles of Pixel Image | |
| slrm | Spatial Logistic Regression | |
| Lcross | Multitype L-function (cross-type) | |
| residuals.ppm | Residuals for Fitted Point Process Model | |
| ord.family | Ord Interaction Process Family | |
| selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
| rescale | Convert dataset to another unit of length | |
| runifpointOnLines | Generate N Uniform Random Points On Line Segments | |
| methods.distfun | Methods for Distance Functions | |
| shift.psp | Apply Vector Translation To Line Segment Pattern | |
| corners | Corners of a rectangle | |
| ponderosa | Ponderosa Pine Tree Point Pattern | |
| rotate.ppp | Rotate a Point Pattern | |
| rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
| plot.fasp | Plot a Function Array | |
| coef.ppm | Coefficients of Fitted Point Process Model | |
| rthin | Random Thinning | |
| superimposePSP | Superimpose Several Line Segment Patterns | |
| summary.psp | Summary of a Line Segment Pattern Dataset | |
| nbfires | Point Patterns of New Brunswick Forest Fires | |
| summary.ppm | Summarizing a Fitted Point Process Model | |
| print.owin | Print Brief Details of a Spatial Window | |
| is.im | Test Whether An Object Is A Pixel Image | |
| update.ppm | Update a Fitted Point Process Model | |
| quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
| summary.im | Summarizing a Pixel Image | |
| simdat | Simulated Point Pattern | |
| rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |
| Gmulti | Marked Nearest Neighbour Distance Function | |
| volume | Volume of an Object | |
| Extract.splitppp | Extract or Replace Sub-Patterns | |
| runifdisc | Generate N Uniform Random Points in a Disc | |
| plot.envelope | Plot a Simulation Envelope | |
| pcf3est | Pair Correlation Function of a Three-Dimensional Point Pattern | |
| plot.owin | Plot a Spatial Window | |
| rMatClust | Simulate Matern Cluster Process | |
| rSSI | Simulate Simple Sequential Inhibition | |
| miplot | Morishita Index Plot | |
| rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
| unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
| rlabel | Random Re-Labelling of Point Pattern | |
| rshift | Random Shift | |
| thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
| Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
| pcfinhom | Inhomogeneous Pair Correlation Function | |
| print.ppp | Print Brief Details of a Point Pattern Dataset | |
| infline | Infinite Straight Lines | |
| eval.im | Evaluate Expression Involving Pixel Images | |
| spruces | Spruces Point Pattern | |
| shift.im | Apply Vector Translation To Pixel Image | |
| betacells | Beta Ganglion Cells in Cat Retina | |
| affine | Apply Affine Transformation | |
| residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
| plot.hyperframe | Plot Entries in a Hyperframe | |
| density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
| urkiola | Urkiola Woods Point Pattern | |
| reduced.sample | Reduced Sample Estimator using Histogram Data | |
| crossdist.ppx | Pairwise Distances Between Two Different Multi-Dimensional Point Patterns | |
| boxx | Multi-Dimensional Box | |
| rmh.ppm | Simulate from a Fitted Point Process Model | |
| lengths.psp | Lengths of Line Segments | |
| perimeter | Perimeter Length of Window | |
| logLik.slrm | Loglikelihood of Spatial Logistic Regression | |
| progressreport | Print Progress Reports | |
| pcf | Pair Correlation Function | |
| matclust.estpcf | Fit the Matern Cluster Point Process by Minimum Contrast Using Pair Correlation | |
| pixelquad | Quadrature Scheme Based on Pixel Grid | |
| rMosaicField | Mosaic Random Field | |
| sharpen | Data Sharpening of Point Pattern | |
| model.matrix.ppm | Extract Design Matrix from Point Process Model | |
| rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
| rmpoint | Generate N Random Multitype Points | |
| as.data.frame.psp | Coerce Line Segment Pattern to a Data Frame | |
| vertices | Vertices of a Window | |
| varblock | Estimate Variance of Summary Statistic by Subdivision | |
| ppp | Create a Point Pattern | |
| methods.boxx | Methods for Multi-Dimensional Box | |
| pppmatching | Create a Point Matching | |
| expand.owin | Expand Window By Factor | |
| profilepl | Profile Maximum Pseudolikelihood | |
| bei | Tropical rain forest trees | |
| summary.owin | Summary of a Spatial Window | |
| heather | Diggle's Heather Data | |
| shift.owin | Apply Vector Translation To Window | |
| pointsOnLines | Place Points Evenly Along Specified Lines | |
| summary.listof | Summary of a List of Things | |
| fryplot | Fry Plot of Point Pattern | |
| split.ppp | Divide Point Pattern into Sub-patterns | |
| ripras | Estimate window from points alone | |
| angles.psp | Orientation Angles of Line Segments | |
| quadrats | Divide Region into Quadrats | |
| as.box3 | Convert Data to Three-Dimensional Box | |
| intersect.owin | Intersection, Union or Set Subtraction of Two Windows | |
| square | Square Window | |
| runifpoint3 | Generate N Uniform Random Points in Three Dimensions | |
| swedishpines | Swedish Pines Point Pattern | |
| rstrat | Simulate Stratified Random Point Pattern | |
| endpoints.psp | Endpoints of Line Segment Pattern | |
| ewcdf | Weighted Empirical Cumulative Distribution Function | |
| simulate.kppm | Simulate a Fitted Cluster Point Process Model | |
| closing | Morphological Closing | |
| shift.ppp | Apply Vector Translation To Point Pattern | |
| simplify.owin | Approximate a Polygon by a Simpler Polygon | |
| rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |
| as.data.frame.im | Convert Pixel Image to Data Frame | |
| identify.psp | Identify Segments in a Line Segment Pattern | |
| bw.relrisk | Cross Validated Bandwidth Selection for Relative Risk Estimation | |
| eval.fv | Evaluate Expression Involving Functions | |
| simulate.ppm | Simulate a Fitted Gibbs Point Process Model | |
| pairsat.family | Saturated Pairwise Interaction Point Process Family | |
| whist | Weighted Histogram | |
| rpoint | Generate N Random Points | |
| rotate.owin | Rotate a Window | |
| rescale.im | Convert Pixel Image to Another Unit of Length | |
| rMaternII | Simulate Matern Model II | |
| rpoisline | Generate Poisson Random Line Process | |
| nncross | Nearest Neighbours Between Two Patterns | |
| ppx | Multidimensional Space-Time Point Pattern | |
| quad.object | Class of Quadrature Schemes | |
| rescale.ppp | Convert Point Pattern to Another Unit of Length | |
| quadratcount | Quadrat counting for a point pattern | |
| plot.slrm | Plot a Fitted Spatial Logistic Regression | |
| trim.rectangle | Cut margins from rectangle | |
| mincontrast | Method of Minimum Contrast | |
| superimpose | Superimpose Several Point Patterns | |
| rescue.rectangle | Convert Window Back To Rectangle | |
| redwood | California Redwoods Point Pattern (Ripley's Subset) | |
| discretise | Safely Convert Point Pattern Window to Binary Mask | |
| gridweights | Compute Quadrature Weights Based on Grid Counts | |
| model.images | Compute Images of Constructed Covariates | |
| pairs.im | Scatterplot Matrix for Pixel Images | |
| plot.quad | plot a Spatial Quadrature Scheme | |
| setcov | Set Covariance of a Window | |
| Kmeasure | Reduced Second Moment Measure | |
| harmonic | Basis for Harmonic Functions | |
| envelope | Simulation Envelopes of Summary Function | |
| rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |
| logLik.ppm | Log Likelihood for Poisson Point Process Model | |
| No Results! | ||
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Details
| Date | 2010-11-11 |
| License | GPL (>= 2) |
| URL | http://www.spatstat.org |
| Packaged | 2010-11-11 07:32:08 UTC; adrian |
| Repository | CRAN |
| Date/Publication | 2010-11-11 13:09:43 |
| 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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