spatstat v1.15-2
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. 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 | |
| rotate.owin | Rotate a Window | |
| rsyst | Simulate systematic random point pattern | |
| runifpointOnLines | Generate N Uniform Random Points On Line Segments | |
| square | Square Window | |
| subset.fasp | Extract Subset of Function Array | |
| update.kppm | Update a Fitted Cluster Point Process Model | |
| summary.ppp | Summary of a Point Pattern Dataset | |
| rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |
| subset.fv | Extract Subset of Function Values | |
| as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |
| Kcross.inhom | Inhomogeneous Cross K Function | |
| rthin | Random Thinning | |
| unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
| superimpose | Superimpose Several Point Patterns | |
| summary.owin | Summary of a Spatial Window | |
| simulate.kppm | Simulate a fitted cluster point process model. | |
| tiles | Extract List of Tiles in a Tessellation | |
| envelope | Simulation envelopes of summary function | |
| subset.splitppp | Extract or Replace Sub-Patterns | |
| rpoisline | Generate Poisson Random Line Process | |
| ppp | Create a Point Pattern | |
| rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
| fv.object | Data Frames of Function Values | |
| scanpp | Read Point Pattern From Data File | |
| stieltjes | Compute Integral of Function Against Cumulative Distribution | |
| solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
| rotate | Rotate | |
| fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
| spokes | Spokes pattern of dummy points | |
| [.quad | Subset of Quadrature Scheme | |
| subset.im | Extract Subset of Image | |
| split.im | Divide Image Into Sub-images | |
| rstrat | Simulate Stratified Random Point Pattern | |
| rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
| trim.rectangle | Cut margins from rectangle | |
| vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
| rmpoispp | Generate Multitype Poisson Point Pattern | |
| subset.listof | Extract or Replace Subset of a List of Things | |
| superimposePSP | Superimpose Several Line Segment Patterns | |
| update.ppm | Update a Fitted Point Process Model | |
| rotate.psp | Rotate a Line Segment Pattern | |
| summary.listof | Summary of a List of Things | |
| subset.psp | Extract Subset of Line Segment Pattern | |
| summary.splitppp | Summary of a Split Point Pattern | |
| shift.psp | Apply Vector Translation To Line Segment Pattern | |
| shift.ppp | Apply Vector Translation To Point Pattern | |
| rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |
| swedishpines | Swedish Pines Point Pattern | |
| thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
| runifdisc | Generate N Uniform Random Points in a Disc | |
| tess | Create a Tessellation | |
| setcov | Set Covariance of a Window | |
| subset.ppp | Extract or Replace Subset of Point Pattern | |
| rshift.ppp | Randomly Shift a Point Pattern | |
| unmark | Remove Marks | |
| subsetget.im | Reset Values in Subset of Image | |
| setmarks | Set or Reset the Marks in a Point Pattern | |
| split.ppp | Divide Point Pattern into Sub-patterns | |
| bounding.box.xy | Convex Hull of Points | |
| [.tess | Extract or Replace Subset of Tessellation | |
| unitname | Name for Unit of Length | |
| rshift | Random Shift | |
| Linhom | L-function | |
| MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
| affine.ppp | Apply Affine Transformation To Point Pattern | |
| spruces | Spruces Point Pattern | |
| rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |
| angles.psp | Orientation Angles of Line Segments | |
| rshift.psp | Randomly Shift a Line Segment Pattern | |
| shift.im | Apply Vector Translation To Pixel Image | |
| rmpoint | Generate N Random Multitype Points | |
| shift.owin | Apply Vector Translation To Window | |
| shift | Apply Vector Translation | |
| Kdot | Multitype K Function (i-to-any) | |
| rpoislinetess | Poisson Line Tessellation | |
| Geyer | Geyer's Saturation Point Process Model | |
| runifpoint | Generate N Uniform Random Points | |
| PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
| as.owin | Convert Data To Class owin | |
| as.psp | Convert Data To Class psp | |
| clip.infline | Intersect Infinite Straight Lines with a Window | |
| summary.ppm | Summarizing a Fitted Point Process Model | |
| rotate.ppp | Rotate a Point Pattern | |
| intersect.tess | Intersection of Two Tessellations | |
| as.ppp | Convert Data To Class ppp | |
| effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model | |
| rpoispp | Generate Poisson Point Pattern | |
| humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
| rpoint | Generate N Random Points | |
| Lcross | Multitype L-function (cross-type) | |
| affine.owin | Apply Affine Transformation To Window | |
| simdat | Simulated Point Pattern | |
| density.psp | Kernel Smoothing of Line Segment Pattern | |
| dirichlet | Dirichlet Tessellation of Point Pattern | |
| summary.im | Summarizing a Pixel Image | |
| fryplot | Fry Plot of Point Pattern | |
| smooth.ppp | Spatial smoothing of observations at irregular points | |
| append.psp | Combine Two Line Segment Patterns | |
| Pairwise | Generic Pairwise Interaction model | |
| bdist.points | Distance to Boundary of Window | |
| as.matrix.im | Convert Pixel Image to Matrix | |
| Ldot | Multitype L-function (i-to-any) | |
| is.multitype | Test whether Object is Multitype | |
| endpoints.psp | Endpoints of Line Segment Pattern | |
| Fest | Estimate the empty space function F | |
| crossing.psp | Crossing Points of Two Line Segment Patterns | |
| suffstat | Sufficient Statistic of Point Process Model | |
| ants | Harkness-Isham ants' nests data | |
| summary.psp | Summary of a Line Segment Pattern Dataset | |
| urkiola | Urkiola Woods Point Pattern | |
| crossdist.ppp | Pairwise distances between two different point patterns | |
| clarkevans | Clark and Evans Aggregation Index | |
| rshift.splitppp | Randomly Shift a List of Point Patterns | |
| im.object | Class of Images | |
| quadrat.test | Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
| discretise | Safely Convert Point Pattern Window to Binary Mask | |
| cut.ppp | Classify Points in a Point Pattern | |
| print.quad | Print a Quadrature Scheme | |
| pairwise.family | Pairwise Interaction Process Family | |
| pcf | Pair Correlation Function | |
| colourmap | Colour Lookup Tables | |
| areadiff | Difference of Disc Areas | |
| Lest | L-function | |
| predict.ppm | Prediction from a Fitted Point Process Model | |
| amacrine | Hughes' Amacrine Cell Data | |
| nearestsegment | Find Line Segment Nearest to Each Point | |
| density.ppp | Kernel Smoothed Intensity of Point Pattern | |
| BadGey | Hybrid Geyer Point Process Model | |
| rNeymanScott | Simulate Neyman-Scott Process | |
| coef.ppm | Coefficients of Fitted Point Process Model | |
| by.ppp | Apply a Function to a Point Pattern Broken Down by Factor | |
| OrdThresh | Ord's Interaction model | |
| Emark | Diagnostics for random marking | |
| complement.owin | Take Complement of a Window | |
| eval.hyper | Evaluate an Expression in Each Row of a Hyperframe | |
| erode.owin | Erode a Window | |
| Strauss | The Strauss Point Process Model | |
| crossdist | Pairwise distances | |
| is.ppp | Test Whether An Object Is A Point Pattern | |
| rjitter | Random Perturbation of a Point Pattern | |
| inforder.family | Infinite Order Interaction Family | |
| gpc2owin | Convert Polygonal Region into Different Format | |
| density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
| plot.splitppp | Plot a List of Point Patterns | |
| rThomas | Simulate Thomas Process | |
| pairdist.psp | Pairwise distances between line segments | |
| eval.fv | Evaluate Expression Involving Functions | |
| as.tess | Convert Data To Tessellation | |
| km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
| hamster | Aherne's hamster tumour data | |
| Jest | Estimate the J-function | |
| eem | Exponential Energy Marks | |
| plot.colourmap | Plot a Colour Map | |
| rescue.rectangle | Convert Window Back To Rectangle | |
| nncorr | Nearest-Neighbour Correlation of Marked Point Pattern | |
| Kinhom | Inhomogeneous K-function | |
| affine | Apply Affine Transformation | |
| clickppp | Interactively Add Points | |
| psp.object | Class of Line Segment Patterns | |
| adaptive.density | Intensity Estimate of Point Pattern Using Tessellation | |
| kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
| rStrauss | Perfect Simulation of the Strauss Process | |
| concatxy | Concatenate x,y Coordinate Vectors | |
| spatstat-internal | Internal spatstat functions | |
| Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
| Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
| redwood | California Redwoods Point Pattern (Ripley's Subset) | |
| murchison | Murchison gold deposits | |
| is.marked.ppp | Test Whether A Point Pattern is Marked | |
| Kest | K-function | |
| nncross | Nearest Neighbours Between Two Patterns | |
| Kcross | Multitype K Function (Cross-type) | |
| distmap.psp | Distance Map of Line Segment Pattern | |
| compatible.fasp | Test Whether Two Function Arrays Are Compatible | |
| plot.psp | plot a Spatial Line Segment Pattern | |
| model.matrix.ppm | Extract Design Matrix from Point Process Model | |
| plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
| ppp.object | Class of Point Patterns | |
| applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
| nearest.raster.point | Find Pixel Nearest to a Given Point | |
| LennardJones | The Lennard-Jones Potential | |
| Jcross | Multitype J Function (i-to-j) | |
| pppdist | Distance Between Two Point Patterns | |
| quadratcount | Quadrat counting for a point pattern | |
| as.mask | Pixel Image Approximation of a Window | |
| persp.im | Perspective Plot of Pixel Image | |
| allstats | Calculate four standard summary functions of a point pattern. | |
| Kmulti | Marked K-Function | |
| blur | Apply Gaussian Blur to a Pixel Image | |
| longleaf | Longleaf Pines Point Pattern | |
| pcf.ppp | Pair Correlation Function of Point Pattern | |
| demopat | Artificial Data Point Pattern | |
| spatstat-deprecated | Deprecated spatstat functions | |
| plot.tess | Plot a tessellation | |
| Gest | Nearest Neighbour Distance Function G | |
| pairdist | Pairwise distances | |
| as.im | Convert to Pixel Image | |
| rlabel | Random Re-Labelling of Point Pattern | |
| residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
| predict.kppm | Prediction from a Fitted Cluster Point Process Model | |
| bdist.pixels | Distance to Boundary of Window | |
| rMosaicSet | Mosaic Random Set | |
| Hest | Spherical Contact Distribution Function | |
| marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern | |
| Iest | Estimate the I-function | |
| rlinegrid | Generate grid of parallel lines with random displacement | |
| Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
| rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
| model.images | Compute Images of Constructed Covariates | |
| chop.tess | Subdivide a Window or Tessellation using a Set of Lines | |
| disc | Circular Window | |
| duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
| fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |
| reach | Interaction Distance of a Point Process | |
| data.ppm | Extract Original Data from a Fitted Point Process Model | |
| alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern | |
| AreaInter | The Area Interaction Point Process Model | |
| pixelquad | Quadrature Scheme Based on Pixel Grid | |
| rescale.im | Convert Pixel Image to Another Unit of Length | |
| ppm.object | Class of Fitted Point Process Models | |
| mean.im | Mean, Median and Range of Pixel Values in an Image | |
| is.im | Test Whether An Object Is A Pixel Image | |
| heather | Diggle's Heather Data | |
| centroid.owin | Centroid of a window | |
| hyperframe | Hyper Data Frame | |
| lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| Kest.fft | K-function using FFT | |
| residuals.ppm | Residuals for Fitted Point Process Model | |
| rMaternII | Simulate Matern Model II | |
| convexhull.xy | Convex Hull of Points | |
| anova.ppm | ANOVA for Fitted Point Process Models | |
| DiggleGratton | Diggle-Gratton model | |
| bei | Tropical rain forest trees | |
| Jdot | Multitype J Function (i-to-any) | |
| project2segment | Move Point To Nearest Line | |
| chorley | Chorley-Ribble Cancer Data | |
| nndist.psp | Nearest neighbour distances between line segments | |
| markvario | Mark Variogram | |
| default.dummy | Generate a Default Pattern of Dummy Points | |
| pcf.fv | Pair Correlation Function obtained from K Function | |
| im | Create a Pixel Image Object | |
| incircle | Find Largest Circle Inside Window | |
| psp | Create a Line Segment Pattern | |
| is.marked | Test Whether Marks Are Present | |
| hist.im | Histogram of Pixel Values in an Image | |
| rmh.ppm | Simulate from a Fitted Point Process Model | |
| nndist | Nearest neighbour distances | |
| lansing | Lansing Woods Point Pattern | |
| kstest.ppm | Kolmogorov-Smirnov Test for Point Process Model | |
| rescale.ppp | Convert Point Pattern to Another Unit of Length | |
| Jmulti | Marked J Function | |
| corners | Corners of a rectangle | |
| plot.owin | Plot a Spatial Window | |
| multiplicity.ppp | Count Multiplicity of Duplicate Points | |
| matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
| miplot | Morishita Index Plot | |
| dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
| dilate.owin | Dilate a Window | |
| lengths.psp | Lengths of Line Segments | |
| owin | Create a Window | |
| localK | Neighbourhood density function | |
| plot.listof | Plot a List of Things | |
| ord.family | Ord Interaction Process Family | |
| area.owin | Area of a Window | |
| pixellate | Convert Point Pattern to Pixel Image | |
| compatible.fv | Test Whether Two Function Objects Are Compatible | |
| ewcdf | Weighted Empirical Cumulative Distribution Function | |
| japanesepines | Japanese Pines Point Pattern | |
| kppm | Fit cluster point process model | |
| lut | Lookup Tables | |
| infline | Infinite Straight Lines | |
| affine.psp | Apply Affine Transformation To Line Segment Pattern | |
| redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
| MultiStrauss | The Multitype Strauss Point Process Model | |
| plot.ppm | plot a Fitted Point Process Model | |
| is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
| betacells | Beta Ganglion Cells in Cat Retina | |
| closing.owin | Morphological Closing of a Window | |
| finpines | Pine saplings in Finland. | |
| clickpoly | Interactively Define a Polygon | |
| expand.owin | Expand Window By Factor | |
| pcfcross | Multitype pair correlation function | |
| rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
| plot.im | Plot a Pixel Image | |
| distmap.owin | Distance Map of Window | |
| eval.im | Evaluate Expression Involving Pixel Images | |
| matchingdist | Distance for a Point Pattern Matching | |
| print.ppm | Print a Fitted Point Process Model | |
| qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
| rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |
| Softcore | The Soft Core Point Process Model | |
| intersect.owin | Intersection or Union of Two Windows | |
| contour.im | Contour plot of pixel image | |
| rescale.owin | Convert Window to Another Unit of Length | |
| pppmatching.object | Class of Point Matchings | |
| cut.im | Convert Pixel Image from Numeric to Factor | |
| rMaternI | Simulate Matern Model I | |
| owin.object | Class owin | |
| rSSI | Simulate Simple Sequential Inhibition | |
| print.owin | Print Brief Details of a Spatial Window | |
| eroded.areas | Areas of Morphological Erosions | |
| rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
| mincontrast | Method of Minimum Contrast | |
| spatstat.options | Internal Options in Spatstat Package | |
| fasp.object | Function Arrays for Spatial Patterns | |
| plot.fasp | Plot a Function Array | |
| delaunay | Delaunay Triangulation of Point Pattern | |
| bramblecanes | Hutchings' Bramble Canes data | |
| cells | Biological Cells Point Pattern | |
| nztrees | New Zealand Trees Point Pattern | |
| as.data.frame.psp | Coerce Line Segment Pattern to a Data Frame | |
| is.subset.owin | Determine Whether One Window is Contained In Another | |
| gridcentres | Rectangular grid of points | |
| markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
| spatstat | The Spatstat Package | |
| by.im | Apply Function to Image Broken Down by Factor | |
| markcorr | Mark Correlation Function | |
| Poisson | Poisson Point Process Model | |
| pppmatching | Create a Point Matching | |
| letterR | Window in Shape of Letter R | |
| rGaussPoisson | Simulate Gauss-Poisson Process | |
| eval.fasp | Evaluate Expression Involving Function Arrays | |
| SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model | |
| progressreport | Print Progress Reports | |
| distmap.ppp | Distance Map of Point Pattern | |
| levelset | Level Set of a Pixel Image | |
| pcf.fasp | Pair Correlation Function obtained from array of K functions | |
| ripras | Estimate window from points alone | |
| is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
| pairsat.family | Saturated Pairwise Interaction Point Process Family | |
| ponderosa | Ponderosa Pine Tree Point Pattern | |
| rMosaicField | Mosaic Random Field | |
| Kmeasure | Reduced Second Moment Measure | |
| rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |
| Ord | Generic Ord Interaction model | |
| copper | Berman-Huntington points and lines data | |
| quadrat.test.splitppp | Chi-Squared Test of CSR for Split Point Pattern | |
| logLik.ppm | Log Likelihood for Poisson Point Process Model | |
| ppm | Fit Point Process Model to Data | |
| nbfires | Point Patterns of New Brunswick Forest Fires | |
| rMatClust | Simulate Matern Cluster Process | |
| pointsOnLines | Place Points Evenly Along Specified Lines | |
| selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
| raster.x | Cartesian Coordinates for a Pixel Raster | |
| gridweights | Compute Quadrature Weights Based on Grid Counts | |
| markcorrint | Mark Correlation Integral | |
| plot.ppp | plot a Spatial Point Pattern | |
| distmap | Distance Map | |
| diameter | Diameter of a Window | |
| profilepl | Profile Maximum Pseudolikelihood | |
| quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
| pairdist.default | Pairwise distances | |
| lurking | Lurking variable plot | |
| rcell | Simulate Baddeley-Silverman Cell Process | |
| union.quad | Union of Data and Dummy Points | |
| markconnect | Mark Connection Function | |
| quantile.im | Sample Quantiles of Pixel Image | |
| harmonic | Basis for Harmonic Functions | |
| print.im | Print Brief Details of an Image | |
| Saturated | Saturated Pairwise Interaction model | |
| print.ppp | Print Brief Details of a Point Pattern Dataset | |
| StraussHard | The Strauss / Hard Core Point Process Model | |
| quad.object | Class of Quadrature Schemes | |
| ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
| midpoints.psp | Midpoints of Line Segment Pattern | |
| quadrats | Divide Region into Quadrats | |
| crossdist.default | Pairwise distances between two different sets of points | |
| is.marked.ppm | Test Whether A Point Process Model is Marked | |
| bounding.box | Bounding Box of a Window or Point Pattern | |
| nnwhich | Nearest neighbour | |
| dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
| interp.im | Interpolate a Pixel Image | |
| identify.ppp | Identify Points in a Point Pattern | |
| plot.fv | Plot Function Valuesn | |
| is.owin | Test Whether An Object Is A Window | |
| Gmulti | Marked Nearest Neighbour Distance Function | |
| pairdist.ppp | Pairwise distances | |
| is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
| opening.owin | Morphological Opening of a Window | |
| plot.quad | plot a Spatial Quadrature Scheme | |
| compatible.im | Test Whether Two Pixel Images Are Compatible | |
| inside.owin | Test Whether Points Are Inside A Window | |
| vertices | Vertices of a Window | |
| quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
| crossdist.psp | Pairwise distances between two different line segment patterns | |
| with.fv | Evaluate an Expression in a Function Table | |
| print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
| as.rectangle | Window Frame | |
| plot.hyperframe | Plot Entries in a Hyperframe | |
| quadratresample | Resample a Point Pattern by Resampling Quadrats | |
| diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
| plot.kppm | Plot a fitted cluster point process | |
| reduced.sample | Reduced Sample Estimator using Histogram Data | |
| summary.quad | Summarizing a Quadrature Scheme | |
| anemones | Beadlet Anemones Data | |
| rescale | Convert dataset to another unit of length | |
| No Results! | ||
Last month downloads
Details
| Date | 14 April 2009 |
| License | GPL (>= 2) |
| URL | http://www.spatstat.org |
| Packaged | Fri Apr 17 01:34:44 2009; adrian |
| Repository | CRAN |
| Date/Publication | 2009-04-16 08:22:00 |
| depends | base (>= 2.7.0) , deldir (>= 0.0-7) , gpclib , graphics , mgcv , R (>= 2.7.0) , stats , utils |
| suggests | maptools , sm |
| Contributors | Rolf Turner, Adrian Baddeley |
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