spatstat v1.12-5
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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 | |
| Kest | K-function | |
| DiggleGratton | Diggle-Gratton model | |
| Ord | Generic Ord Interaction model | |
| anemones | Beadlet Anemones Data | |
| Geyer | Geyer's Saturation Point Process Model | |
| Gest | Nearest Neighbour Distance Function G | |
| spatstat | The Spatstat Package | |
| Jdot | Multitype J Function (i-to-any) | |
| MultiStrauss | The Multitype Strauss Point Process Model | |
| bei | Tropical rain forest trees | |
| Kinhom | Inhomogeneous K-function | |
| Softcore | The Soft Core Point Process Model | |
| chorley | Chorley-Ribble Cancer Data | |
| Jest | Estimate the J-function | |
| Strauss | The Strauss Point Process Model | |
| bdist.points | Distance to Boundary of Window | |
| Saturated | Saturated Pairwise Interaction model | |
| applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
| as.matrix.im | Convert Pixel Image to Matrix | |
| Kest.fft | K-function using FFT | |
| cut.ppp | Convert Point Pattern Marks from Numeric to Factor | |
| corners | Corners of a rectangle | |
| as.rectangle | Window Frame | |
| contour.im | Contour plot of pixel image | |
| StraussHard | The Strauss / Hard Core Point Process Model | |
| as.owin | Convert Data To Class owin | |
| bounding.box.xy | Convex Hull of Points | |
| eval.im | Evaluate Expression Involving Pixel Images | |
| Kdot | Multitype K Function (i-to-any) | |
| area.owin | Area of a Window | |
| affine.owin | Apply Affine Transformation To Window | |
| Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
| Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
| centroid.owin | Centroid of a window | |
| PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
| duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
| Jcross | Multitype J Function (i-to-j) | |
| im.object | Class of Images | |
| LennardJones | The Lennard-Jones Potential | |
| fasp.object | Function Arrays for Spatial Patterns | |
| distmap | Distance Map | |
| as.ppp | Convert Data To Class ppp | |
| as.psp | Convert Data To Class psp | |
| compatible.im | Test Whether Two Pixel Images Are Compatible | |
| hist.im | Histogram of Pixel Values in an Image | |
| convexhull.xy | Convex Hull of Points | |
| bounding.box | Bounding Box of a Window or Point Pattern | |
| endpoints.psp | Endpoints of Line Segment Pattern | |
| Kcross.inhom | Inhomogeneous Cross K Function | |
| midpoints.psp | Midpoints of Line Segment Pattern | |
| affine.psp | Apply Affine Transformation To Line Segment Pattern | |
| dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
| crossdist.ppp | Pairwise distances between two different point patterns | |
| dilate.owin | Dilate a Window | |
| Gmulti | Marked Nearest Neighbour Distance Function | |
| levelset | Level Set of a Pixel Image | |
| ewcdf | Weighted Empirical Cumulative Distribution Function | |
| is.marked.ppm | Test Whether A Point Process Model is Marked | |
| betacells | Beta Ganglion Cells in Cat Retina | |
| ppp.object | Class of Point Patterns | |
| eroded.areas | Areas of Morphological Erosions | |
| concatxy | Concatenate x,y Coordinate Vectors | |
| plot.fv | Plot Function Valuesn | |
| OrdThresh | Ord's Interaction model | |
| as.im | Convert to Pixel Image | |
| cut.im | Convert Pixel Image from Numeric to Factor | |
| cells | Biological Cells Point Pattern | |
| clickppp | Interactively Add Points | |
| ants | Harkness-Isham ants' nests data | |
| lansing | Lansing Woods Point Pattern | |
| is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
| anova.ppm | ANOVA for Fitted Point Process Models | |
| Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
| pcf | Pair Correlation Function | |
| disc | Circular Window | |
| Pairwise | Generic Pairwise Interaction model | |
| rescale | Convert dataset to another unit of length | |
| distmap.psp | Distance Map of Line Segment Pattern | |
| Kmeasure | Reduced Second Moment Measure | |
| discretise | Safely Convert Point Pattern Window to Binary Mask | |
| eval.hyper | Evaluate an Expression in Each Row of a Hyperframe | |
| rsyst | Simulate systematic random point pattern | |
| append.psp | Combine Two Line Segment Patterns | |
| Jmulti | Marked J Function | |
| demopat | Artificial Data Point Pattern | |
| bramblecanes | Hutchings' Bramble Canes data | |
| alltypes | Calculate Statistic for All Types in a Multitype Point Pattern | |
| finpines | Pine saplings in Finland. | |
| MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
| as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |
| amacrine | Hughes' Amacrine Cell Data | |
| as.mask | Pixel Image Approximation of a Window | |
| compatible.fv | Test Whether Two Function Objects Are Compatible | |
| clickpoly | Interactively Define a Polygon | |
| Poisson | Poisson Point Process Model | |
| intersect.owin | Intersection or Union of Two Windows | |
| im | Create a Pixel Image Object | |
| complement.owin | Take Complement of a Window | |
| clarkevans | Clark and Evans Aggregation Index | |
| Kmulti | Marked K-Function | |
| Kcross | Multitype K Function (Cross-type) | |
| crossdist.default | Pairwise distances between two different sets of points | |
| bdist.pixels | Distance to Boundary of Window | |
| logLik.ppm | Log Likelihood for Poisson Point Process Model | |
| copper | Berman-Huntington points and lines data | |
| is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
| harmonic | Basis for Harmonic Functions | |
| diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
| distmap.ppp | Distance Map of Point Pattern | |
| expand.owin | Expand Window By Factor | |
| humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
| fv.object | Data Frames of Function Values | |
| ponderosa | Ponderosa Pine Tree Point Pattern | |
| rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |
| lengths.psp | Lengths of Line Segments | |
| plot.listof | Plot a List of Things | |
| pairdist.psp | Pairwise distances between line segments | |
| rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |
| km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
| gridweights | Compute Quadrature Weights Based on Grid Counts | |
| fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
| plot.im | Plot a Pixel Image | |
| rMaternI | Simulate Matern Model I | |
| japanesepines | Japanese Pines Point Pattern | |
| pairsat.family | Saturated Pairwise Interaction Point Process Family | |
| plot.quad | plot a Spatial Quadrature Scheme | |
| is.multitype | Test whether Object is Multitype | |
| rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |
| plot.ppm | plot a Fitted Point Process Model | |
| density.psp | Kernel Smoothing of Line Segment Pattern | |
| plot.splitppp | Plot a List of Point Patterns | |
| owin | Create a Window | |
| summary.listof | Summary of a List of Things | |
| shift.psp | Apply Vector Translation To Line Segment Pattern | |
| qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
| nnwhich | Nearest neighbour | |
| gridcentres | Rectangular grid of points | |
| rThomas | Simulate Thomas Process | |
| distmap.owin | Distance Map of Window | |
| plot.ppp | plot a Spatial Point Pattern | |
| plot.fasp | Plot a Function Array | |
| density.ppp | Kernel Smoothed Intensity of Point Pattern | |
| letterR | Window in Shape of Letter R | |
| rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
| suffstat | Sufficient Statistic of Point Process Model | |
| psp | Create a Line Segment Pattern | |
| diameter | Diameter of a Window | |
| summary.ppm | Summarizing a Fitted Point Process Model | |
| rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
| setcov | Set Covariance of a Window | |
| rshift | Random Shift | |
| runifpoint | Generate N Uniform Random Points | |
| pcf.fv | Pair Correlation Function obtained from K Function | |
| rotate | Rotate | |
| lurking | Lurking variable plot | |
| dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
| quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
| nndist.psp | Nearest neighbour distances between line segments | |
| pcf.fasp | Pair Correlation Function obtained from array of K functions | |
| pppdist | Distance Between Two Point Patterns | |
| crossing.psp | Crossing Points of Two Line Segment Patterns | |
| erode.owin | Erode a Window | |
| identify.ppp | Identify Points in a Point Pattern | |
| rlinegrid | Generate grid of parallel lines with random displacement | |
| ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
| print.ppm | Print a Fitted Point Process Model | |
| is.im | Test Whether An Object Is A Pixel Image | |
| psp.object | Class of Line Segment Patterns | |
| spokes | Spokes pattern of dummy points | |
| data.ppm | Extract Original Data from a Fitted Point Process Model | |
| default.dummy | Generate a Default Pattern of Dummy Points | |
| interp.im | Interpolate a Pixel Image | |
| is.marked.ppp | Test Whether A Point Pattern is Marked | |
| crossdist | Pairwise distances | |
| hamster | Aherne's hamster tumour data | |
| spatstat-deprecated | Deprecated spatstat functions | |
| redwood | California Redwoods Point Pattern (Ripley's Subset) | |
| eval.fv | Evaluate Expression Involving Functions | |
| ppm.object | Class of Fitted Point Process Models | |
| print.ppp | Print Brief Details of a Point Pattern Dataset | |
| predict.ppm | Prediction from a Fitted Point Process Model | |
| rmpoispp | Generate Multitype Poisson Point Pattern | |
| hyperframe | Hyper Data Frame | |
| rshift.ppp | Randomly Shift a Point Pattern | |
| is.owin | Test Whether An Object Is A Window | |
| is.marked | Test Whether Marks Are Present | |
| is.ppp | Test Whether An Object Is A Point Pattern | |
| is.subset.owin | Determine Whether One Window is Contained In Another | |
| raster.x | Cartesian Coordinates for a Pixel Raster | |
| kstest.ppm | Kolmogorov-Smirnov Test for Point Process Model | |
| owin.object | Class owin | |
| mean.im | Mean Pixel Value in an Image | |
| lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| rthin | Random Thinning | |
| ppm | Fit Point Process Model to Data | |
| eem | Exponential Energy Marks | |
| spruces | Spruces Point Pattern | |
| print.im | Print Brief Details of an Image | |
| smooth.ppp | Spatial smoothing of observations at irregular points | |
| reach | Interaction Distance of a Point Process | |
| ord.family | Ord Interaction Process Family | |
| setmarks | Set or Reset the Marks in a Point Pattern | |
| fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |
| rStrauss | Perfect Simulation of the Strauss Process | |
| residuals.ppm | Residuals for Fitted Point Process Model | |
| pairdist.default | Pairwise distances | |
| persp.im | Perspective Plot of Pixel Image | |
| rcell | Simulate Baddeley-Silverman Cell Process | |
| rmh.ppm | Simulate from a Fitted Point Process Model | |
| matchingdist | Distance for a Point Pattern Matching | |
| rstrat | Simulate Stratified Random Point Pattern | |
| split.ppp | Divide Point Pattern into Sub-patterns | |
| markcorr | Mark Correlation Function | |
| matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
| subset.ppp | Extract or Replace Subset of Point Pattern | |
| crossdist.psp | Pairwise distances between two different line segment patterns | |
| rmpoint | Generate N Random Multitype Points | |
| rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |
| plot.owin | Plot a Spatial Window | |
| pppmatching | Create a Point Matching | |
| Lest | L-function | |
| shift.im | Apply Vector Translation To Pixel Image | |
| affine | Apply Affine Transformation | |
| Fest | Estimate the empty space function F | |
| rescue.rectangle | Convert Window Back To Rectangle | |
| runifdisc | Generate N Uniform Random Points in a Disc | |
| allstats | Calculate four standard summary functions of a point pattern. | |
| shift.ppp | Apply Vector Translation To Point Pattern | |
| subset.splitppp | Extract or Replace Sub-Patterns | |
| profilepl | Profile Maximum Pseudolikelihood | |
| shift.owin | Apply Vector Translation To Window | |
| quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
| rescale.owin | Convert Window to Another Unit of Length | |
| nncorr | Nearest-Neighbour Correlation of Marked Point Pattern | |
| subset.fv | Extract Subset of Function Values | |
| quadratcount | Quadrat counting for a point pattern | |
| simdat | Simulated Point Pattern | |
| nearest.raster.point | Find Pixel Nearest to a Given Point | |
| rNeymanScott | Simulate Neyman-Scott Process | |
| multiplicity.ppp | Count Multiplicity of Duplicate Points | |
| square | Square Window | |
| plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
| angles.psp | Orientation Angles of Line Segments | |
| pcf.ppp | Pair Correlation Function of Point Pattern | |
| redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
| nztrees | New Zealand Trees Point Pattern | |
| rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
| ripras | Estimate window from points alone | |
| pairwise.family | Pairwise Interaction Process Family | |
| rpoint | Generate N Random Points | |
| rMaternII | Simulate Matern Model II | |
| print.quad | Print a Quadrature Scheme | |
| rescale.ppp | Convert Point Pattern to Another Unit of Length | |
| plot.psp | plot a Spatial Line Segment Pattern | |
| quadrat.test | Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
| residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
| rlabel | Random Re-Labelling of Point Pattern | |
| spatstat.options | Internal Options in Spatstat Package | |
| progressreport | Print Progress Reports | |
| quad.object | Class of Quadrature Schemes | |
| pairdist.ppp | Pairwise distances | |
| reduced.sample | Reduced Sample Estimator using Histogram Data | |
| selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
| inside.owin | Test Whether Points Are Inside A Window | |
| nncross | Nearest Neighbour in Another Point Pattern | |
| rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
| shift | Apply Vector Translation | |
| rMatClust | Simulate Matern Cluster Process | |
| subset.fasp | Extract Subset of Function Array | |
| rotate.psp | Rotate a Line Segment Pattern | |
| rpoisline | Generate Poisson Random Line Process | |
| nbfires | Point Patterns of New Brunswick Forest Fires | |
| solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
| rSSI | Simulate Simple Sequential Inhibition | |
| summary.ppp | Summary of a Point Pattern Dataset | |
| summary.psp | Summary of a Line Segment Pattern Dataset | |
| subsetget.im | Reset Values in Subset of Image | |
| rpoispp | Generate Poisson Point Pattern | |
| quantile.im | Sample Quantiles of Pixel Image | |
| rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
| summary.im | Summarizing a Pixel Image | |
| summary.owin | Summary of a Spatial Window | |
| rshift.psp | Randomly Shift a Line Segment Pattern | |
| rotate.owin | Rotate a Window | |
| superimpose | Superimpose Several Point Patterns | |
| subset.listof | Extract or Replace Subset of a List of Things | |
| rotate.ppp | Rotate a Point Pattern | |
| subset.im | Extract Subset of Image | |
| subset.psp | Extract Subset of Line Segment Pattern | |
| swedishpines | Swedish Pines Point Pattern | |
| unmark | Remove Marks from a Marked Point Pattern | |
| vertices | Vertices of a Window | |
| unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
| trim.rectangle | Cut margins from rectangle | |
| unitname | Name for Unit of Length | |
| summary.quad | Summarizing a Quadrature Scheme | |
| summary.splitppp | Summary of a Split Point Pattern | |
| update.ppm | Update a Fitted Point Process Model | |
| vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
| union.quad | Union of Data and Dummy Points | |
| affine.ppp | Apply Affine Transformation To Point Pattern | |
| Iest | Estimate the I-function | |
| thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
| coef.ppm | Coefficients of Fitted Point Process Model | |
| density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
| envelope | Simulation envelopes of summary function | |
| is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
| mincontrast | Method of Minimum Contrast | |
| pairdist | Pairwise distances | |
| plot.hyperframe | Plot Entries in a Hyperframe | |
| spatstat-internal | Internal spatstat functions | |
| longleaf | Longleaf Pines Point Pattern | |
| markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
| localK | Neighbourhood density function | |
| nndist | Nearest neighbour distances | |
| print.owin | Print Brief Details of a Spatial Window | |
| kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
| rshift.splitppp | Randomly Shift a List of Point Patterns | |
| scanpp | Read Point Pattern From Data File | |
| ppp | Create a Point Pattern | |
| print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
| pppmatching.object | Class of Point Matchings | |
| No Results! | ||
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Details
| Date | 07 January 2008 |
| License | GPL (>= 2) |
| URL | http://www.spatstat.org |
| Packaged | Mon Jan 7 18:49:13 2008; adrian |
| depends | base (>= 2.6.0) , graphics , mgcv , R (>= 2.6.0) , stats |
| suggests | deldir , sm |
| Contributors | Rolf Turner, Adrian Baddeley |
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