spatstat v1.12-2
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 | |
| Geyer | Geyer's Saturation Point Process Model | |
| as.ppp | Convert Data To Class ppp | |
| cut.ppp | Convert Point Pattern Marks from Numeric to Factor | |
| ks.test.ppm | Kolmogorov-Smirnov Test for Point Process Model | |
| midpoints.psp | Midpoints of Line Segment Pattern | |
| plot.hyperframe | Plot Entries in a Hyperframe | |
| plot.fasp | Plot a Function Array | |
| rshift | Random Shift | |
| rmpoint | Generate N Random Multitype Points | |
| shift.ppp | Apply Vector Translation To Point Pattern | |
| affine.ppp | Apply Affine Transformation To Point Pattern | |
| corners | Corners of a rectangle | |
| clickppp | Interactively Add Points | |
| smooth.ppp | Spatial smoothing of observations at irregular points | |
| demopat | Artificial Data Point Pattern | |
| Fest | Estimate the empty space function F | |
| as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |
| as.owin | Convert Data To Class owin | |
| spruces | Spruces Point Pattern | |
| update.ppm | Update a Fitted Point Process Model | |
| bounding.box | Bounding Box of a Window or Point Pattern | |
| bdist.points | Distance to Boundary of Window | |
| Kest | K-function | |
| affine.psp | Apply Affine Transformation To Line Segment Pattern | |
| clickpoly | Interactively Define a Polygon | |
| crossing.psp | Crossing Points of Two Line Segment Patterns | |
| im | Create a Pixel Image Object | |
| contour.im | Contour plot of pixel image | |
| eroded.areas | Areas of Morphological Erosions | |
| mean.im | Mean Pixel Value in an Image | |
| envelope | Simulation envelopes of summary function | |
| pairdist | Pairwise distances | |
| hamster | Aherne's hamster tumour data | |
| is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
| Kdot | Multitype K Function (i-to-any) | |
| MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
| pairdist.psp | Pairwise distances between line segments | |
| plot.owin | Plot a Spatial Window | |
| matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
| dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
| multiplicity.ppp | Count Multiplicity of Duplicate Points | |
| print.im | Print Brief Details of an Image | |
| plot.ppp | plot a Spatial Point Pattern | |
| density.psp | Kernel Smoothing of Line Segment Pattern | |
| spatstat-deprecated | Deprecated spatstat functions | |
| Jcross | Multitype J Function (i-to-j) | |
| Jdot | Multitype J Function (i-to-any) | |
| gridweights | Compute Quadrature Weights Based on Grid Counts | |
| plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
| eval.hyper | Evaluate an Expression in Each Row of a Hyperframe | |
| angles.psp | Orientation Angles of Line Segments | |
| as.matrix.im | Convert Pixel Image to Matrix | |
| pairsat.family | Saturated Pairwise Interaction Point Process Family | |
| fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |
| eval.fv | Evaluate Expression Involving Functions | |
| diameter | Diameter of a Window | |
| discretise | Safely Convert Point Pattern Window to Binary Mask | |
| alltypes | Calculate Statistic for All Types in a Multitype Point Pattern | |
| plot.splitppp | Plot a List of Point Patterns | |
| quad.object | Class of Quadrature Schemes | |
| eem | Exponential Energy Marks | |
| superimpose | Superimpose Several Point Patterns | |
| subset.im | Extract Subset of Image | |
| as.psp | Convert Data To Class psp | |
| is.marked.ppm | Test Whether A Point Process Model is Marked | |
| gridcentres | Rectangular grid of points | |
| localK | Neighbourhood density function | |
| anemones | Beadlet Anemones Data | |
| allstats | Calculate four standard summary functions of a point pattern. | |
| ripras | Estimate window from points alone | |
| pcf.fasp | Pair Correlation Function obtained from array of K functions | |
| print.ppp | Print Brief Details of a Point Pattern Dataset | |
| rotate.owin | Rotate a Window | |
| fv.object | Data Frames of Function Values | |
| rshift.psp | Randomly Shift a Line Segment Pattern | |
| rthin | Random Thinning | |
| rSSI | Simulate Simple Sequential Inhibition | |
| quantile.im | Sample Quantiles of Pixel Image | |
| harmonic | Basis for Harmonic Functions | |
| Ord | Generic Ord Interaction model | |
| redwood | California Redwoods Point Pattern (Ripley's Subset) | |
| rescale.ppp | Convert Point Pattern to Another Unit of Length | |
| shift.im | Apply Vector Translation To Pixel Image | |
| Kmulti | Marked K-Function | |
| Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
| Kmeasure | Reduced Second Moment Measure | |
| compatible.fv | Test Whether Two Function Objects Are Compatible | |
| humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
| as.im | Convert to Pixel Image | |
| Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
| bramblecanes | Hutchings' Bramble Canes data | |
| clarkevans | Clark and Evans Aggregation Index | |
| letterR | Window in Shape of Letter R | |
| pairwise.family | Pairwise Interaction Process Family | |
| im.object | Class of Images | |
| as.rectangle | Window Frame | |
| rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
| crossdist | Pairwise distances | |
| complement.owin | Take Complement of a Window | |
| nbfires | Point Patterns of New Brunswick Forest Fires | |
| distmap | Distance Map | |
| Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
| Jest | Estimate the J-function | |
| nncorr | Nearest-Neighbour Correlation of Marked Point Pattern | |
| bounding.box.xy | Convex Hull of Points | |
| owin | Create a Window | |
| MultiStrauss | The Multitype Strauss Point Process Model | |
| erode.owin | Erode a Window | |
| plot.listof | Plot a List of Things | |
| profilepl | Profile Maximum Pseudolikelihood | |
| fasp.object | Function Arrays for Spatial Patterns | |
| ants | Harkness-Isham ants' nests data | |
| cut.im | Convert Pixel Image from Numeric to Factor | |
| inside.owin | Test Whether Points Are Inside A Window | |
| setcov | Set Covariance of a Window | |
| subset.ppp | Extract or Replace Subset of Point Pattern | |
| Kcross.inhom | Inhomogeneous Cross K Function | |
| suffstat | Sufficient Statistic of Point Process Model | |
| hist.im | Histogram of Pixel Values in an Image | |
| subsetget.im | Reset Values in Subset of Image | |
| nndist.psp | Nearest neighbour distances between line segments | |
| rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
| solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
| unmark | Remove Marks from a Marked Point Pattern | |
| owin.object | Class owin | |
| Kinhom | Inhomogeneous K-function | |
| expand.owin | Expand Window By Factor | |
| Strauss | The Strauss Point Process Model | |
| subset.splitppp | Extract or Replace Sub-Patterns | |
| vertices | Vertices of a Window | |
| copper | Berman-Huntington points and lines data | |
| Jmulti | Marked J Function | |
| identify.ppp | Identify Points in a Point Pattern | |
| simdat | Simulated Point Pattern | |
| dilate.owin | Dilate a Window | |
| endpoints.psp | Endpoints of Line Segment Pattern | |
| amacrine | Hughes' Amacrine Cell Data | |
| markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
| ewcdf | Weighted Empirical Cumulative Distribution Function | |
| DiggleGratton | Diggle-Gratton model | |
| spatstat | The Spatstat Package | |
| summary.ppp | Summary of a Point Pattern Dataset | |
| japanesepines | Japanese Pines Point Pattern | |
| Iest | Estimate the I-function | |
| interp.im | Interpolate a Pixel Image | |
| ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
| lansing | Lansing Woods Point Pattern | |
| OrdThresh | Ord's Interaction model | |
| data.ppm | Extract Original Data from a Fitted Point Process Model | |
| concatxy | Concatenate x,y Coordinate Vectors | |
| nnwhich | Nearest neighbour | |
| hyperframe | Hyper Data Frame | |
| subset.psp | Extract Subset of Line Segment Pattern | |
| ppp | Create a Point Pattern | |
| spatstat-internal | Internal spatstat functions | |
| summary.listof | Summary of a List of Things | |
| ord.family | Ord Interaction Process Family | |
| summary.psp | Summary of a Line Segment Pattern Dataset | |
| psp | Create a Line Segment Pattern | |
| pcf | Pair Correlation Function | |
| ppp.object | Class of Point Patterns | |
| pcf.fv | Pair Correlation Function obtained from K Function | |
| StraussHard | The Strauss / Hard Core Point Process Model | |
| pppdist | Distance Between Two Point Patterns | |
| rThomas | Simulate Thomas Process | |
| append.psp | Combine Two Line Segment Patterns | |
| print.quad | Print a Quadrature Scheme | |
| crossdist.default | Pairwise distances between two different sets of points | |
| redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
| vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
| is.im | Test Whether An Object Is A Pixel Image | |
| fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
| is.multitype | Test whether Object is Multitype | |
| predict.ppm | Prediction from a Fitted Point Process Model | |
| kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
| levelset | Level Set of a Pixel Image | |
| is.subset.owin | Determine Whether One Window is Contained In Another | |
| swedishpines | Swedish Pines Point Pattern | |
| matchingdist | Distance for a Point Pattern Matching | |
| mincontrast | Method of Minimum Contrast | |
| nndist | Nearest neighbour distances | |
| pcf.ppp | Pair Correlation Function of Point Pattern | |
| logLik.ppm | Log Likelihood for Poisson Point Process Model | |
| rNeymanScott | Simulate Neyman-Scott Process | |
| rMaternII | Simulate Matern Model II | |
| nztrees | New Zealand Trees Point Pattern | |
| plot.quad | plot a Spatial Quadrature Scheme | |
| nearest.raster.point | Find Pixel Nearest to a Given Point | |
| ponderosa | Ponderosa Pine Tree Point Pattern | |
| plot.im | Plot a Pixel Image | |
| affine | Apply Affine Transformation | |
| residuals.ppm | Residuals for Fitted Point Process Model | |
| rstrat | Simulate Stratified Random Point Pattern | |
| rStrauss | Perfect Simulation of the Strauss Process | |
| rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |
| setmarks | Set or Reset the Marks in a Point Pattern | |
| chorley | Chorley-Ribble Cancer Data | |
| reduced.sample | Reduced Sample Estimator using Histogram Data | |
| convexhull.xy | Convex Hull of Points | |
| runifdisc | Generate N Uniform Random Points in a Disc | |
| summary.im | Summarizing a Pixel Image | |
| subset.fasp | Extract Subset of Function Array | |
| is.marked | Test Whether Marks Are Present | |
| rescale.owin | Convert Window to Another Unit of Length | |
| thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
| reach | Interaction Distance of a Point Process | |
| quadratcount | Quadrat counting for a point pattern | |
| quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
| print.owin | Print Brief Details of a Spatial Window | |
| print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
| Softcore | The Soft Core Point Process Model | |
| duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
| print.ppm | Print a Fitted Point Process Model | |
| rcell | Simulate Baddeley-Silverman Cell Process | |
| quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
| rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |
| distmap.ppp | Distance Map of Point Pattern | |
| km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
| rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
| trim.rectangle | Cut margins from rectangle | |
| rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
| rescue.rectangle | Convert Window Back To Rectangle | |
| rpoispp | Generate Poisson Point Pattern | |
| subset.listof | Extract or Replace Subset of a List of Things | |
| pairdist.ppp | Pairwise distances | |
| pairdist.default | Pairwise distances | |
| rmpoispp | Generate Multitype Poisson Point Pattern | |
| rlinegrid | Generate grid of parallel lines with random displacement | |
| rsyst | Simulate systematic random point pattern | |
| shift.psp | Apply Vector Translation To Line Segment Pattern | |
| rpoint | Generate N Random Points | |
| rotate.ppp | Rotate a Point Pattern | |
| plot.psp | plot a Spatial Line Segment Pattern | |
| qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
| union.quad | Union of Data and Dummy Points | |
| rMatClust | Simulate Matern Cluster Process | |
| unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
| raster.x | Cartesian Coordinates for a Pixel Raster | |
| rlabel | Random Re-Labelling of Point Pattern | |
| centroid.owin | Centroid of a window | |
| bdist.pixels | Distance to Boundary of Window | |
| crossdist.psp | Pairwise distances between two different line segment patterns | |
| shift | Apply Vector Translation | |
| summary.splitppp | Summary of a Split Point Pattern | |
| density.ppp | Kernel Smoothed Intensity of Point Pattern | |
| eval.im | Evaluate Expression Involving Pixel Images | |
| is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
| markcorr | Mark Correlation Function | |
| ppm | Fit Point Process Model to Data | |
| pppmatching.object | Class of Point Matchings | |
| rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |
| rpoisline | Generate Poisson Random Line Process | |
| split.ppp | Divide Point Pattern into Sub-patterns | |
| spatstat.options | Internal Options in Spatstat Package | |
| Gest | Nearest Neighbour Distance Function G | |
| LennardJones | The Lennard-Jones Potential | |
| PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
| Saturated | Saturated Pairwise Interaction model | |
| affine.owin | Apply Affine Transformation To Window | |
| crossdist.ppp | Pairwise distances between two different point patterns | |
| default.dummy | Generate a Default Pattern of Dummy Points | |
| density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
| distmap.psp | Distance Map of Line Segment Pattern | |
| progressreport | Print Progress Reports | |
| quadrat.test | Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
| residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
| rmh.ppm | Simulate from a Fitted Point Process Model | |
| rshift.splitppp | Randomly Shift a List of Point Patterns | |
| runifpoint | Generate N Uniform Random Points | |
| subset.fv | Extract Subset of Function Values | |
| summary.owin | Summary of a Spatial Window | |
| area.owin | Area of a Window | |
| bei | Tropical rain forest trees | |
| disc | Circular Window | |
| is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
| is.ppp | Test Whether An Object Is A Point Pattern | |
| persp.im | Perspective Plot of Pixel Image | |
| lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |
| rescale | Convert dataset to another unit of length | |
| shift.owin | Apply Vector Translation To Window | |
| rotate.psp | Rotate a Line Segment Pattern | |
| square | Square Window | |
| summary.quad | Summarizing a Quadrature Scheme | |
| Lest | L-function | |
| as.mask | Pixel Image Approximation of a Window | |
| Pairwise | Generic Pairwise Interaction model | |
| cells | Biological Cells Point Pattern | |
| compatible.im | Test Whether Two Pixel Images Are Compatible | |
| diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
| dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
| finpines | Pine saplings in Finland. | |
| is.marked.ppp | Test Whether A Point Pattern is Marked | |
| lurking | Lurking variable plot | |
| rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
| ppm.object | Class of Fitted Point Process Models | |
| rotate | Rotate | |
| summary.ppm | Summarizing a Fitted Point Process Model | |
| unitname | Name for Unit of Length | |
| Gmulti | Marked Nearest Neighbour Distance Function | |
| Kest.fft | K-function using FFT | |
| betacells | Beta Ganglion Cells in Cat Retina | |
| Poisson | Poisson Point Process Model | |
| coef.ppm | Coefficients of Fitted Point Process Model | |
| distmap.owin | Distance Map of Window | |
| nncross | Nearest Neighbour in Another Point Pattern | |
| longleaf | Longleaf Pines Point Pattern | |
| plot.ppm | plot a Fitted Point Process Model | |
| rMaternI | Simulate Matern Model I | |
| spokes | Spokes pattern of dummy points | |
| Kcross | Multitype K Function (Cross-type) | |
| anova.ppm | ANOVA for Fitted Point Process Models | |
| applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
| intersect.owin | Intersection or Union of Two Windows | |
| is.owin | Test Whether An Object Is A Window | |
| pppmatching | Create a Point Matching | |
| plot.fv | Plot Function Valuesn | |
| lengths.psp | Lengths of Line Segments | |
| psp.object | Class of Line Segment Patterns | |
| rshift.ppp | Randomly Shift a Point Pattern | |
| selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
| scanpp | Read Point Pattern From Data File | |
| No Results! | ||
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Details
| Date | 26 October 2007 |
| License | GPL version 2 or newer |
| URL | http://www.spatstat.org |
| Packaged | Sat Oct 27 01:15:04 2007; 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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