spatstat v1.11-6
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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 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 | |
| DiggleGratton | Diggle-Gratton model | |
| Kdot | Multitype K Function (i-to-any) | |
| as.ppp | Convert Data To Class ppp | |
| concatxy | Concatenate x,y Coordinate Vectors | |
| crossdist.default | Pairwise distances between two different sets of points | |
| density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
| bdist.points | Distance to Boundary of Window | |
| is.im | Test Whether An Object Is A Pixel Image | |
| distmap.ppp | Distance Map of Point Pattern | |
| intersect.owin | Intersection or Union of Two Windows | |
| ks.test.ppm | Kolmogorov-Smirnov Test for Point Process Model | |
| pcf.ppp | Pair Correlation Function of Point Pattern | |
| Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
| plot.fasp | Plot a Function Array | |
| plot.splitppp | Plot a List of Point Patterns | |
| ppp | Create a Point Pattern | |
| Fest | Estimate the empty space function F | |
| plot.fv | Plot Function Valuesn | |
| Iest | Estimate the I-function | |
| append.psp | Combine Two Line Segment Patterns | |
| print.quad | Print a Quadrature Scheme | |
| print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
| data.ppm | Extract Original Data from a Fitted Point Process Model | |
| bounding.box.xy | Convex Hull of Points | |
| ewcdf | Weighted Empirical Cumulative Distribution Function | |
| rStrauss | Perfect Simulation of the Strauss Process | |
| rMaternII | Simulate Matern Model II | |
| raster.x | Cartesian Coordinates for a Pixel Raster | |
| compatible.im | Test Whether Two Pixel Images Are Compatible | |
| letterR | Window in Shape of Letter R | |
| default.dummy | Generate a Default Pattern of Dummy Points | |
| rotate | Rotate | |
| setmarks | Set or Reset the Marks in a Point Pattern | |
| erode.owin | Erode a Window | |
| redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
| unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
| residuals.ppm | Residuals for Fitted Point Process Model | |
| matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
| rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |
| eroded.areas | Areas of Morphological Erosions | |
| pairdist.default | Pairwise distances | |
| spatstat.options | Internal Options in Spatstat Package | |
| plot.psp | plot a Spatial Line Segment Pattern | |
| subset.fasp | Extract Subset of Function Array | |
| humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
| is.marked | Test Whether Marks Are Present | |
| subset.listof | Extract or Replace Subset of a List of Things | |
| applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
| PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
| nncross | Nearest Neighbour in Another Point Pattern | |
| density.psp | Kernel Smoothing of Line Segment Pattern | |
| vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
| rThomas | Simulate Thomas Process | |
| summary.owin | Summary of a Spatial Window | |
| distmap.psp | Distance Map of Line Segment Pattern | |
| bdist.pixels | Distance to Boundary of Window | |
| alltypes | Calculate Statistic for All Types in a Multitype Point Pattern | |
| rpoisline | Generate Poisson Random Line Process | |
| Kcross.inhom | Inhomogeneous Cross K Function | |
| residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
| crossing.psp | Crossing Points of Two Line Segment Patterns | |
| plot.owin | Plot a Spatial Window | |
| rmh.ppm | Simulate from a Fitted Point Process Model | |
| quantile.im | Sample Quantiles of Pixel Image | |
| affine.psp | Apply Affine Transformation To Line Segment Pattern | |
| rSSI | Simulate Simple Sequential Inhibition | |
| density.ppp | Kernel Smoothed Intensity of Point Pattern | |
| as.im | Convert to Pixel Image | |
| dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
| rotate.ppp | Rotate a Point Pattern | |
| is.ppp | Test Whether An Object Is A Point Pattern | |
| subset.ppp | Extract or Replace Subset of Point Pattern | |
| owin.object | Class owin | |
| crossdist.psp | Pairwise distances between two different line segment patterns | |
| Kcross | Multitype K Function (Cross-type) | |
| quad.object | Class of Quadrature Schemes | |
| copper | Berman-Huntington points and lines data | |
| fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |
| superimpose | Superimpose Several Point Patterns | |
| Saturated | Saturated Pairwise Interaction model | |
| angles.psp | Orientation Angles of Line Segments | |
| spatstat-internal | Internal spatstat functions | |
| is.marked.ppp | Test Whether A Point Pattern is Marked | |
| rmpoispp | Generate Multitype Poisson Point Pattern | |
| rotate.psp | Rotate a Line Segment Pattern | |
| disc | Circular Window | |
| Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
| shift.ppp | Apply Vector Translation To Point Pattern | |
| longleaf | Longleaf Pines Point Pattern | |
| hamster | Aherne's hamster tumour data | |
| mean.im | Mean Pixel Value in an Image | |
| gridcentres | Rectangular grid of points | |
| hist.im | Histogram of Pixel Values in an Image | |
| rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |
| interp.im | Interpolate a Pixel Image | |
| spatstat | The Spatstat Package | |
| spokes | Spokes pattern of dummy points | |
| japanesepines | Japanese Pines Point Pattern | |
| Softcore | The Soft Core Point Process Model | |
| MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
| affine | Apply Affine Transformation | |
| lurking | Lurking variable plot | |
| rsyst | Simulate systematic random point pattern | |
| amacrine | Hughes' Amacrine Cell Data | |
| subset.im | Extract Subset of Image | |
| distmap.owin | Distance Map of Window | |
| nztrees | New Zealand Trees Point Pattern | |
| as.rectangle | Window Frame | |
| chorley | Chorley-Ribble Cancer Data | |
| rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
| rpoispp | Generate Poisson Point Pattern | |
| cells | Biological Cells Point Pattern | |
| solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
| unmark | Remove Marks from a Marked Point Pattern | |
| Jmulti | Marked J Function | |
| ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
| inside.owin | Test Whether Points Are Inside A Window | |
| print.ppm | Print a Fitted Point Process Model | |
| summary.quad | Summarizing a Quadrature Scheme | |
| pairdist | Pairwise distances | |
| Pairwise | Generic Pairwise Interaction model | |
| crossdist.ppp | Pairwise distances between two different point patterns | |
| pairsat.family | Saturated Pairwise Interaction Point Process Family | |
| demopat | Artificial Data Point Pattern | |
| profilepl | Profile Maximum Pseudolikelihood | |
| envelope | Simulation envelopes of summary function | |
| levelset | Level Set of a Pixel Image | |
| pcf.fv | Pair Correlation Function obtained from K Function | |
| nbfires | Point Patterns of New Brunswick Forest Fires | |
| summary.im | Summarizing a Pixel Image | |
| subset.psp | Extract Subset of Line Segment Pattern | |
| plot.ppp | plot a Spatial Point Pattern | |
| pppdist | Optimal Match Between Two Point Patterns | |
| ppm | Fit Point Process Model to Data | |
| gridweights | Compute Quadrature Weights Based on Grid Counts | |
| multiplicity.ppp | Count Multiplicity of Duplicate Points | |
| rescale.owin | Convert Window to Another Unit of Length | |
| rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
| quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
| rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
| rotate.owin | Rotate a Window | |
| plot.listof | Plot a List of Things | |
| psp.object | Class of Line Segment Patterns | |
| simdat | Simulated Point Pattern | |
| bei | Tropical rain forest trees | |
| rNeymanScott | Simulate Neyman-Scott Process | |
| suffstat | Sufficient Statistic of Point Process Model | |
| shift | Apply Vector Translation | |
| union.quad | Union of Data and Dummy Points | |
| bramblecanes | Hutchings' Bramble Canes data | |
| diameter | Diameter of a Window | |
| shift.psp | Apply Vector Translation To Line Segment Pattern | |
| Kinhom | Inhomogeneous K-function | |
| trim.rectangle | Cut margins from rectangle | |
| thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
| summary.splitppp | Summary of a Split Point Pattern | |
| ants | Harkness-Isham ants' nests data | |
| vertices | Vertices of a Window | |
| lansing | Lansing Woods Point Pattern | |
| owin | Create a Window | |
| as.matrix.im | Convert Pixel Image to Matrix | |
| rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |
| Geyer | Geyer's Saturation Point Process Model | |
| Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
| rescue.rectangle | Convert Window Back To Rectangle | |
| endpoints.psp | Endpoints of Line Segment Pattern | |
| finpines | Pine saplings in Finland. | |
| Poisson | Poisson Point Process Model | |
| harmonic | Basis for Harmonic Functions | |
| area.owin | Area of a Window | |
| as.owin | Convert Data To Class owin | |
| fv.object | Data Frames of Function Values | |
| coef.ppm | Coefficients of Fitted Point Process Model | |
| plot.quad | plot a Spatial Quadrature Scheme | |
| quadratcount | Quadrat counting for a point pattern | |
| runifpoint | Generate N Uniform Random Points | |
| dilate.owin | Dilate a Window | |
| compatible.fv | Test Whether Two Function Objects Are Compatible | |
| fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
| swedishpines | Swedish Pines Point Pattern | |
| im.object | Class of Images | |
| complement.owin | Take Complement of a Window | |
| is.owin | Test Whether An Object Is A Window | |
| logLik.ppm | Log Likelihood for Poisson Point Process Model | |
| nearest.raster.point | Find Pixel Nearest to a Given Point | |
| lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| mincontrast | Method of Minimum Contrast | |
| markcorr | Mark Correlation Function | |
| nndist | Nearest neighbour distances | |
| pairwise.family | Pairwise Interaction Process Family | |
| plot.ppm | plot a Fitted Point Process Model | |
| print.im | Print Brief Details of an Image | |
| shift.im | Apply Vector Translation To Pixel Image | |
| summary.psp | Summary of a Line Segment Pattern Dataset | |
| rlabel | Random Re-Labelling of Point Pattern | |
| ripras | Estimate window from points alone | |
| scanpp | Read Point Pattern From Data File | |
| subset.splitppp | Extract or Replace Sub-Patterns | |
| shift.owin | Apply Vector Translation To Window | |
| Kest | K-function | |
| Jcross | Multitype J Function (i-to-j) | |
| duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
| expand.owin | Expand Window By Factor | |
| Kest.fft | K-function using FFT | |
| betacells | Beta Ganglion Cells in Cat Retina | |
| im | Create a Pixel Image Object | |
| kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
| plot.im | Plot a Pixel Image | |
| rescale | Convert dataset to another unit of length | |
| anova.ppm | ANOVA for Fitted Point Process Models | |
| MultiStrauss | The Multitype Strauss Point Process Model | |
| clickpoly | Interactively Define a Polygon | |
| km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
| rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
| rstrat | Simulate Stratified Random Point Pattern | |
| summary.ppp | Summary of a Point Pattern Dataset | |
| ord.family | Ord Interaction Process Family | |
| summary.ppm | Summarizing a Fitted Point Process Model | |
| is.marked.ppm | Test Whether A Point Process Model is Marked | |
| psp | Create a Line Segment Pattern | |
| rMatClust | Simulate Matern Cluster Process | |
| quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
| rthin | Random Thinning | |
| rshift.splitppp | Randomly Shift a List of Point Patterns | |
| split.ppp | Divide Point Pattern into Sub-patterns | |
| square | Square Window | |
| units | Name for Unit of Length | |
| fasp.object | Function Arrays for Spatial Patterns | |
| eval.fv | Evaluate Expression Involving Functions | |
| is.multitype | Test whether Object is Multitype | |
| is.subset.owin | Determine Whether One Window is Contained In Another | |
| pcf | Pair Correlation Function | |
| Ord | Generic Ord Interaction model | |
| contour.im | Contour plot of pixel image | |
| ppm.object | Class of Fitted Point Process Models | |
| corners | Corners of a rectangle | |
| cut.im | Convert Pixel Image from Numeric to Factor | |
| print.owin | Print Brief Details of a Spatial Window | |
| rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |
| rescale.ppp | Convert Point Pattern to Another Unit of Length | |
| dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
| spatstat-deprecated | Deprecated spatstat functions | |
| eval.im | Evaluate Expression Involving Pixel Images | |
| lengths.psp | Lengths of Line Segments | |
| rshift.ppp | Randomly Shift a Point Pattern | |
| markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
| setcov | Set Covariance of a Window | |
| nnwhich | Nearest neighbour | |
| plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
| predict.ppm | Prediction from a Fitted Point Process Model | |
| rMaternI | Simulate Matern Model I | |
| rcell | Simulate Baddeley-Silverman Cell Process | |
| reach | Interaction Distance of a Point Process | |
| redwood | California Redwoods Point Pattern (Ripley's Subset) | |
| runifdisc | Generate N Uniform Random Points in a Disc | |
| rmpoint | Generate N Random Multitype Points | |
| spruces | Spruces Point Pattern | |
| selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
| Gest | Nearest Neighbour Distance Function G | |
| Jest | Estimate the J-function | |
| Gmulti | Marked Nearest Neighbour Distance Function | |
| Strauss | The Strauss Point Process Model | |
| affine.owin | Apply Affine Transformation To Window | |
| allstats | Calculate four standard summary functions of a point pattern. | |
| bounding.box | Bounding Box of a Window or Point Pattern | |
| convexhull.xy | Convex Hull of Points | |
| centroid.owin | Centroid of a window | |
| cut.ppp | Convert Point Pattern Marks from Numeric to Factor | |
| as.mask | Pixel Image Approximation of a Window | |
| is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
| nndist.psp | Nearest neighbour distances between line segments | |
| is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
| pairdist.ppp | Pairwise distances | |
| pairdist.psp | Pairwise distances between line segments | |
| pcf.fasp | Pair Correlation Function obtained from array of K functions | |
| persp.im | Perspective Plot of Pixel Image | |
| print.ppp | Print Brief Details of a Point Pattern Dataset | |
| update.ppm | Update a Fitted Point Process Model | |
| Jdot | Multitype J Function (i-to-any) | |
| anemones | Beadlet Anemones Data | |
| diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
| distmap | Distance Map | |
| eem | Exponential Energy Marks | |
| is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
| midpoints.psp | Midpoints of Line Segment Pattern | |
| ppp.object | Class of Point Patterns | |
| rpoint | Generate N Random Points | |
| subset.fv | Extract Subset of Function Values | |
| LennardJones | The Lennard-Jones Potential | |
| Kmulti | Marked K-Function | |
| nncorr | Nearest-Neighbour Correlation of Marked Point Pattern | |
| quadrat.test | Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
| rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
| rshift | Random Shift | |
| rshift.psp | Randomly Shift a Line Segment Pattern | |
| subsetget.im | Reset Values in Subset of Image | |
| OrdThresh | Ord's Interaction model | |
| affine.ppp | Apply Affine Transformation To Point Pattern | |
| Kmeasure | Reduced Second Moment Measure | |
| StraussHard | The Strauss / Hard Core Point Process Model | |
| as.psp | Convert Data To Class psp | |
| clickppp | Interactively Add Points | |
| crossdist | Pairwise distances | |
| identify.ppp | Identify Points in a Point Pattern | |
| progressreport | Print Progress Reports | |
| qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
| reduced.sample | Reduced Sample Estimator using Histogram Data | |
| summary.listof | Summary of a List of Things | |
| No Results! | ||
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Details
| Date | 18 May 2007 |
| License | GPL version 2 or newer |
| URL | http://www.spatstat.org |
| Packaged | Fri May 18 20:13:37 2007; adrian |
| depends | base (>= 2.4.0) , graphics , mgcv , R (>= 2.4.0) , stats |
| suggests | deldir , sm |
| Contributors | Rolf Turner, Adrian Baddeley |
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