spatstat v1.9-1
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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.
Contains functions for exploratory data analysis,
model-fitting, simulation, 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 | |
| betacells | Beta Ganglion Cells in Cat Retina | |
| as.mask | Pixel Image Approximation of a Window | |
| alltypes | Calculate Statistic for All Types in a Multitype Point Pattern | |
| crossdist.psp | Pairwise distances between two different line segment patterns | |
| density.psp | Kernel Smoothing of Line Segment Pattern | |
| default.dummy | Generate a Default Pattern of Dummy Points | |
| spatstat-deprecated | Deprecated spatstat functions | |
| diameter | Diameter of a Window Frame | |
| spatstat-internal | Internal spatstat functions | |
| eval.im | Evaluate Expression Involving Pixel Images | |
| harmonic | Basis for Harmonic Functions | |
| is.owin | Test Whether An Object Is A Window | |
| longleaf | Longleaf Pines Point Pattern | |
| ppm.object | Class of Fitted Point Process Models | |
| anova.ppm | ANOVA for Fitted Point Process Models | |
| Saturated | Saturated Pairwise Interaction model | |
| nndist | Nearest neighbour distances | |
| envelope | Simulation envelopes of summary function | |
| rlabel | Random Re-Labelling of Point Pattern | |
| distmap.owin | Distance Map of Window | |
| as.im | Convert to Pixel Image | |
| as.matrix.im | Convert Pixel Image to Matrix | |
| compatible.fv | Test Whether Two Function Objects Are Compatible | |
| plot.fv | Plot Function Valuesn | |
| mincontrast | Method of Minimum Contrast | |
| hamster | Aherne's hamster tumour data | |
| nnwhich | Nearest neighbour | |
| plot.quad | plot a Spatial Quadrature Scheme | |
| thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
| crossdist.default | Pairwise distances between two different sets of points | |
| print.owin | Print Brief Details of a Spatial Window | |
| OrdThresh | Ord's Interaction model | |
| Pairwise | Generic Pairwise Interaction model | |
| diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
| fv.object | Data Frames of Function Values | |
| fasp.object | Function Arrays for Spatial Patterns | |
| print.ppm | Print a Fitted Point Process Model | |
| rshift.ppp | Randomly Shift a Point Pattern | |
| plot.owin | Plot a Spatial Window | |
| ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
| kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
| rmpoispp | Generate Multitype Poisson Point Pattern | |
| selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
| rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
| subset.fv | Extract Subset of Function Values | |
| ppp.object | Class of Point Patterns | |
| setcov | Set Covariance of a Window | |
| mean.im | Mean Pixel Value in an Image | |
| owin | Create a Window | |
| rstrat | Stratified random point pattern | |
| shift.psp | Apply Vector Translation To Line Segment Pattern | |
| pcf.fasp | Pair Correlation Function obtained from array of K functions | |
| summary.ppm | Summarizing a Fitted Point Process Model | |
| predict.ppm | Prediction from a Fitted Point Process Model | |
| summary.owin | Summary of a Spatial Window | |
| qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
| Kcross | Multitype K Function (Cross-type) | |
| Softcore | The Soft Core Point Process Model | |
| reach | Interaction Distance of a Point Process | |
| ants | Harkness-Isham ants' nests data | |
| shift.owin | Apply Vector Translation To Window | |
| affine.psp | Apply Affine Transformation To Line Segment Pattern | |
| is.ppp | Test Whether An Object Is A Point Pattern | |
| pairwise.family | Pairwise Interaction Process Family | |
| reduced.sample | Reduced Sample Estimator using Histogram Data | |
| Kest | K-function | |
| unmark | Remove Marks from a Marked Point Pattern | |
| Kmulti | Marked K-Function | |
| Jest | Estimate the J-function | |
| Jdot | Multitype J Function (i-to-any) | |
| Ord | Generic Ord Interaction model | |
| affine | Apply Affine Transformation | |
| as.psp | Convert Data To Class psp | |
| as.ppp | Convert Data To Class ppp | |
| amacrine | Hughes' Amacrine Cell Data | |
| area.owin | Area of a Window | |
| endpoints.psp | Endpoints of Line Segment Pattern | |
| complement.owin | Take Complement of a Window | |
| data.ppm | Extract Original Data from a Fitted Point Process Model | |
| nztrees | New Zealand Trees Point Pattern | |
| coef.ppm | Coefficients of Fitted Point Process Model | |
| eval.fv | Evaluate Expression Involving Functions | |
| erode.owin | Erode a Window | |
| Fest | Estimate the empty space function F | |
| lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| Kest.fft | K-function using FFT | |
| bounding.box | Bounding Box of a Window | |
| lurking | Lurking variable plot | |
| dilate.owin | Dilate a Window | |
| rMaternII | Simulate Matern Model II | |
| midpoints.psp | Midpoints of Line Segment Pattern | |
| plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
| rMatClust | Simulate Matern Cluster Process | |
| rmpoint | Generate N Random Multitype Points | |
| markcorr | Mark Correlation Function | |
| quad.object | Class of Quadrature Schemes | |
| rthin | Random Thinning | |
| pairsat.family | Saturated Pairwise Interaction Point Process Family | |
| identify.ppp | Identify Points in a Point Pattern | |
| simdat | Simulated Point Pattern | |
| pairdist.ppp | Pairwise distances | |
| quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
| matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
| lengths.psp | Lengths of Line Segments | |
| rpoint | Generate N Random Points | |
| nearest.raster.point | Find Pixel Nearest to a Given Point | |
| is.im | Test Whether An Object Is A Pixel Image | |
| rshift.splitppp | Randomly Shift a List of Point Patterns | |
| subset.ppp | Extract or Replace Subset of Point Pattern | |
| Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
| residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
| setmarks | Set or Reset the Marks in a Point Pattern | |
| Poisson | Poisson Point Process Model | |
| allstats | Calculate four standard summary functions of a point pattern. | |
| Jmulti | Marked J Function | |
| centroid.owin | Centroid of a window | |
| concatxy | Concatenate x,y Coordinate Vectors | |
| bramblecanes | Hutchings' Bramble Canes data | |
| superimpose | Superimpose Several Point Patterns | |
| Gest | Nearest Neighbour Distance Function G | |
| Kmeasure | Reduced Second Moment Measure | |
| compatible.im | Test Whether Two Pixel Images Are Compatible | |
| affine.owin | Apply Affine Transformation To Window | |
| chorley | Chorley-Ribble Cancer Data | |
| distmap.ppp | Distance Map of Point Pattern | |
| duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
| inside.owin | Test Whether Points Are Inside A Window | |
| cut.ppp | Convert Point Pattern Marks from Numeric to Factor | |
| is.marked.ppm | Test Whether A Point Process Model is Marked | |
| square | Square Window | |
| rshift | Random Shift | |
| nncorr | Nearest-Neighbour Correlation of Marked Point Pattern | |
| pairdist | Pairwise distances | |
| rotate.ppp | Rotate a Point Pattern | |
| plot.im | Plot a Pixel Image | |
| eroded.areas | Areas of Morphological Erosions | |
| dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
| ppm | Fit Point Process Model to Data | |
| suffstat | Sufficient Statistic of Point Process Model | |
| quadrat.test | Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
| print.ppp | Print Brief Details of a Point Pattern Dataset | |
| rmh.ppm | Simulate from a Fitted Point Process Model | |
| raster.x | Cartesian Coordinates for a Pixel Raster | |
| rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
| DiggleGratton | Diggle-Gratton model | |
| Jcross | Multitype J Function (i-to-j) | |
| StraussHard | The Strauss / Hard Core Point Process Model | |
| Gmulti | Marked Nearest Neighbour Distance Function | |
| bdist.points | Distance to Boundary of Window | |
| Kcross.inhom | Inhomogeneous Cross K Function | |
| PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
| is.marked | Test Whether Marks Are Present | |
| crossing.psp | Crossing Points of Two Line Segment Patterns | |
| spatstat | The Spatstat Package | |
| Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
| cut.im | Convert Pixel Image from Numeric to Factor | |
| affine.ppp | Apply Affine Transformation To Point Pattern | |
| as.rectangle | Window Frame | |
| LennardJones | The Lennard-Jones Potential | |
| distmap.psp | Distance Map of Line Segment Pattern | |
| dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
| bdist.pixels | Distance to Boundary of Window | |
| angles.psp | Orientation Angles of Line Segments | |
| distmap | Distance Map | |
| gridweights | Compute Quadrature Weights Based on Grid Counts | |
| hist.im | Histogram of Pixel Values in an Image | |
| as.owin | Convert Data To Class owin | |
| markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
| rNeymanScott | Simulate Neyman-Scott Process | |
| Iest | Estimate the I-function | |
| km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
| applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
| levelset | Level Set of a Pixel Image | |
| Kinhom | Inhomogeneous K-function | |
| MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
| letterR | Window in Shape of Letter R | |
| psp.object | Class of Line Segment Patterns | |
| pcf.fv | Pair Correlation Function obtained from K Function | |
| humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
| multiplicity.ppp | Count Multiplicity of Duplicate Points | |
| rotate | Rotate | |
| subset.fasp | Extract Subset of Function Array | |
| intersect.owin | Intersection or Union of Two Windows | |
| finpines | Pine saplings in Finland. | |
| pcf.ppp | Pair Correlation Function of Point Pattern | |
| redwood | California Redwoods Point Pattern (Ripley's Subset) | |
| corners | Corners of a rectangle | |
| append.psp | Combine Two Line Segment Patterns | |
| Strauss | The Strauss Point Process Model | |
| is.subset.owin | Determine Whether One Window is Contained In Another | |
| is.marked.ppp | Test Whether A Point Pattern is Marked | |
| rpoisline | Generate Poisson Random Line Process | |
| ord.family | Ord Interaction Process Family | |
| MultiStrauss | The Multitype Strauss Point Process Model | |
| cells | Biological Cells Point Pattern | |
| expand.owin | Expand Window By Factor | |
| Kdot | Multitype K Function (i-to-any) | |
| shift.ppp | Apply Vector Translation To Point Pattern | |
| quantile.im | Sample Quantiles of Pixel Image | |
| plot.ppm | plot a Fitted Point Process Model | |
| rSSI | Simple Sequential Inhibition | |
| Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
| rotate.owin | Rotate a Window | |
| im.object | Class of Images | |
| lansing | Lansing Woods Point Pattern | |
| density.ppp | Kernel Smoothed Intensity of Point Pattern | |
| crossdist.ppp | Pairwise distances between two different point patterns | |
| japanesepines | Japanese Pines Point Pattern | |
| gridcentres | Rectangular grid of points | |
| is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
| print.im | Print Brief Details of an Image | |
| rescue.rectangle | Convert Window Back To Rectangle | |
| plot.ppp | plot a Spatial Point Pattern | |
| plot.psp | plot a Spatial Line Segment Pattern | |
| plot.splitppp | Plot a List of Point Patterns | |
| subset.im | Extract Subset of Image | |
| rpoispp | Generate Poisson Point Pattern | |
| pairdist.default | Pairwise distances | |
| owin.object | Class owin | |
| rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
| shift | Apply Vector Translation | |
| spokes | Spokes pattern of dummy points | |
| shift.im | Apply Vector Translation To Pixel Image | |
| split.ppp | Divide Point Pattern into Sub-patterns | |
| psp | Create a Line Segment Pattern | |
| quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
| pcf | Pair Correlation Function | |
| copper | Berman-Huntington points and lines data | |
| rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
| summary.psp | Summary of a Line Segment Pattern Dataset | |
| runifpoint | Generate N Uniform Random Points | |
| rThomas | Simulate Thomas Process | |
| ppp | Create a Point Pattern | |
| vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
| rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
| print.quad | Print a Quadrature Scheme | |
| fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
| redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
| ripras | Estimate window from points alone | |
| im | Create a Pixel Image Object | |
| rMaternI | Simulate Matern Model I | |
| crossdist | Pairwise distances | |
| scanpp | Read Point Pattern From Data File | |
| union.quad | Union of Data and Dummy Points | |
| unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
| demopat | Artificial Data Point Pattern | |
| subset.psp | Extract Subset of Line Segment Pattern | |
| print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
| spruces | Spruces Point Pattern | |
| pairdist.psp | Pairwise distances between line segments | |
| solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
| quadratcount | Quadrat counting for a point pattern | |
| rshift.psp | Randomly Shift a Line Segment Pattern | |
| rcell | Simulate Baddeley-Silverman Cell Process | |
| plot.fasp | Plot a Function Array | |
| residuals.ppm | Residuals for Fitted Point Process Model | |
| eem | Exponential Energy Marks | |
| swedishpines | Swedish Pines Point Pattern | |
| summary.ppp | Summary of a Point Pattern Dataset | |
| rotate.psp | Rotate a Line Segment Pattern | |
| summary.quad | Summarizing a Quadrature Scheme | |
| spatstat.options | Internal Options in Spatstat Package | |
| update.ppm | Update a Fitted Point Process Model | |
| rsyst | Systematic random point pattern | |
| summary.im | Summarizing a Pixel Image | |
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Details
| Date | 26 May 2006 |
| License | GPL version 2 or newer |
| URL | http://www.spatstat.org |
| Packaged | Fri May 26 12:14:51 2006; adrian |
| depends | base (>= 2.2.0) , mgcv , R (>= 2.2.0) |
| suggests | sm |
| Contributors | Rolf Turner, Adrian Baddeley |
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