spatstat v1.9-3
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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 | |
| affine.owin | Apply Affine Transformation To Window | |
| append.psp | Combine Two Line Segment Patterns | |
| Jdot | Multitype J Function (i-to-any) | |
| compatible.fv | Test Whether Two Function Objects Are Compatible | |
| as.mask | Pixel Image Approximation of a Window | |
| eval.im | Evaluate Expression Involving Pixel Images | |
| crossing.psp | Crossing Points of Two Line Segment Patterns | |
| humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
| letterR | Window in Shape of Letter R | |
| midpoints.psp | Midpoints of Line Segment Pattern | |
| cut.ppp | Convert Point Pattern Marks from Numeric to Factor | |
| eem | Exponential Energy Marks | |
| Kinhom | Inhomogeneous K-function | |
| im.object | Class of Images | |
| pairwise.family | Pairwise Interaction Process Family | |
| bdist.pixels | Distance to Boundary of Window | |
| nztrees | New Zealand Trees Point Pattern | |
| print.im | Print Brief Details of an Image | |
| Iest | Estimate the I-function | |
| area.owin | Area of a Window | |
| lengths.psp | Lengths of Line Segments | |
| rpoispp | Generate Poisson Point Pattern | |
| pairdist.ppp | Pairwise distances | |
| pcf.fv | Pair Correlation Function obtained from K Function | |
| shift.owin | Apply Vector Translation To Window | |
| crossdist | Pairwise distances | |
| pairsat.family | Saturated Pairwise Interaction Point Process Family | |
| swedishpines | Swedish Pines Point Pattern | |
| markcorr | Mark Correlation Function | |
| rsyst | Systematic random point pattern | |
| psp.object | Class of Line Segment Patterns | |
| quantile.im | Sample Quantiles of Pixel Image | |
| rmpoispp | Generate Multitype Poisson Point Pattern | |
| residuals.ppm | Residuals for Fitted Point Process Model | |
| rlabel | Random Re-Labelling of Point Pattern | |
| Strauss | The Strauss Point Process Model | |
| Kest | K-function | |
| rthin | Random Thinning | |
| split.ppp | Divide Point Pattern into Sub-patterns | |
| shift.ppp | Apply Vector Translation To Point Pattern | |
| angles.psp | Orientation Angles of Line Segments | |
| shift.im | Apply Vector Translation To Pixel Image | |
| Saturated | Saturated Pairwise Interaction model | |
| MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
| applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
| OrdThresh | Ord's Interaction model | |
| rpoisline | Generate Poisson Random Line Process | |
| default.dummy | Generate a Default Pattern of Dummy Points | |
| Softcore | The Soft Core Point Process Model | |
| inside.owin | Test Whether Points Are Inside A Window | |
| is.ppp | Test Whether An Object Is A Point Pattern | |
| bdist.points | Distance to Boundary of Window | |
| pairdist.psp | Pairwise distances between line segments | |
| longleaf | Longleaf Pines Point Pattern | |
| crossdist.default | Pairwise distances between two different sets of points | |
| profilepl | Profile Maximum Pseudolikelihood | |
| subset.fv | Extract Subset of Function Values | |
| data.ppm | Extract Original Data from a Fitted Point Process Model | |
| solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
| summary.psp | Summary of a Line Segment Pattern Dataset | |
| spatstat-deprecated | Deprecated spatstat functions | |
| distmap.psp | Distance Map of Line Segment Pattern | |
| summary.im | Summarizing a Pixel Image | |
| multiplicity.ppp | Count Multiplicity of Duplicate Points | |
| Geyer | Geyer's Saturation Point Process Model | |
| as.matrix.im | Convert Pixel Image to Matrix | |
| nncorr | Nearest-Neighbour Correlation of Marked Point Pattern | |
| psp | Create a Line Segment Pattern | |
| PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
| quadratcount | Quadrat counting for a point pattern | |
| Poisson | Poisson Point Process Model | |
| pcf.ppp | Pair Correlation Function of Point Pattern | |
| MultiStrauss | The Multitype Strauss Point Process Model | |
| plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
| quadrat.test | Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
| quad.object | Class of Quadrature Schemes | |
| print.ppp | Print Brief Details of a Point Pattern Dataset | |
| affine | Apply Affine Transformation | |
| complement.owin | Take Complement of a Window | |
| as.psp | Convert Data To Class psp | |
| as.ppp | Convert Data To Class ppp | |
| Kdot | Multitype K Function (i-to-any) | |
| distmap | Distance Map | |
| rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
| centroid.owin | Centroid of a window | |
| bramblecanes | Hutchings' Bramble Canes data | |
| rNeymanScott | Simulate Neyman-Scott Process | |
| spruces | Spruces Point Pattern | |
| diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
| diameter | Diameter of a Window Frame | |
| expand.owin | Expand Window By Factor | |
| hamster | Aherne's hamster tumour data | |
| harmonic | Basis for Harmonic Functions | |
| owin | Create a Window | |
| rescue.rectangle | Convert Window Back To Rectangle | |
| endpoints.psp | Endpoints of Line Segment Pattern | |
| nndist | Nearest neighbour distances | |
| reach | Interaction Distance of a Point Process | |
| Kest.fft | K-function using FFT | |
| anova.ppm | ANOVA for Fitted Point Process Models | |
| pcf | Pair Correlation Function | |
| plot.fv | Plot Function Valuesn | |
| subset.fasp | Extract Subset of Function Array | |
| eroded.areas | Areas of Morphological Erosions | |
| rThomas | Simulate Thomas Process | |
| qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
| residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
| is.im | Test Whether An Object Is A Pixel Image | |
| unmark | Remove Marks from a Marked Point Pattern | |
| Gmulti | Marked Nearest Neighbour Distance Function | |
| unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
| affine.psp | Apply Affine Transformation To Line Segment Pattern | |
| corners | Corners of a rectangle | |
| plot.owin | Plot a Spatial Window | |
| plot.splitppp | Plot a List of Point Patterns | |
| crossdist.ppp | Pairwise distances between two different point patterns | |
| rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
| plot.ppm | plot a Fitted Point Process Model | |
| ppp | Create a Point Pattern | |
| rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
| superimpose | Superimpose Several Point Patterns | |
| scanpp | Read Point Pattern From Data File | |
| nnwhich | Nearest neighbour | |
| Jmulti | Marked J Function | |
| as.owin | Convert Data To Class owin | |
| simdat | Simulated Point Pattern | |
| suffstat | Sufficient Statistic of Point Process Model | |
| demopat | Artificial Data Point Pattern | |
| Gest | Nearest Neighbour Distance Function G | |
| betacells | Beta Ganglion Cells in Cat Retina | |
| allstats | Calculate four standard summary functions of a point pattern. | |
| concatxy | Concatenate x,y Coordinate Vectors | |
| finpines | Pine saplings in Finland. | |
| dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
| distmap.ppp | Distance Map of Point Pattern | |
| is.owin | Test Whether An Object Is A Window | |
| fv.object | Data Frames of Function Values | |
| hist.im | Histogram of Pixel Values in an Image | |
| fasp.object | Function Arrays for Spatial Patterns | |
| is.marked | Test Whether Marks Are Present | |
| gridweights | Compute Quadrature Weights Based on Grid Counts | |
| Jest | Estimate the J-function | |
| DiggleGratton | Diggle-Gratton model | |
| print.ppm | Print a Fitted Point Process Model | |
| envelope | Simulation envelopes of summary function | |
| rshift | Random Shift | |
| intersect.owin | Intersection or Union of Two Windows | |
| kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
| runifpoint | Generate N Uniform Random Points | |
| plot.im | Plot a Pixel Image | |
| summary.ppp | Summary of a Point Pattern Dataset | |
| mincontrast | Method of Minimum Contrast | |
| rcell | Simulate Baddeley-Silverman Cell Process | |
| ppp.object | Class of Point Patterns | |
| rshift.splitppp | Randomly Shift a List of Point Patterns | |
| erode.owin | Erode a Window | |
| selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
| summary.owin | Summary of a Spatial Window | |
| shift | Apply Vector Translation | |
| plot.ppp | plot a Spatial Point Pattern | |
| raster.x | Cartesian Coordinates for a Pixel Raster | |
| quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
| rSSI | Simple Sequential Inhibition | |
| shift.psp | Apply Vector Translation To Line Segment Pattern | |
| setmarks | Set or Reset the Marks in a Point Pattern | |
| union.quad | Union of Data and Dummy Points | |
| rmh.ppm | Simulate from a Fitted Point Process Model | |
| Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
| Kcross.inhom | Inhomogeneous Cross K Function | |
| vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
| bounding.box | Bounding Box of a Window | |
| Kmeasure | Reduced Second Moment Measure | |
| rotate.ppp | Rotate a Point Pattern | |
| spatstat.options | Internal Options in Spatstat Package | |
| rshift.psp | Randomly Shift a Line Segment Pattern | |
| summary.ppm | Summarizing a Fitted Point Process Model | |
| dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
| eval.fv | Evaluate Expression Involving Functions | |
| duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
| pairdist.default | Pairwise distances | |
| plot.psp | plot a Spatial Line Segment Pattern | |
| print.owin | Print Brief Details of a Spatial Window | |
| print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
| rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
| rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
| rotate | Rotate | |
| Kcross | Multitype K Function (Cross-type) | |
| copper | Berman-Huntington points and lines data | |
| density.ppp | Kernel Smoothed Intensity of Point Pattern | |
| is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
| japanesepines | Japanese Pines Point Pattern | |
| km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
| nearest.raster.point | Find Pixel Nearest to a Given Point | |
| plot.fasp | Plot a Function Array | |
| lurking | Lurking variable plot | |
| print.quad | Print a Quadrature Scheme | |
| predict.ppm | Prediction from a Fitted Point Process Model | |
| ants | Harkness-Isham ants' nests data | |
| compatible.im | Test Whether Two Pixel Images Are Compatible | |
| identify.ppp | Identify Points in a Point Pattern | |
| lansing | Lansing Woods Point Pattern | |
| quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
| ripras | Estimate window from points alone | |
| rshift.ppp | Randomly Shift a Point Pattern | |
| rstrat | Stratified random point pattern | |
| summary.quad | Summarizing a Quadrature Scheme | |
| pairdist | Pairwise distances | |
| levelset | Level Set of a Pixel Image | |
| redwood | California Redwoods Point Pattern (Ripley's Subset) | |
| owin.object | Class owin | |
| square | Square Window | |
| rotate.psp | Rotate a Line Segment Pattern | |
| subset.ppp | Extract or Replace Subset of Point Pattern | |
| thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
| alltypes | Calculate Statistic for All Types in a Multitype Point Pattern | |
| StraussHard | The Strauss / Hard Core Point Process Model | |
| amacrine | Hughes' Amacrine Cell Data | |
| density.psp | Kernel Smoothing of Line Segment Pattern | |
| as.rectangle | Window Frame | |
| coef.ppm | Coefficients of Fitted Point Process Model | |
| spatstat-internal | Internal spatstat functions | |
| matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
| distmap.owin | Distance Map of Window | |
| ord.family | Ord Interaction Process Family | |
| Fest | Estimate the empty space function F | |
| Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
| setcov | Set Covariance of a Window | |
| Kmulti | Marked K-Function | |
| Pairwise | Generic Pairwise Interaction model | |
| chorley | Chorley-Ribble Cancer Data | |
| as.im | Convert to Pixel Image | |
| cells | Biological Cells Point Pattern | |
| Jcross | Multitype J Function (i-to-j) | |
| Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
| LennardJones | The Lennard-Jones Potential | |
| crossdist.psp | Pairwise distances between two different line segment patterns | |
| redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
| is.marked.ppp | Test Whether A Point Pattern is Marked | |
| mean.im | Mean Pixel Value in an Image | |
| is.marked.ppm | Test Whether A Point Process Model is Marked | |
| spatstat | The Spatstat Package | |
| fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
| markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
| im | Create a Pixel Image Object | |
| gridcentres | Rectangular grid of points | |
| rMaternII | Simulate Matern Model II | |
| is.subset.owin | Determine Whether One Window is Contained In Another | |
| plot.quad | plot a Spatial Quadrature Scheme | |
| reduced.sample | Reduced Sample Estimator using Histogram Data | |
| rotate.owin | Rotate a Window | |
| ppm | Fit Point Process Model to Data | |
| ppm.object | Class of Fitted Point Process Models | |
| rmpoint | Generate N Random Multitype Points | |
| spokes | Spokes pattern of dummy points | |
| rpoint | Generate N Random Points | |
| rMatClust | Simulate Matern Cluster Process | |
| subset.psp | Extract Subset of Line Segment Pattern | |
| rMaternI | Simulate Matern Model I | |
| dilate.owin | Dilate a Window | |
| lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| pcf.fasp | Pair Correlation Function obtained from array of K functions | |
| affine.ppp | Apply Affine Transformation To Point Pattern | |
| persp.im | Perspective Plot of Pixel Image | |
| ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
| subset.im | Extract Subset of Image | |
| Ord | Generic Ord Interaction model | |
| cut.im | Convert Pixel Image from Numeric to Factor | |
| update.ppm | Update a Fitted Point Process Model | |
| No Results! | ||
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Details
| Date | 20 June 2006 |
| License | GPL version 2 or newer |
| URL | http://www.spatstat.org |
| Packaged | Wed Jun 21 12:37:31 2006; adrian |
| depends | base (>= 2.2.0) , mgcv , R (>= 2.2.0) |
| suggests | sm |
| Contributors | Rolf Turner, Adrian Baddeley |
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