spatstat v1.14-4
0
Monthly downloads
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 | |
| AreaInter | The Area Interaction Point Process Model | |
| as.mask | Pixel Image Approximation of a Window | |
| matchingdist | Distance for a Point Pattern Matching | |
| chorley | Chorley-Ribble Cancer Data | |
| ppp | Create a Point Pattern | |
| plot.kppm | Plot a fitted cluster point process | |
| OrdThresh | Ord's Interaction model | |
| eval.hyper | Evaluate an Expression in Each Row of a Hyperframe | |
| murchison | Murchison gold deposits | |
| Saturated | Saturated Pairwise Interaction model | |
| marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern | |
| areadiff | Difference of Disc Areas | |
| Gest | Nearest Neighbour Distance Function G | |
| quantile.im | Sample Quantiles of Pixel Image | |
| as.rectangle | Window Frame | |
| rMatClust | Simulate Matern Cluster Process | |
| Kinhom | Inhomogeneous K-function | |
| predict.ppm | Prediction from a Fitted Point Process Model | |
| compatible.fv | Test Whether Two Function Objects Are Compatible | |
| demopat | Artificial Data Point Pattern | |
| persp.im | Perspective Plot of Pixel Image | |
| copper | Berman-Huntington points and lines data | |
| pairwise.family | Pairwise Interaction Process Family | |
| rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
| rescale.im | Convert Pixel Image to Another Unit of Length | |
| adaptive.density | Intensity Estimate of Point Pattern Using Tessellation | |
| distmap.psp | Distance Map of Line Segment Pattern | |
| applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
| Kmeasure | Reduced Second Moment Measure | |
| effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model | |
| psp.object | Class of Line Segment Patterns | |
| MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
| km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
| density.ppp | Kernel Smoothed Intensity of Point Pattern | |
| lengths.psp | Lengths of Line Segments | |
| density.psp | Kernel Smoothing of Line Segment Pattern | |
| is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
| Jest | Estimate the J-function | |
| affine | Apply Affine Transformation | |
| by.ppp | Apply a Function to a Point Pattern Broken Down by Factor | |
| owin.object | Class owin | |
| as.im | Convert to Pixel Image | |
| Poisson | Poisson Point Process Model | |
| Linhom | L-function | |
| StraussHard | The Strauss / Hard Core Point Process Model | |
| clickpoly | Interactively Define a Polygon | |
| cut.im | Convert Pixel Image from Numeric to Factor | |
| bei | Tropical rain forest trees | |
| Kmulti | Marked K-Function | |
| multiplicity.ppp | Count Multiplicity of Duplicate Points | |
| anova.ppm | ANOVA for Fitted Point Process Models | |
| with.fv | Evaluate an Expression in a Function Table | |
| letterR | Window in Shape of Letter R | |
| rlabel | Random Re-Labelling of Point Pattern | |
| Softcore | The Soft Core Point Process Model | |
| nbfires | Point Patterns of New Brunswick Forest Fires | |
| allstats | Calculate four standard summary functions of a point pattern. | |
| Kest | K-function | |
| rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |
| affine.ppp | Apply Affine Transformation To Point Pattern | |
| ants | Harkness-Isham ants' nests data | |
| print.im | Print Brief Details of an Image | |
| blur | Apply Gaussian Blur to a Pixel Image | |
| erode.owin | Erode a Window | |
| Kest.fft | K-function using FFT | |
| distmap.owin | Distance Map of Window | |
| as.ppp | Convert Data To Class ppp | |
| crossdist | Pairwise distances | |
| Geyer | Geyer's Saturation Point Process Model | |
| fasp.object | Function Arrays for Spatial Patterns | |
| anemones | Beadlet Anemones Data | |
| cut.ppp | Classify Points in a Point Pattern | |
| gridcentres | Rectangular grid of points | |
| Kcross.inhom | Inhomogeneous Cross K Function | |
| spatstat-internal | Internal spatstat functions | |
| diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
| as.matrix.im | Convert Pixel Image to Matrix | |
| plot.ppp | plot a Spatial Point Pattern | |
| bdist.pixels | Distance to Boundary of Window | |
| finpines | Pine saplings in Finland. | |
| convexhull.xy | Convex Hull of Points | |
| dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
| delaunay | Delaunay Triangulation of Point Pattern | |
| discretise | Safely Convert Point Pattern Window to Binary Mask | |
| quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
| dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
| is.marked.ppp | Test Whether A Point Pattern is Marked | |
| distmap.ppp | Distance Map of Point Pattern | |
| ord.family | Ord Interaction Process Family | |
| print.ppm | Print a Fitted Point Process Model | |
| is.owin | Test Whether An Object Is A Window | |
| rescale | Convert dataset to another unit of length | |
| hist.im | Histogram of Pixel Values in an Image | |
| crossing.psp | Crossing Points of Two Line Segment Patterns | |
| corners | Corners of a rectangle | |
| reduced.sample | Reduced Sample Estimator using Histogram Data | |
| residuals.ppm | Residuals for Fitted Point Process Model | |
| plot.fasp | Plot a Function Array | |
| concatxy | Concatenate x,y Coordinate Vectors | |
| diameter | Diameter of a Window | |
| Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
| plot.psp | plot a Spatial Line Segment Pattern | |
| Lcross | Multitype L-function (cross-type) | |
| endpoints.psp | Endpoints of Line Segment Pattern | |
| PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
| model.matrix.ppm | Extract Design Matrix from Point Process Model | |
| pcf | Pair Correlation Function | |
| quadrats | Divide Region into Quadrats | |
| default.dummy | Generate a Default Pattern of Dummy Points | |
| ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
| rGaussPoisson | Simulate Gauss-Poisson Process | |
| print.ppp | Print Brief Details of a Point Pattern Dataset | |
| Fest | Estimate the empty space function F | |
| pppdist | Distance Between Two Point Patterns | |
| pcfcross | Multitype pair correlation function | |
| pairsat.family | Saturated Pairwise Interaction Point Process Family | |
| rsyst | Simulate systematic random point pattern | |
| is.im | Test Whether An Object Is A Pixel Image | |
| clickppp | Interactively Add Points | |
| Kdot | Multitype K Function (i-to-any) | |
| lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| crossdist.default | Pairwise distances between two different sets of points | |
| SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model | |
| rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |
| rNeymanScott | Simulate Neyman-Scott Process | |
| levelset | Level Set of a Pixel Image | |
| hyperframe | Hyper Data Frame | |
| fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |
| Gmulti | Marked Nearest Neighbour Distance Function | |
| envelope | Simulation envelopes of summary function | |
| dirichlet | Dirichlet Tessellation of Point Pattern | |
| Jmulti | Marked J Function | |
| is.marked | Test Whether Marks Are Present | |
| disc | Circular Window | |
| identify.ppp | Identify Points in a Point Pattern | |
| interp.im | Interpolate a Pixel Image | |
| longleaf | Longleaf Pines Point Pattern | |
| quadratcount | Quadrat counting for a point pattern | |
| markcorr | Mark Correlation Function | |
| Ldot | Multitype L-function (i-to-any) | |
| midpoints.psp | Midpoints of Line Segment Pattern | |
| as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |
| quadratresample | Resample a Point Pattern by Resampling Quadrats | |
| rshift.ppp | Randomly Shift a Point Pattern | |
| DiggleGratton | Diggle-Gratton model | |
| nearest.raster.point | Find Pixel Nearest to a Given Point | |
| rpoispp | Generate Poisson Point Pattern | |
| by.im | Apply Function to Image Broken Down by Factor | |
| Lest | L-function | |
| Kcross | Multitype K Function (Cross-type) | |
| is.subset.owin | Determine Whether One Window is Contained In Another | |
| Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
| duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
| angles.psp | Orientation Angles of Line Segments | |
| pcf.fv | Pair Correlation Function obtained from K Function | |
| nnwhich | Nearest neighbour | |
| data.ppm | Extract Original Data from a Fitted Point Process Model | |
| lurking | Lurking variable plot | |
| bdist.points | Distance to Boundary of Window | |
| model.images | Compute Images of Constructed Covariates | |
| shift | Apply Vector Translation | |
| split.im | Divide Image Into Sub-images | |
| eval.fasp | Evaluate Expression Involving Function Arrays | |
| cells | Biological Cells Point Pattern | |
| summary.psp | Summary of a Line Segment Pattern Dataset | |
| runifdisc | Generate N Uniform Random Points in a Disc | |
| crossdist.ppp | Pairwise distances between two different point patterns | |
| MultiStrauss | The Multitype Strauss Point Process Model | |
| ponderosa | Ponderosa Pine Tree Point Pattern | |
| logLik.ppm | Log Likelihood for Poisson Point Process Model | |
| Pairwise | Generic Pairwise Interaction model | |
| dilate.owin | Dilate a Window | |
| Ord | Generic Ord Interaction model | |
| eval.fv | Evaluate Expression Involving Functions | |
| affine.psp | Apply Affine Transformation To Line Segment Pattern | |
| rotate | Rotate | |
| intersect.owin | Intersection or Union of Two Windows | |
| Strauss | The Strauss Point Process Model | |
| pppmatching.object | Class of Point Matchings | |
| rmpoispp | Generate Multitype Poisson Point Pattern | |
| subset.im | Extract Subset of Image | |
| subset.psp | Extract Subset of Line Segment Pattern | |
| subset.splitppp | Extract or Replace Sub-Patterns | |
| rescale.ppp | Convert Point Pattern to Another Unit of Length | |
| nncorr | Nearest-Neighbour Correlation of Marked Point Pattern | |
| im.object | Class of Images | |
| fv.object | Data Frames of Function Values | |
| plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
| summary.splitppp | Summary of a Split Point Pattern | |
| clarkevans | Clark and Evans Aggregation Index | |
| solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
| bramblecanes | Hutchings' Bramble Canes data | |
| hamster | Aherne's hamster tumour data | |
| quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
| nndist.psp | Nearest neighbour distances between line segments | |
| Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
| is.ppp | Test Whether An Object Is A Point Pattern | |
| pixelquad | Quadrature Scheme Based on Pixel Grid | |
| plot.im | Plot a Pixel Image | |
| area.owin | Area of a Window | |
| plot.splitppp | Plot a List of Point Patterns | |
| unmark | Remove Marks from a Marked Point Pattern | |
| is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
| harmonic | Basis for Harmonic Functions | |
| Jdot | Multitype J Function (i-to-any) | |
| quad.object | Class of Quadrature Schemes | |
| is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
| as.owin | Convert Data To Class owin | |
| progressreport | Print Progress Reports | |
| lansing | Lansing Woods Point Pattern | |
| BadGey | Hybrid Geyer Point Process Model | |
| rshift.psp | Randomly Shift a Line Segment Pattern | |
| rotate.ppp | Rotate a Point Pattern | |
| bounding.box | Bounding Box of a Window or Point Pattern | |
| ppm | Fit Point Process Model to Data | |
| distmap | Distance Map | |
| ripras | Estimate window from points alone | |
| rjitter | Random Perturbation of a Point Pattern | |
| inside.owin | Test Whether Points Are Inside A Window | |
| gpc2owin | Convert Polygonal Region into Different Format | |
| vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
| spatstat | The Spatstat Package | |
| expand.owin | Expand Window By Factor | |
| nncross | Nearest Neighbour in Another Point Pattern | |
| localK | Neighbourhood density function | |
| rSSI | Simulate Simple Sequential Inhibition | |
| alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern | |
| vertices | Vertices of a Window | |
| Iest | Estimate the I-function | |
| mean.im | Mean, Median and Range of Pixel Values in an Image | |
| Jcross | Multitype J Function (i-to-j) | |
| LennardJones | The Lennard-Jones Potential | |
| nztrees | New Zealand Trees Point Pattern | |
| nndist | Nearest neighbour distances | |
| rmh.ppm | Simulate from a Fitted Point Process Model | |
| append.psp | Combine Two Line Segment Patterns | |
| betacells | Beta Ganglion Cells in Cat Retina | |
| incircle | Find Largest Circle Inside Window | |
| bounding.box.xy | Convex Hull of Points | |
| rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
| as.psp | Convert Data To Class psp | |
| density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
| rmpoint | Generate N Random Multitype Points | |
| ppp.object | Class of Point Patterns | |
| eroded.areas | Areas of Morphological Erosions | |
| print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
| markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
| amacrine | Hughes' Amacrine Cell Data | |
| centroid.owin | Centroid of a window | |
| rpoint | Generate N Random Points | |
| compatible.fasp | Test Whether Two Function Arrays Are Compatible | |
| compatible.im | Test Whether Two Pixel Images Are Compatible | |
| japanesepines | Japanese Pines Point Pattern | |
| contour.im | Contour plot of pixel image | |
| rthin | Random Thinning | |
| pcf.ppp | Pair Correlation Function of Point Pattern | |
| reach | Interaction Distance of a Point Process | |
| plot.listof | Plot a List of Things | |
| coef.ppm | Coefficients of Fitted Point Process Model | |
| rpoisline | Generate Poisson Random Line Process | |
| ewcdf | Weighted Empirical Cumulative Distribution Function | |
| rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
| redwood | California Redwoods Point Pattern (Ripley's Subset) | |
| shift.psp | Apply Vector Translation To Line Segment Pattern | |
| [.tess | Extract or Replace Subset of Tessellation | |
| setcov | Set Covariance of a Window | |
| rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
| plot.tess | Plot a tessellation | |
| selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
| eval.im | Evaluate Expression Involving Pixel Images | |
| pairdist | Pairwise distances | |
| owin | Create a Window | |
| matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
| print.quad | Print a Quadrature Scheme | |
| pairdist.psp | Pairwise distances between line segments | |
| superimpose | Superimpose Several Point Patterns | |
| plot.owin | Plot a Spatial Window | |
| is.multitype | Test whether Object is Multitype | |
| rMaternII | Simulate Matern Model II | |
| spruces | Spruces Point Pattern | |
| rotate.owin | Rotate a Window | |
| shift.im | Apply Vector Translation To Pixel Image | |
| redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
| profilepl | Profile Maximum Pseudolikelihood | |
| [.quad | Subset of Quadrature Scheme | |
| setmarks | Set or Reset the Marks in a Point Pattern | |
| pppmatching | Create a Point Matching | |
| rThomas | Simulate Thomas Process | |
| fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
| inforder.family | Infinite Order Interaction Family | |
| rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |
| pairdist.default | Pairwise distances | |
| pcf.fasp | Pair Correlation Function obtained from array of K functions | |
| trim.rectangle | Cut margins from rectangle | |
| kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
| rstrat | Simulate Stratified Random Point Pattern | |
| rescue.rectangle | Convert Window Back To Rectangle | |
| rescale.owin | Convert Window to Another Unit of Length | |
| plot.ppm | plot a Fitted Point Process Model | |
| runifpoint | Generate N Uniform Random Points | |
| mincontrast | Method of Minimum Contrast | |
| plot.quad | plot a Spatial Quadrature Scheme | |
| eem | Exponential Energy Marks | |
| square | Square Window | |
| affine.owin | Apply Affine Transformation To Window | |
| psp | Create a Line Segment Pattern | |
| shift.owin | Apply Vector Translation To Window | |
| print.owin | Print Brief Details of a Spatial Window | |
| gridweights | Compute Quadrature Weights Based on Grid Counts | |
| is.marked.ppm | Test Whether A Point Process Model is Marked | |
| spatstat.options | Internal Options in Spatstat Package | |
| kppm | Fit cluster point process model | |
| update.kppm | Update a Fitted Cluster Point Process Model | |
| summary.owin | Summary of a Spatial Window | |
| subset.fv | Extract Subset of Function Values | |
| im | Create a Pixel Image Object | |
| suffstat | Sufficient Statistic of Point Process Model | |
| summary.ppm | Summarizing a Fitted Point Process Model | |
| rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
| complement.owin | Take Complement of a Window | |
| update.ppm | Update a Fitted Point Process Model | |
| unitname | Name for Unit of Length | |
| crossdist.psp | Pairwise distances between two different line segment patterns | |
| urkiola | Urkiola Woods Point Pattern | |
| plot.fv | Plot Function Valuesn | |
| split.ppp | Divide Point Pattern into Sub-patterns | |
| subset.listof | Extract or Replace Subset of a List of Things | |
| spatstat-deprecated | Deprecated spatstat functions | |
| rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |
| ppm.object | Class of Fitted Point Process Models | |
| rlinegrid | Generate grid of parallel lines with random displacement | |
| rMaternI | Simulate Matern Model I | |
| summary.listof | Summary of a List of Things | |
| subset.fasp | Extract Subset of Function Array | |
| shift.ppp | Apply Vector Translation To Point Pattern | |
| swedishpines | Swedish Pines Point Pattern | |
| rStrauss | Perfect Simulation of the Strauss Process | |
| raster.x | Cartesian Coordinates for a Pixel Raster | |
| smooth.ppp | Spatial smoothing of observations at irregular points | |
| humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
| unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
| union.quad | Union of Data and Dummy Points | |
| residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
| kstest.ppm | Kolmogorov-Smirnov Test for Point Process Model | |
| pairdist.ppp | Pairwise distances | |
| rotate.psp | Rotate a Line Segment Pattern | |
| stieltjes | Compute Integral of Function Against Cumulative Distribution | |
| predict.kppm | Prediction from a Fitted Cluster Point Process Model | |
| qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
| plot.hyperframe | Plot Entries in a Hyperframe | |
| simulate.kppm | Simulate a fitted cluster point process model. | |
| summary.ppp | Summary of a Point Pattern Dataset | |
| spokes | Spokes pattern of dummy points | |
| quadrat.test | Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
| tess | Create a Tessellation | |
| rcell | Simulate Baddeley-Silverman Cell Process | |
| rshift | Random Shift | |
| scanpp | Read Point Pattern From Data File | |
| rshift.splitppp | Randomly Shift a List of Point Patterns | |
| simdat | Simulated Point Pattern | |
| subset.ppp | Extract or Replace Subset of Point Pattern | |
| summary.im | Summarizing a Pixel Image | |
| thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
| subsetget.im | Reset Values in Subset of Image | |
| tiles | Extract List of Tiles in a Tessellation | |
| summary.quad | Summarizing a Quadrature Scheme | |
| No Results! | ||
Last month downloads
Details
| Date | 16 October 2008 |
| License | GPL (>= 2) |
| URL | http://www.spatstat.org |
| Packaged | Fri Oct 17 12:12:15 2008; adrian |
| depends | base (>= 2.6.0) , deldir (>= 0.0-7) , gpclib , graphics , mgcv , R (>= 2.6.0) , stats , utils |
| suggests | sm |
| Contributors | Rolf Turner, Adrian Baddeley |
Include our badge in your README
[](http://www.rdocumentation.org/packages/spatstat)