spatstat v1.9-6
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 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 | |
| Kcross.inhom | Inhomogeneous Cross K Function | |
| Iest | Estimate the I-function | |
| as.matrix.im | Convert Pixel Image to Matrix | |
| Kest | K-function | |
| gridcentres | Rectangular grid of points | |
| corners | Corners of a rectangle | |
| PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
| betacells | Beta Ganglion Cells in Cat Retina | |
| as.ppp | Convert Data To Class ppp | |
| Pairwise | Generic Pairwise Interaction model | |
| density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
| dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
| as.owin | Convert Data To Class owin | |
| Gmulti | Marked Nearest Neighbour Distance Function | |
| longleaf | Longleaf Pines Point Pattern | |
| alltypes | Calculate Statistic for All Types in a Multitype Point Pattern | |
| fv.object | Data Frames of Function Values | |
| LennardJones | The Lennard-Jones Potential | |
| inside.owin | Test Whether Points Are Inside A Window | |
| distmap.ppp | Distance Map of Point Pattern | |
| nnwhich | Nearest neighbour | |
| MultiStrauss | The Multitype Strauss Point Process Model | |
| Strauss | The Strauss Point Process Model | |
| km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
| applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
| amacrine | Hughes' Amacrine Cell Data | |
| distmap.owin | Distance Map of Window | |
| Poisson | Poisson Point Process Model | |
| plot.ppm | plot a Fitted Point Process Model | |
| rshift.psp | Randomly Shift a Line Segment Pattern | |
| plot.splitppp | Plot a List of Point Patterns | |
| summary.ppp | Summary of a Point Pattern Dataset | |
| is.ppp | Test Whether An Object Is A Point Pattern | |
| bramblecanes | Hutchings' Bramble Canes data | |
| dilate.owin | Dilate a Window | |
| bounding.box | Bounding Box of a Window | |
| ants | Harkness-Isham ants' nests data | |
| rMatClust | Simulate Matern Cluster Process | |
| density.ppp | Kernel Smoothed Intensity of Point Pattern | |
| nndist | Nearest neighbour distances | |
| intersect.owin | Intersection or Union of Two Windows | |
| cells | Biological Cells Point Pattern | |
| ppp.object | Class of Point Patterns | |
| fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
| dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
| pppdist | Optimal Match Between Two Point Patterns | |
| humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
| rNeymanScott | Simulate Neyman-Scott Process | |
| reduced.sample | Reduced Sample Estimator using Histogram Data | |
| runifpoint | Generate N Uniform Random Points | |
| quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
| rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
| letterR | Window in Shape of Letter R | |
| crossdist.ppp | Pairwise distances between two different point patterns | |
| qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
| distmap | Distance Map | |
| rStrauss | Perfect Simulation of the Strauss Process | |
| mincontrast | Method of Minimum Contrast | |
| rMaternI | Simulate Matern Model I | |
| gridweights | Compute Quadrature Weights Based on Grid Counts | |
| spatstat-deprecated | Deprecated spatstat functions | |
| quad.object | Class of Quadrature Schemes | |
| pairdist.ppp | Pairwise distances | |
| expand.owin | Expand Window By Factor | |
| rpoisline | Generate Poisson Random Line Process | |
| simdat | Simulated Point Pattern | |
| rmpoint | Generate N Random Multitype Points | |
| redwood | California Redwoods Point Pattern (Ripley's Subset) | |
| print.ppm | Print a Fitted Point Process Model | |
| rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
| quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
| summary.owin | Summary of a Spatial Window | |
| selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
| eroded.areas | Areas of Morphological Erosions | |
| rlabel | Random Re-Labelling of Point Pattern | |
| rshift | Random Shift | |
| shift.psp | Apply Vector Translation To Line Segment Pattern | |
| Jdot | Multitype J Function (i-to-any) | |
| plot.quad | plot a Spatial Quadrature Scheme | |
| append.psp | Combine Two Line Segment Patterns | |
| eval.im | Evaluate Expression Involving Pixel Images | |
| hamster | Aherne's hamster tumour data | |
| is.owin | Test Whether An Object Is A Window | |
| scanpp | Read Point Pattern From Data File | |
| complement.owin | Take Complement of a Window | |
| subset.fasp | Extract Subset of Function Array | |
| pairsat.family | Saturated Pairwise Interaction Point Process Family | |
| nncorr | Nearest-Neighbour Correlation of Marked Point Pattern | |
| residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
| pcf | Pair Correlation Function | |
| split.ppp | Divide Point Pattern into Sub-patterns | |
| rmpoispp | Generate Multitype Poisson Point Pattern | |
| rmh.ppm | Simulate from a Fitted Point Process Model | |
| rotate | Rotate | |
| pcf.fasp | Pair Correlation Function obtained from array of K functions | |
| plot.im | Plot a Pixel Image | |
| plot.psp | plot a Spatial Line Segment Pattern | |
| print.owin | Print Brief Details of a Spatial Window | |
| plot.fv | Plot Function Valuesn | |
| print.quad | Print a Quadrature Scheme | |
| quadrat.test | Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
| psp.object | Class of Line Segment Patterns | |
| psp | Create a Line Segment Pattern | |
| ppm.object | Class of Fitted Point Process Models | |
| rescue.rectangle | Convert Window Back To Rectangle | |
| rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
| nztrees | New Zealand Trees Point Pattern | |
| subset.psp | Extract Subset of Line Segment Pattern | |
| rshift.ppp | Randomly Shift a Point Pattern | |
| Kest.fft | K-function using FFT | |
| rotate.ppp | Rotate a Point Pattern | |
| plot.listof | Plot a List of Things | |
| raster.x | Cartesian Coordinates for a Pixel Raster | |
| residuals.ppm | Residuals for Fitted Point Process Model | |
| quadratcount | Quadrat counting for a point pattern | |
| setmarks | Set or Reset the Marks in a Point Pattern | |
| Jcross | Multitype J Function (i-to-j) | |
| Saturated | Saturated Pairwise Interaction model | |
| summary.im | Summarizing a Pixel Image | |
| affine.ppp | Apply Affine Transformation To Point Pattern | |
| hist.im | Histogram of Pixel Values in an Image | |
| pcf.ppp | Pair Correlation Function of Point Pattern | |
| shift.im | Apply Vector Translation To Pixel Image | |
| Ord | Generic Ord Interaction model | |
| rpoint | Generate N Random Points | |
| pairdist | Pairwise distances | |
| angles.psp | Orientation Angles of Line Segments | |
| Kmulti | Marked K-Function | |
| anova.ppm | ANOVA for Fitted Point Process Models | |
| bei | Tropical rain forest trees | |
| is.marked.ppp | Test Whether A Point Pattern is Marked | |
| shift.ppp | Apply Vector Translation To Point Pattern | |
| superimpose | Superimpose Several Point Patterns | |
| as.mask | Pixel Image Approximation of a Window | |
| area.owin | Area of a Window | |
| as.rectangle | Window Frame | |
| diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
| distmap.psp | Distance Map of Line Segment Pattern | |
| im | Create a Pixel Image Object | |
| ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
| Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
| Gest | Nearest Neighbour Distance Function G | |
| crossdist.psp | Pairwise distances between two different line segment patterns | |
| erode.owin | Erode a Window | |
| affine.owin | Apply Affine Transformation To Window | |
| fasp.object | Function Arrays for Spatial Patterns | |
| lengths.psp | Lengths of Line Segments | |
| lurking | Lurking variable plot | |
| eval.fv | Evaluate Expression Involving Functions | |
| owin | Create a Window | |
| lansing | Lansing Woods Point Pattern | |
| square | Square Window | |
| ord.family | Ord Interaction Process Family | |
| spruces | Spruces Point Pattern | |
| pcf.fv | Pair Correlation Function obtained from K Function | |
| is.marked | Test Whether Marks Are Present | |
| solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
| plot.ppp | plot a Spatial Point Pattern | |
| rotate.psp | Rotate a Line Segment Pattern | |
| setcov | Set Covariance of a Window | |
| spokes | Spokes pattern of dummy points | |
| rsyst | Simulate systematic random point pattern | |
| shift.owin | Apply Vector Translation To Window | |
| rMaternII | Simulate Matern Model II | |
| print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
| StraussHard | The Strauss / Hard Core Point Process Model | |
| affine | Apply Affine Transformation | |
| diameter | Diameter of a Window Frame | |
| density.psp | Kernel Smoothing of Line Segment Pattern | |
| identify.ppp | Identify Points in a Point Pattern | |
| is.subset.owin | Determine Whether One Window is Contained In Another | |
| envelope | Simulation envelopes of summary function | |
| japanesepines | Japanese Pines Point Pattern | |
| lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
| quantile.im | Sample Quantiles of Pixel Image | |
| redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
| spatstat | The Spatstat Package | |
| summary.psp | Summary of a Line Segment Pattern Dataset | |
| Kdot | Multitype K Function (i-to-any) | |
| as.im | Convert to Pixel Image | |
| cut.ppp | Convert Point Pattern Marks from Numeric to Factor | |
| centroid.owin | Centroid of a window | |
| Jest | Estimate the J-function | |
| levelset | Level Set of a Pixel Image | |
| eem | Exponential Energy Marks | |
| pairdist.default | Pairwise distances | |
| coef.ppm | Coefficients of Fitted Point Process Model | |
| swedishpines | Swedish Pines Point Pattern | |
| Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
| pairwise.family | Pairwise Interaction Process Family | |
| Kmeasure | Reduced Second Moment Measure | |
| subset.fv | Extract Subset of Function Values | |
| crossing.psp | Crossing Points of Two Line Segment Patterns | |
| print.ppp | Print Brief Details of a Point Pattern Dataset | |
| chorley | Chorley-Ribble Cancer Data | |
| crossdist | Pairwise distances | |
| rshift.splitppp | Randomly Shift a List of Point Patterns | |
| subset.ppp | Extract or Replace Subset of Point Pattern | |
| nncross | Nearest Neighbour in Another Point Pattern | |
| print.im | Print Brief Details of an Image | |
| rcell | Simulate Baddeley-Silverman Cell Process | |
| Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
| Kinhom | Inhomogeneous K-function | |
| affine.psp | Apply Affine Transformation To Line Segment Pattern | |
| Softcore | The Soft Core Point Process Model | |
| concatxy | Concatenate x,y Coordinate Vectors | |
| demopat | Artificial Data Point Pattern | |
| spatstat-internal | Internal spatstat functions | |
| data.ppm | Extract Original Data from a Fitted Point Process Model | |
| shift | Apply Vector Translation | |
| rstrat | Simulate Stratified Random Point Pattern | |
| summary.quad | Summarizing a Quadrature Scheme | |
| Geyer | Geyer's Saturation Point Process Model | |
| Kcross | Multitype K Function (Cross-type) | |
| as.psp | Convert Data To Class psp | |
| contour.im | Contour plot of pixel image | |
| default.dummy | Generate a Default Pattern of Dummy Points | |
| duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
| is.im | Test Whether An Object Is A Pixel Image | |
| multiplicity.ppp | Count Multiplicity of Duplicate Points | |
| kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
| markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
| rThomas | Simulate Thomas Process | |
| subset.im | Extract Subset of Image | |
| plot.owin | Plot a Spatial Window | |
| trim.rectangle | Cut margins from rectangle | |
| summary.ppm | Summarizing a Fitted Point Process Model | |
| is.marked.ppm | Test Whether A Point Process Model is Marked | |
| rthin | Random Thinning | |
| compatible.im | Test Whether Two Pixel Images Are Compatible | |
| DiggleGratton | Diggle-Gratton model | |
| allstats | Calculate four standard summary functions of a point pattern. | |
| copper | Berman-Huntington points and lines data | |
| ppp | Create a Point Pattern | |
| vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
| compatible.fv | Test Whether Two Function Objects Are Compatible | |
| MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
| mean.im | Mean Pixel Value in an Image | |
| OrdThresh | Ord's Interaction model | |
| Fest | Estimate the empty space function F | |
| bdist.points | Distance to Boundary of Window | |
| cut.im | Convert Pixel Image from Numeric to Factor | |
| rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
| is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
| suffstat | Sufficient Statistic of Point Process Model | |
| im.object | Class of Images | |
| finpines | Pine saplings in Finland. | |
| thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
| rSSI | Simulate Simple Sequential Inhibition | |
| Jmulti | Marked J Function | |
| clickppp | Interactively Add Points | |
| reach | Interaction Distance of a Point Process | |
| midpoints.psp | Midpoints of Line Segment Pattern | |
| crossdist.default | Pairwise distances between two different sets of points | |
| bdist.pixels | Distance to Boundary of Window | |
| ppm | Fit Point Process Model to Data | |
| ripras | Estimate window from points alone | |
| owin.object | Class owin | |
| plot.fasp | Plot a Function Array | |
| harmonic | Basis for Harmonic Functions | |
| endpoints.psp | Endpoints of Line Segment Pattern | |
| predict.ppm | Prediction from a Fitted Point Process Model | |
| union.quad | Union of Data and Dummy Points | |
| update.ppm | Update a Fitted Point Process Model | |
| profilepl | Profile Maximum Pseudolikelihood | |
| plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
| markcorr | Mark Correlation Function | |
| rpoispp | Generate Poisson Point Pattern | |
| nearest.raster.point | Find Pixel Nearest to a Given Point | |
| rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
| unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
| pairdist.psp | Pairwise distances between line segments | |
| persp.im | Perspective Plot of Pixel Image | |
| rotate.owin | Rotate a Window | |
| unmark | Remove Marks from a Marked Point Pattern | |
| spatstat.options | Internal Options in Spatstat Package | |
| No Results! | ||
Last month downloads
Details
| Date | 27 September 2006 |
| License | GPL version 2 or newer |
| URL | http://www.spatstat.org |
| Packaged | Wed Sep 27 17:21:44 2006; adrian |
| depends | base (>= 2.2.0) , mgcv , R (>= 2.2.0) |
| suggests | sm |
| Contributors | Rolf Turner, Adrian Baddeley |
Include our badge in your README
[](http://www.rdocumentation.org/packages/spatstat)