spatstat v1.8-7
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Spatial Point Pattern analysis, model-fitting and simulation
Spatial Point Pattern data analysis, modelling and simulation
including multitype/marked points and spatial covariates
Functions in spatstat
| Name | Description | |
| Strauss | The Strauss Point Process Model | |
| OrdThresh | Ord's Interaction model | |
| StraussHard | The Strauss / Hard Core Point Process Model | |
| complement.owin | Take Complement of a Window | |
| compatible.im | Test Whether Two Pixel Images Are Compatible | |
| amacrine | Hughes' Amacrine Cell Data | |
| concatxy | Concatenate x,y Coordinate Vectors | |
| data.ppm | Extract Original Data from a Fitted Point Process Model | |
| demopat | Artificial Data Point Pattern | |
| distmap | Distance Map | |
| diameter | Diameter of a Window Frame | |
| hamster | Aherne's hamster tumour data | |
| is.owin | Test Whether An Object Is A Window | |
| kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
| markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
| pairdist | Pairwise distances | |
| pcf.fv | Pair Correlation Function obtained from K Function | |
| plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
| quadratcount | Quadrat counting for a point pattern | |
| print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
| psp.object | Class of Line Segment Patterns | |
| ppm.object | Class of Fitted Point Process Models | |
| Ord | Generic Ord Interaction model | |
| affine.ppp | Apply Affine Transformation To Point Pattern | |
| allstats | Calculate four standard summary functions of a point pattern. | |
| rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
| ripras | Estimate window from points alone | |
| as.mask | Pixel Image Approximation of a Window | |
| rotate.owin | Rotate a Window | |
| shift.im | Apply Vector Translation To Pixel Image | |
| cells | Biological Cells Point Pattern | |
| dilate.owin | Dilate a Window | |
| endpoints.psp | Endpoints of Line Segment Pattern | |
| finpines | Pine saplings in Finland. | |
| simdat | Simulated Point Pattern | |
| gridweights | Compute Quadrature Weights Based on Grid Counts | |
| inside.owin | Test Whether Points Are Inside A Window | |
| subset.fv | Extract Subset of Function Values | |
| multiplicity.ppp | Count Multiplicity of Duplicate Points | |
| nearest.raster.point | Find Pixel Nearest to a Given Point | |
| pairdist.default | Pairwise distances | |
| superimpose | Superimpose Several Point Patterns | |
| rpoispp | Generate Poisson Point Pattern | |
| rMatClust | Simulate Matern Cluster Process | |
| crossdist.ppp | Pairwise distances between two different point patterns | |
| rMaternII | Simulate Matern Model II | |
| reach | Interaction Distance of a Point Process | |
| Geyer | Geyer's Saturation Point Process Model | |
| Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
| Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
| redwood | California Redwoods Point Pattern (Ripley's Subset) | |
| rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
| rpoisline | Generate Poisson Random Line Process | |
| Jdot | Multitype J Function (i-to-any) | |
| Jcross | Multitype J Function (i-to-j) | |
| Jmulti | Marked J Function | |
| Kcross | Multitype K Function (Cross-type) | |
| Kest | K-function | |
| Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
| shift.psp | Apply Vector Translation To Line Segment Pattern | |
| Kmulti | Marked K-Function | |
| LennardJones | The Lennard-Jones Potential | |
| subset.psp | Extract Subset of Line Segment Pattern | |
| Jest | Estimate the J-function | |
| MultiStrauss | The Multitype Strauss Point Process Model | |
| Kmeasure | Reduced Second Moment Measure | |
| spatstat | The Spatstat Package | |
| MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
| subset.fasp | Extract Subset of Function Array | |
| Softcore | The Soft Core Point Process Model | |
| PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
| summary.quad | Summarizing a Quadrature Scheme | |
| update.ppm | Update a Fitted Point Process Model | |
| summary.ppp | Summary of a Point Pattern Dataset | |
| Pairwise | Generic Pairwise Interaction model | |
| affine.psp | Apply Affine Transformation To Line Segment Pattern | |
| area.owin | Area of a Window | |
| Saturated | Saturated Pairwise Interaction model | |
| centroid.owin | Centroid of a window | |
| angles.psp | Orientation Angles of Line Segments | |
| alltypes | Calculate Statistic for All Types in a Multitype Point Pattern | |
| as.im | Convert to Pixel Image | |
| append.psp | Combine Two Line Segment Patterns | |
| as.rectangle | Window Frame | |
| bdist.points | Distance to Boundary of Window | |
| Kcross.inhom | Inhomogeneous Cross K Function | |
| as.psp | Convert Data To Class psp | |
| corners | Corners of a rectangle | |
| copper | Berman-Huntington points and lines data | |
| bramblecanes | Hutchings' Bramble Canes data | |
| ants | Harkness-Isham ants' nests data | |
| betacells | Beta Ganglion Cells in Cat Retina | |
| fasp.object | Function Arrays for Spatial Patterns | |
| compatible.fv | Test Whether Two Function Objects Are Compatible | |
| applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
| spatstat-internal | Internal spatstat functions | |
| default.dummy | Generate a Default Pattern of Dummy Points | |
| diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
| fv.object | Data Frames of Function Values | |
| crossdist | Pairwise distances | |
| lansing | Lansing Woods Point Pattern | |
| plot.im | Plot a Pixel Image | |
| dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
| distmap.ppp | Distance Map of Point Pattern | |
| eem | Exponential Energy Marks | |
| cut.ppp | Convert Point Pattern Marks from Numeric to Factor | |
| rThomas | Simulate Thomas Process | |
| duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
| qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
| plot.splitppp | Plot a List of Point Patterns | |
| erode.owin | Erode a Window | |
| expand.owin | Expand Window By Factor | |
| rMaternI | Simulate Matern Model I | |
| harmonic | Basis for Harmonic Functions | |
| fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
| ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
| subset.im | Extract Subset of Image | |
| im | Create a Pixel Image Object | |
| subset.ppp | Extract or Replace Subset of Point Pattern | |
| im.object | Class of Images | |
| eroded.areas | Areas of Morphological Erosions | |
| humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
| intersect.owin | Intersection or Union of Two Windows | |
| envelope | Simulation envelopes of summary function | |
| bounding.box | Bounding Box of a Window | |
| density.ppp | Kernel Smoothed Intensity of Point Pattern | |
| lengths.psp | Lengths of Line Segments | |
| is.marked.ppm | Test Whether A Point Process Model is Marked | |
| is.im | Test Whether An Object Is A Pixel Image | |
| is.ppp | Test Whether An Object Is A Point Pattern | |
| is.marked | Test Whether Marks Are Present | |
| lurking | Lurking variable plot | |
| is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
| nndist | Nearest neighbour distances | |
| longleaf | Longleaf Pines Point Pattern | |
| ord.family | Ord Interaction Process Family | |
| letterR | Window in Shape of Letter R | |
| owin | Create a Window | |
| pairsat.family | Saturated Pairwise Interaction Point Process Family | |
| plot.fv | Plot Function Valuesn | |
| pairdist.ppp | Pairwise distances | |
| pcf.ppp | Pair Correlation Function of Point Pattern | |
| plot.owin | Plot a Spatial Window | |
| pairwise.family | Pairwise Interaction Process Family | |
| pairdist.psp | Pairwise distances between line segments | |
| plot.ppm | plot a Fitted Point Process Model | |
| plot.quad | plot a Spatial Quadrature Scheme | |
| plot.ppp | plot a Spatial Point Pattern | |
| ppp.object | Class of Point Patterns | |
| predict.ppm | Prediction from a Fitted Point Process Model | |
| ppp | Create a Point Pattern | |
| psp | Create a Line Segment Pattern | |
| print.owin | Print Brief Details of a Spatial Window | |
| print.ppm | Print a Fitted Point Process Model | |
| quad.object | Class of Quadrature Schemes | |
| raster.x | Cartesian Coordinates for a Pixel Raster | |
| rescue.rectangle | Convert Window Back To Rectangle | |
| residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
| residuals.ppm | Residuals for Fitted Point Process Model | |
| rmh.ppm | Simulate from a Fitted Point Process Model | |
| reduced.sample | Reduced Sample Estimator using Histogram Data | |
| rlabel | Random Re-Labelling of Point Pattern | |
| rmpoint | Generate N Random Multitype Points | |
| rmpoispp | Generate Multitype Poisson Point Pattern | |
| rotate | Rotate | |
| rshift.ppp | Randomly Shift a Point Pattern | |
| shift | Apply Vector Translation | |
| rtoro | Random Toroidal Shift of Point Pattern | |
| shift.owin | Apply Vector Translation To Window | |
| rshift.psp | Randomly Shift a Line Segment Pattern | |
| runifpoint | Generate N Uniform Random Points | |
| setcov | Set Covariance of a Window | |
| scanpp | Read Point Pattern From Data File | |
| Fest | Estimate the empty space function F | |
| Gmulti | Marked Nearest Neighbour Distance Function | |
| spatstat.options | Internal Options in Spatstat Package | |
| stratrand | Stratified random point pattern | |
| Kest.fft | K-function using FFT | |
| Poisson | Poisson Point Process Model | |
| as.owin | Convert Data To Class owin | |
| spruces | Spruces Point Pattern | |
| square | Square Window | |
| chorley | Chorley-Ribble Cancer Data | |
| summary.owin | Summary of a Spatial Window | |
| spatstat-deprecated | Deprecated spatstat functions | |
| density.psp | Kernel Smoothing of Line Segment Pattern | |
| affine.owin | Apply Affine Transformation To Window | |
| summary.im | Summarizing a Pixel Image | |
| summary.ppm | Summarizing a Fitted Point Process Model | |
| distmap.psp | Distance Map of Line Segment Pattern | |
| distmap.owin | Distance Map of Window | |
| is.subset.owin | Determine Whether One Window is Contained In Another | |
| owin.object | Class owin | |
| nztrees | New Zealand Trees Point Pattern | |
| km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
| spokes | Spokes pattern of dummy points | |
| print.ppp | Print Brief Details of a Point Pattern Dataset | |
| quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
| rNeymanScott | Simulate Neyman-Scott Process | |
| rshift | Random Shift | |
| rotate.psp | Rotate a Line Segment Pattern | |
| rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
| union.quad | Union of Data and Dummy Points | |
| swedishpines | Swedish Pines Point Pattern | |
| rpoint | Generate N Random Points | |
| is.marked.ppp | Test Whether A Point Pattern is Marked | |
| suffstat | Sufficient Statistic of Point Process Model | |
| quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
| anova.ppm | ANOVA for Fitted Point Process Models | |
| rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
| unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
| identify.ppp | Identify Points in a Point Pattern | |
| ppm | Fit Point Process Model to Data | |
| rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
| rotate.ppp | Rotate a Point Pattern | |
| affine | Apply Affine Transformation | |
| rSSI | Simple Sequential Inhibition | |
| eval.im | Evaluate Expression Involving Pixel Images | |
| print.quad | Print a Quadrature Scheme | |
| DiggleGratton | Diggle-Gratton model | |
| Iest | Estimate the I-function | |
| Gest | Nearest Neighbour Distance Function G | |
| Kdot | Multitype K Function (i-to-any) | |
| Kinhom | Inhomogeneous K-function | |
| as.ppp | Convert Data To Class ppp | |
| bdist.pixels | Distance to Boundary of Window | |
| crossdist.default | Pairwise distances between two different sets of points | |
| dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
| crossdist.psp | Pairwise distances between two different line segment patterns | |
| eval.fv | Evaluate Expression Involving Functions | |
| gridcentres | Rectangular grid of points | |
| coef.ppm | Coefficients of Fitted Point Process Model | |
| midpoints.psp | Midpoints of Line Segment Pattern | |
| markcorr | Mark Correlation Function | |
| japanesepines | Japanese Pines Point Pattern | |
| pcf | Pair Correlation Function | |
| pcf.fasp | Pair Correlation Function obtained from array of K functions | |
| plot.fasp | Plot a Function Array | |
| print.im | Print Brief Details of an Image | |
| plot.psp | plot a Spatial Line Segment Pattern | |
| redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
| rshift.splitppp | Randomly Shift a List of Point Patterns | |
| shift.ppp | Apply Vector Translation To Point Pattern | |
| setmarks | Set or Reset the Marks in a Point Pattern | |
| split.ppp | Divide Point Pattern into Sub-patterns | |
| summary.psp | Summary of a Line Segment Pattern Dataset | |
| unmark | Remove Marks from a Marked Point Pattern | |
| No Results! | ||
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Details
| Date | 2 March 2006 |
| License | GPL version 2 or newer |
| URL | http://www.spatstat.org |
| Packaged | Thu Mar 2 18:18:46 2006; adrian |
| depends | base (>= 2.2.0) , mgcv , R (>= 2.2.0) , sm |
| Contributors | Rolf Turner, Adrian Baddeley |
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