spatstat v1.39-1
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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. Also supports three-dimensional point patterns, space-time point patterns in any number of dimensions, and point patterns on a linear network.
Contains about 2000 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, pixel images, tessellations, and linear networks.
Exploratory methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Diggle-Cressie-Loosmore-Ford, Dao-Genton) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov) are also supported.
Parametric models can be fitted to point pattern data using the functions ppm, kppm, slrm similar to glm. Types of models include Poisson, Gibbs, Cox and cluster point processes. Models may involve dependence on covariates, interpoint interaction, cluster formation and dependence on marks. Models are fitted by maximum likelihood, logistic regression, minimum contrast, and composite likelihood methods.
Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise, AIC). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots.
Functions in spatstat
| Name | Description | |
| Hybrid | Hybrid Interaction Point Process Model | |
| Extract.fasp | Extract Subset of Function Array | |
| Extract.linnet | Extract Subset of Linear Network | |
| Kdot | Multitype K Function (i-to-any) | |
| AreaInter | The Area Interaction Point Process Model | |
| Extract.fv | Extract or Replace Subset of Function Values | |
| Kmodel | K Function or Pair Correlation Function of a Point Process Model | |
| Kmulti | Marked K-Function | |
| Extract.im | Extract Subset of Image | |
| Extract.splitppp | Extract or Replace Sub-Patterns | |
| areaLoss | Difference of Disc Areas | |
| Geyer | Geyer's Saturation Point Process Model | |
| Extract.solist | Extract or Replace Subset of a List of Spatial Objest | |
| Frame | Extract or Change the Containing Rectangle of a Spatial Object | |
| DiggleGratton | Diggle-Gratton model | |
| Extract.tess | Extract or Replace Subset of Tessellation | |
| Fiksel | The Fiksel Interaction | |
| Extract.quad | Subset of Quadrature Scheme | |
| SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model | |
| Jdot | Multitype J Function (i-to-any) | |
| F3est | Empty Space Function of a Three-Dimensional Point Pattern | |
| Gmulti | Marked Nearest Neighbour Distance Function | |
| MultiHard | The Multitype Hard Core Point Process Model | |
| Kinhom | Inhomogeneous K-function | |
| Lest | L-function | |
| Jcross | Multitype J Function (i-to-j) | |
| Kcross.inhom | Inhomogeneous Cross K Function | |
| Kmulti.inhom | Inhomogeneous Marked K-Function | |
| Extract.lpp | Extract Subset of Point Pattern on Linear Network | |
| Extract.anylist | Extract or Replace Subset of a List of Things | |
| Extract.influence.ppm | Extract Subset of Influence Object | |
| Jest | Estimate the J-function | |
| Kres | Residual K Function | |
| Extract.msr | Extract Subset of Signed or Vector Measure | |
| anemones | Beadlet Anemones Data | |
| Ginhom | Inhomogeneous Nearest Neighbour Function | |
| as.interact | Extract Interaction Structure | |
| Gfox | Foxall's Distance Functions | |
| Emark | Diagnostics for random marking | |
| Replace.im | Reset Values in Subset of Image | |
| affine | Apply Affine Transformation | |
| Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
| as.mask | Pixel Image Approximation of a Window | |
| Kest | K-function | |
| as.ppp | Convert Data To Class ppp | |
| Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
| cauchy.estpcf | Fit the Neyman-Scott cluster process with Cauchy kernel | |
| Kscaled | Locally Scaled K-function | |
| Kmodel.ppm | K Function or Pair Correlation Function of Gibbs Point Process model | |
| BadGey | Hybrid Geyer Point Process Model | |
| Extract.ppx | Extract Subset of Multidimensional Point Pattern | |
| Tstat | Third order summary statistic | |
| Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
| anova.ppm | ANOVA for Fitted Point Process Models | |
| Kmeasure | Reduced Second Moment Measure | |
| Linhom | L-function | |
| Extract.layered | Extract Subset of a Layered Object | |
| as.rectangle | Window Frame | |
| Kcom | Model Compensator of K Function | |
| Ldot | Multitype L-function (i-to-any) | |
| box3 | Three-Dimensional Box | |
| G3est | Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern | |
| Ldot.inhom | Inhomogeneous Multitype L Dot Function | |
| Pairwise | Generic Pairwise Interaction model | |
| addvar | Added Variable Plot for Point Process Model | |
| areaGain | Difference of Disc Areas | |
| distmap.ppp | Distance Map of Point Pattern | |
| Smooth.ppp | Spatial smoothing of observations at irregular points | |
| amacrine | Hughes' Amacrine Cell Data | |
| alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern | |
| Iest | Estimate the I-function | |
| Smooth | Spatial smoothing of data | |
| bw.frac | Bandwidth Selection Based on Window Geometry | |
| DiggleGatesStibbard | Diggle-Gates-Stibbard Point Process Model | |
| as.hyperframe.ppx | Extract coordinates and marks of multidimensional point pattern | |
| Window | Extract or Change the Window of a Spatial Object | |
| cells | Biological Cells Point Pattern | |
| Kmodel.kppm | K Function or Pair Correlation Function of Cluster Model or Cox model | |
| LennardJones | The Lennard-Jones Potential | |
| density.ppp | Kernel Smoothed Intensity of Point Pattern | |
| bounding.box.xy | Convex Hull of Points | |
| MultiStrauss | The Multitype Strauss Point Process Model | |
| Kest.fft | K-function using FFT | |
| as.fv | Convert Data To Class fv | |
| Ord | Generic Ord Interaction model | |
| bind.fv | Combine Function Value Tables | |
| Hardcore | The Hard Core Point Process Model | |
| append.psp | Combine Two Line Segment Patterns | |
| Extract.listof | Extract or Replace Subset of a List of Things | |
| Jinhom | Inhomogeneous J-function | |
| Lcross | Multitype L-function (cross-type) | |
| Extract.owin | Extract Subset of Window | |
| Poisson | Poisson Point Process Model | |
| allstats | Calculate four standard summary functions of a point pattern. | |
| Saturated | Saturated Pairwise Interaction model | |
| as.owin | Convert Data To Class owin | |
| crossing.psp | Crossing Points of Two Line Segment Patterns | |
| MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
| bdist.tiles | Distance to Boundary of Window | |
| circumradius | Circumradius of a Window | |
| Smoothfun.ppp | Smooth Interpolation of Marks as a Spatial Function | |
| as.hyperframe | Convert Data to Hyperframe | |
| compareFit | Residual Diagnostics for Multiple Fitted Models | |
| chicago | Chicago Street Crime Data | |
| StraussHard | The Strauss / Hard Core Point Process Model | |
| as.solist | Convert List of Two-Dimensional Spatial Objects | |
| copper | Berman-Huntington points and lines data | |
| applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
| Softcore | The Soft Core Point Process Model | |
| eval.im | Evaluate Expression Involving Pixel Images | |
| as.matrix.owin | Convert Pixel Image to Matrix | |
| PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
| Lcross.inhom | Inhomogeneous Cross Type L Function | |
| bw.diggle | Cross Validated Bandwidth Selection for Kernel Density | |
| closing | Morphological Closing | |
| affine.tess | Apply Geometrical Transformation To Tessellation | |
| beginner | Print Introduction For Beginners | |
| affine.lpp | Apply Geometrical Transformations to Point Pattern on a Linear Network | |
| adaptive.density | Intensity Estimate of Point Pattern Using Tessellation | |
| disc | Circular Window | |
| affine.im | Apply Affine Transformation To Pixel Image | |
| harmonic | Basis for Harmonic Functions | |
| add.texture | Fill Plot With Texture | |
| effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model | |
| berman.test | Berman's Tests for Point Process Model | |
| anova.mppm | ANOVA for Fitted Multiple Point Process Models | |
| bronzefilter | Bronze gradient filter data | |
| bw.stoyan | Stoyan's Rule of Thumb for Bandwidth Selection | |
| as.box3 | Convert Data to Three-Dimensional Box | |
| bdist.pixels | Distance to Boundary of Window | |
| complement.owin | Take Complement of a Window | |
| bdist.points | Distance to Boundary of Window | |
| Strauss | The Strauss Point Process Model | |
| connected.ppp | Connected components of a point pattern | |
| as.psp | Convert Data To Class psp | |
| as.im | Convert to Pixel Image | |
| edges | Extract Boundary Edges of a Window. | |
| compatible.fv | Test Whether Function Objects Are Compatible | |
| coef.ppm | Coefficients of Fitted Point Process Model | |
| as.tess | Convert Data To Tessellation | |
| dmixpois | Mixed Poisson Distribution | |
| crossdist | Pairwise distances | |
| beachcolours | Create Colour Scheme for a Range of Numbers | |
| bei | Tropical rain forest trees | |
| border | Border Region of a Window | |
| affine.psp | Apply Affine Transformation To Line Segment Pattern | |
| coords | Extract or Change Coordinates of a Spatial or Spatiotemporal Point Pattern | |
| Gres | Residual G Function | |
| closepairs.pp3 | Close Pairs of Points in 3 Dimensions | |
| diameter | Diameter of an Object | |
| as.lpp | Convert Data to a Point Pattern on a Linear Network | |
| as.data.frame.psp | Coerce Line Segment Pattern to a Data Frame | |
| anylist | List of Objects | |
| crossdist.psp | Pairwise distances between two different line segment patterns | |
| delaunay.distance | Distance on Delaunay Triangulation | |
| centroid.owin | Centroid of a window | |
| blur | Apply Gaussian Blur to a Pixel Image | |
| ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
| Smooth.msr | Smooth a Signed or Vector-Valued Measure | |
| as.mask.psp | Convert Line Segment Pattern to Binary Pixel Mask | |
| cdf.test | Spatial Distribution Test for Point Pattern or Point Process Model | |
| deriv.fv | Calculate Derivative of Function Values | |
| clarkevans.test | Clark and Evans Test | |
| as.data.frame.im | Convert Pixel Image to Data Frame | |
| intensity.lpp | Empirical Intensity of Point Pattern on Linear Network | |
| commonGrid | Determine A Common Spatial Domain And Pixel Resolution | |
| clickbox | Interactively Define a Rectangle | |
| area.owin | Area of a Window | |
| closepairs | Close Pairs of Points | |
| integral.im | Integral of a Pixel Image | |
| clickppp | Interactively Add Points | |
| Triplets | The Triplet Point Process Model | |
| clip.infline | Intersect Infinite Straight Lines with a Window | |
| dummify | Convert Data to Numeric Values by Constructing Dummy Variables | |
| as.matrix.im | Convert Pixel Image to Matrix or Array | |
| anova.lppm | ANOVA for Fitted Point Process Models on Linear Network | |
| affine.linnet | Apply Geometrical Transformations to a Linear Network | |
| diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
| by.ppp | Apply a Function to a Point Pattern Broken Down by Factor | |
| compatible.fasp | Test Whether Function Arrays Are Compatible | |
| contour.im | Contour plot of pixel image | |
| discs | Union of Discs | |
| bw.scott | Scott's Rule for Bandwidth Selection for Kernel Density | |
| delaunay | Delaunay Triangulation of Point Pattern | |
| dclf.test | Diggle-Cressie-Loosmore-Ford and Maximum Absolute Deviation Tests | |
| betacells | Beta Ganglion Cells in Cat Retina | |
| convolve.im | Convolution of Pixel Images | |
| default.dummy | Generate a Default Pattern of Dummy Points | |
| lppm | Fit Point Process Model to Point Pattern on Linear Network | |
| density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
| crossdist.default | Pairwise distances between two different sets of points | |
| fv | Create a Function Value Table | |
| diameter.owin | Diameter of a Window | |
| crossdist.ppx | Pairwise Distances Between Two Different Multi-Dimensional Point Patterns | |
| default.rmhcontrol | Set Default Control Parameters for Metropolis-Hastings Algorithm. | |
| harmonise | Make Objects Compatible | |
| corners | Corners of a rectangle | |
| clarkevans | Clark and Evans Aggregation Index | |
| connected | Connected components | |
| WindowOnly | Extract Window of Spatial Object | |
| affine.ppp | Apply Affine Transformation To Point Pattern | |
| nndist | Nearest neighbour distances | |
| persp.im | Perspective Plot of Pixel Image | |
| eval.linim | Evaluate Expression Involving Pixel Images on Linear Network | |
| edge.Trans | Translation Edge Correction | |
| colourtools | Convert and Compare Colours in Different Formats | |
| bramblecanes | Hutchings' Bramble Canes data | |
| by.im | Apply Function to Image Broken Down by Factor | |
| cut.im | Convert Pixel Image from Numeric to Factor | |
| colourmap | Colour Lookup Tables | |
| coef.mppm | Coefficients of Point Process Model Fitted to Multiple Point Patterns | |
| exactMPLEstrauss | Exact Maximum Pseudolikelihood Estimate for Stationary Strauss Process | |
| intersect.tess | Intersection of Two Tessellations | |
| dilated.areas | Areas of Morphological Dilations | |
| compatible | Test Whether Objects Are Compatible | |
| collapse.fv | Collapse Several Function Tables into One | |
| eval.fv | Evaluate Expression Involving Functions | |
| distfun | Distance Map as a Function | |
| dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
| eval.fasp | Evaluate Expression Involving Function Arrays | |
| diameter.box3 | Geometrical Calculations for Three-Dimensional Box | |
| as.ppm | Extract Fitted Point Process Model | |
| bw.smoothppp | Cross Validated Bandwidth Selection for Spatial Smoothing | |
| edges2vees | List Dihedral Triples in a Graph | |
| kppm | Fit Cluster or Cox Point Process Model | |
| endpoints.psp | Endpoints of Line Segment Pattern | |
| chop.tess | Subdivide a Window or Tessellation using a Set of Lines | |
| kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
| fitted.slrm | Fitted Probabilities for Spatial Logistic Regression | |
| envelope.pp3 | Simulation Envelopes of Summary Function for 3D Point Pattern | |
| letterR | Window in Shape of Letter R | |
| pcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-Type) | |
| iplot | Point and Click Interface for Displaying Spatial Data | |
| hyperframe | Hyper Data Frame | |
| lgcp.estpcf | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| is.convex | Test Whether a Window is Convex | |
| increment.fv | Increments of a Function | |
| mucosa | Cells in Gastric Mucosa | |
| concatxy | Concatenate x,y Coordinate Vectors | |
| logLik.slrm | Loglikelihood of Spatial Logistic Regression | |
| dilation | Morphological Dilation | |
| dfbetas.ppm | Parameter influence measure | |
| is.rectangle | Determine Type of Window | |
| gauss.hermite | Gauss-Hermite Quadrature Approximation to Expectation for Normal Distribution | |
| intensity.ppm | Intensity of Fitted Point Process Model | |
| linearpcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-type) for Linear Point Pattern | |
| clickpoly | Interactively Define a Polygon | |
| is.marked | Test Whether Marks Are Present | |
| dirichlet | Dirichlet Tessellation of Point Pattern | |
| cut.ppp | Classify Points in a Point Pattern | |
| lpp | Create Point Pattern on Linear Network | |
| print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
| foo | Foo is Not a Variable | |
| interp.colourmap | Interpolate smoothly between specified colours | |
| envelope.envelope | Recompute Envelopes | |
| pool.envelope | Pool Data from Several Envelopes | |
| heather | Diggle's Heather Data | |
| linearpcfdot | Multitype Pair Correlation Function (Dot-type) for Linear Point Pattern | |
| grow.rectangle | Add margins to rectangle | |
| methods.kppm | Methods for Cluster Point Process Models | |
| pairorient | Point Pair Orientation Distribution | |
| ppm.object | Class of Fitted Point Process Models | |
| methods.rhohat | Methods for Intensity Functions of Spatial Covariate | |
| erosion | Morphological Erosion | |
| bw.relrisk | Cross Validated Bandwidth Selection for Relative Risk Estimation | |
| distmap.owin | Distance Map of Window | |
| nndist.pp3 | Nearest neighbour distances in three dimensions | |
| distmap.psp | Distance Map of Line Segment Pattern | |
| duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
| is.subset.owin | Determine Whether One Window is Contained In Another | |
| lut | Lookup Tables | |
| harmonise.im | Make Pixel Images Compatible | |
| idw | Inverse-distance weighted smoothing of observations at irregular points | |
| is.marked.ppm | Test Whether A Point Process Model is Marked | |
| clickjoin | Interactively join vertices on a plot | |
| linim | Create Pixel Image on Linear Network | |
| methods.linnet | Methods for Linear Networks | |
| quadrat.test | Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
| plot.listof | Plot a List of Things | |
| envelope | Simulation Envelopes of Summary Function | |
| convexhull.xy | Convex Hull of Points | |
| fryplot | Fry Plot of Point Pattern | |
| hyytiala | Scots pines and other trees at Hyytiala | |
| envelope.lpp | Envelope for Point Patterns on Linear Network | |
| incircle | Find Largest Circle Inside Window | |
| hist.im | Histogram of Pixel Values in an Image | |
| is.hybrid | Test Whether Object is a Hybrid | |
| is.lpp | Test Whether An Object Is A Point Pattern on a Linear Network | |
| methods.objsurf | Methods for Objective Function Surfaces | |
| markcorr | Mark Correlation Function | |
| distfun.lpp | Distance Map on Linear Network | |
| flipxy | Exchange X and Y Coordinates | |
| plot.tess | Plot a tessellation | |
| harmonise.fv | Make Function Tables Compatible | |
| methods.lppm | Methods for Fitted Point Process Models on a Linear Network | |
| plot.hyperframe | Plot Entries in a Hyperframe | |
| im.object | Class of Images | |
| invoke.symbolmap | Plot Data Using Graphics Symbol Map | |
| marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern | |
| fvnames | Abbreviations for Groups of Columns in Function Value Table | |
| linfun | Function on a Linear Network | |
| domain | Extract the Domain of any Spatial Object | |
| finpines | Pine saplings in Finland. | |
| convexhull | Convex Hull | |
| hybrid.family | Hybrid Interaction Family | |
| is.im | Test Whether An Object Is A Pixel Image | |
| rpoispp | Generate Poisson Point Pattern | |
| deltametric | Delta Metric | |
| rpoint | Generate N Random Points | |
| is.stationary | Recognise Stationary and Poisson Point Process Models | |
| influence.ppm | Influence Measure for Spatial Point Process Model | |
| midpoints.psp | Midpoints of Line Segment Pattern | |
| linearmarkequal | Mark Connection Function for Multitype Point Pattern on Linear Network | |
| nnfun | Nearest Neighbour Index Map as a Function | |
| nndist.lpp | Nearest neighbour distances on a linear network | |
| is.owin | Test Whether An Object Is A Window | |
| gridcentres | Rectangular grid of points | |
| lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| nearest.raster.point | Find Pixel Nearest to a Given Point | |
| is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
| japanesepines | Japanese Pines Point Pattern | |
| edge.Ripley | Ripley's Isotropic Edge Correction | |
| lineardisc | Compute Disc of Given Radius in Linear Network | |
| scanLRTS | Likelihood Ratio Test Statistic for Scan Test | |
| intersect.owin | Intersection, Union or Set Subtraction of Two Windows | |
| imcov | Spatial Covariance of a Pixel Image | |
| is.dppm | Recognise Fitted Determinantal Point Process Models | |
| murchison | Murchison gold deposits | |
| fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |
| rescale | Convert dataset to another unit of length | |
| rotate.owin | Rotate a Window | |
| eem | Exponential Energy Marks | |
| pcfinhom | Inhomogeneous Pair Correlation Function | |
| latest.news | Print News About Latest Version of Package | |
| methods.fii | Methods for Fitted Interactions | |
| methods.slrm | Methods for Spatial Logistic Regression Models | |
| ewcdf | Weighted Empirical Cumulative Distribution Function | |
| marks.psp | Marks of a Line Segment Pattern | |
| ippm | Fit Point Process Model Involving Irregular Trend Parameters | |
| layered | Create List of Plotting Layers | |
| lansing | Lansing Woods Point Pattern | |
| leverage.ppm | Leverage Measure for Spatial Point Process Model | |
| linearmarkconnect | Mark Connection Function for Multitype Point Pattern on Linear Network | |
| markvario | Mark Variogram | |
| marks | Marks of a Point Pattern | |
| simplify.owin | Approximate a Polygon by a Simpler Polygon | |
| integral.msr | Integral of a Measure | |
| overlap.owin | Compute Area of Overlap | |
| pppmatching | Create a Point Matching | |
| methods.boxx | Methods for Multi-Dimensional Box | |
| inside.owin | Test Whether Points Are Inside A Window | |
| lengths.psp | Lengths of Line Segments | |
| linearK | Linear K Function | |
| progressreport | Print Progress Reports | |
| layerplotargs | Extract or Replace the Plot Arguments of a Layered Object | |
| redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
| gorillas | Gorilla Nesting Sites | |
| nncorr | Nearest-Neighbour Correlation Indices of Marked Point Pattern | |
| texturemap | Texture Map | |
| crossdist.pp3 | Pairwise distances between two different three-dimensional point patterns | |
| pairdist.default | Pairwise distances | |
| plot.ppp | plot a Spatial Point Pattern | |
| fardist | Farthest Distance to Boundary of Window | |
| hopskel | Hopkins-Skellam Test | |
| plot.bermantest | Plot Result of Berman Test | |
| pppmatching.object | Class of Point Matchings | |
| methods.layered | Methods for Layered Objects | |
| miplot | Morisita Index Plot | |
| npfun | Dummy Function Returns Number of Points | |
| model.depends | Identify Covariates Involved in each Model Term | |
| mincontrast | Method of Minimum Contrast | |
| urkiola | Urkiola Woods Point Pattern | |
| nnwhich | Nearest neighbour | |
| rescale.im | Convert Pixel Image to Another Unit of Length | |
| multiplicity.ppp | Count Multiplicity of Duplicate Points | |
| identify.ppp | Identify Points in a Point Pattern | |
| nearestsegment | Find Line Segment Nearest to Each Point | |
| linearKdot.inhom | Inhomogeneous multitype K Function (Dot-type) for Linear Point Pattern | |
| linearKdot | Multitype K Function (Dot-type) for Linear Point Pattern | |
| parres | Partial Residuals for Point Process Model | |
| nncross.pp3 | Nearest Neighbours Between Two Patterns in 3D | |
| linearKinhom | Inhomogeneous Linear K Function | |
| localK | Neighbourhood density function | |
| layout.boxes | Generate a Row or Column Arrangement of Rectangles. | |
| nndist.psp | Nearest neighbour distances between line segments | |
| quantile.ewcdf | Quantiles of Weighted Empirical Cumulative Distribution Function | |
| pairdist.pp3 | Pairwise distances in Three Dimensions | |
| linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |
| nbfires | Point Patterns of New Brunswick Forest Fires | |
| pcf.ppp | Pair Correlation Function of Point Pattern | |
| rlabel | Random Re-Labelling of Point Pattern | |
| model.matrix.slrm | Extract Design Matrix from Spatial Logistic Regression Model | |
| intensity.quadratcount | Intensity Estimates Using Quadrat Counts | |
| plot.msr | Plot a Signed or Vector-Valued Measure | |
| pairs.im | Scatterplot Matrix for Pixel Images | |
| linearpcf | Linear Pair Correlation Function | |
| summary.solist | Summary of a List of Spatial Objects | |
| methods.rho2hat | Methods for Intensity Functions of Two Spatial Covariates | |
| model.images | Compute Images of Constructed Covariates | |
| nztrees | New Zealand Trees Point Pattern | |
| pcf3est | Pair Correlation Function of a Three-Dimensional Point Pattern | |
| im.apply | Apply Function Pixelwise to List of Images | |
| interp.im | Interpolate a Pixel Image | |
| nnclean | Nearest Neighbour Clutter Removal | |
| plot.cdftest | Plot a Spatial Distribution Test | |
| lurking | Lurking variable plot | |
| linearKcross.inhom | Inhomogeneous multitype K Function (Cross-type) for Linear Point Pattern | |
| is.empty | Test Whether An Object Is Empty | |
| ponderosa | Ponderosa Pine Tree Point Pattern | |
| nnmap | K-th Nearest Point Map | |
| osteo | Osteocyte Lacunae Data: Replicated Three-Dimensional Point Patterns | |
| ppx | Multidimensional Space-Time Point Pattern | |
| pcfdot | Multitype pair correlation function (i-to-any) | |
| plot.pp3 | Plot a three-dimensional point pattern | |
| methods.lpp | Methods for Point Patterns on a Linear Network | |
| npoints | Number of Points in a Point Pattern | |
| linearpcfcross | Multitype Pair Correlation Function (Cross-type) for Linear Point Pattern | |
| pixelcentres | Extract Pixel Centres as Point Pattern | |
| localKinhom | Inhomogeneous Neighbourhood Density Function | |
| tweak.colourmap | Change Colour Values in a Colour Map | |
| padimage | Pad the Border of a Pixel Image | |
| plot.linnet | Plot a linear network | |
| plot.mppm | plot a Fitted Multiple Point Process Model | |
| rQuasi | Generate Quasirandom Point Pattern in Given Window | |
| methods.linfun | Methods for Functions on Linear Network | |
| plot.solist | Plot a List of Spatial Objects | |
| mean.im | Maximum, Minimum, Mean, Median, Range or Sum of Pixel Values in an Image | |
| nnfun.lpp | Nearest Neighbour Map on Linear Network | |
| ord.family | Ord Interaction Process Family | |
| rat | Ratio object | |
| pool.fasp | Pool Data from Several Function Arrays | |
| plot.envelope | Plot a Simulation Envelope | |
| project2set | Find Nearest Point in a Region | |
| matchingdist | Distance for a Point Pattern Matching | |
| rpoislinetess | Poisson Line Tessellation | |
| rpoisline | Generate Poisson Random Line Process | |
| runifpoint3 | Generate N Uniform Random Points in Three Dimensions | |
| plot.linim | Plot Pixel Image on Linear Network | |
| nnwhich.lpp | Identify Nearest Neighbours on a Linear Network | |
| shift.im | Apply Vector Translation To Pixel Image | |
| methods.units | Methods for Units | |
| objsurf | Objective Function Surface | |
| summary.splitppp | Summary of a Split Point Pattern | |
| pixellate.owin | Convert Window to Pixel Image | |
| pixelquad | Quadrature Scheme Based on Pixel Grid | |
| print.owin | Print Brief Details of a Spatial Window | |
| rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
| psp | Create a Line Segment Pattern | |
| plot.im | Plot a Pixel Image | |
| profilepl | Profile Maximum Pseudolikelihood | |
| quadrat.test.mppm | Chi-Squared Test for Multiple Point Process Model Based on Quadrat Counts | |
| nnwhich.pp3 | Nearest neighbours in three dimensions | |
| psst | Pseudoscore Diagnostic For Fitted Model against General Alternative | |
| runifpoint | Generate N Uniform Random Points | |
| pointsOnLines | Place Points Evenly Along Specified Lines | |
| rlinegrid | Generate grid of parallel lines with random displacement | |
| plot.psp | plot a Spatial Line Segment Pattern | |
| rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |
| triplet.family | Triplet Interaction Family | |
| intensity.ppp | Empirical Intensity of Point Pattern | |
| plot.scan.test | Plot Result of Scan Test | |
| discpartarea | Area of Part of Disc | |
| plot.splitppp | Plot a List of Point Patterns | |
| volume | Volume of an Object | |
| project2segment | Move Point To Nearest Line | |
| nsegments | Number of Line Segments in a Line Segment Pattern | |
| split.im | Divide Image Into Sub-images | |
| maxnndist | Compute Minimum or Maximum Nearest-Neighbour Distance | |
| qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
| rMaternII | Simulate Matern Model II | |
| predict.mppm | Prediction for Fitted Multiple Point Process Model | |
| pcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Type-i-To-Any-Type) | |
| plot.quad | Plot a Spatial Quadrature Scheme | |
| residuals.ppm | Residuals for Fitted Point Process Model | |
| linearpcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Dot-type) for Linear Point Pattern | |
| predict.ppm | Prediction from a Fitted Point Process Model | |
| rDiggleGratton | Perfect Simulation of the Diggle-Gratton Process | |
| plot.symbolmap | Plot a Graphics Symbol Map | |
| pool.quadrattest | Pool Several Quadrat Tests | |
| quad.object | Class of Quadrature Schemes | |
| rthin | Random Thinning | |
| rNeymanScott | Simulate Neyman-Scott Process | |
| plot.texturemap | Plot a Texture Map | |
| ppm | Fit Point Process Model to Data | |
| rhohat | Smoothing Estimate of Covariate Transformation | |
| pyramidal | Pyramidal Neurons in Cingulate Cortex | |
| rotate.ppp | Rotate a Point Pattern | |
| rThomas | Simulate Thomas Process | |
| perimeter | Perimeter Length of Window | |
| print.quad | Print a Quadrature Scheme | |
| runifdisc | Generate N Uniform Random Points in a Disc | |
| rotate.psp | Rotate a Line Segment Pattern | |
| quantile.im | Sample Quantiles of Pixel Image | |
| plot.fv | Plot Function Values | |
| project.ppm | Force Point Process Model to be Valid | |
| longleaf | Longleaf Pines Point Pattern | |
| quadratresample | Resample a Point Pattern by Resampling Quadrats | |
| simba | Simulated data from a two-group experiment with replication within each group. | |
| pairsat.family | Saturated Pairwise Interaction Point Process Family | |
| pixellate.ppp | Convert Point Pattern to Pixel Image | |
| shift.owin | Apply Vector Translation To Window | |
| rStraussHard | Perfect Simulation of the Strauss-Hardcore Process | |
| rSSI | Simulate Simple Sequential Inhibition | |
| runifpointOnLines | Generate N Uniform Random Points On Line Segments | |
| pairdist.psp | Pairwise distances between line segments | |
| reach | Interaction Distance of a Point Process | |
| plot.lpp | Plot Point Pattern on Linear Network | |
| reduced.sample | Reduced Sample Estimator using Histogram Data | |
| methods.pp3 | Methods for three-dimensional point patterns | |
| redwood | California Redwoods Point Pattern (Ripley's Subset) | |
| simdat | Simulated Point Pattern | |
| vcov.kppm | Variance-Covariance Matrix for a Fitted Cluster Point Process Model | |
| pixellate | Convert Spatial Object to Pixel Image | |
| rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |
| rescale.ppp | Convert Point Pattern to Another Unit of Length | |
| plot.ppm | plot a Fitted Point Process Model | |
| reload.or.compute | Compute Unless Previously Saved | |
| subfits | Extract List of Individual Point Process Models | |
| quasirandom | Quasirandom Patterns | |
| psstG | Pseudoscore Diagnostic For Fitted Model against Saturation Alternative | |
| tess | Create a Tessellation | |
| plot.kppm | Plot a fitted cluster point process | |
| textureplot | Plot Image Using Texture Fill | |
| predict.kppm | Prediction from a Fitted Cluster Point Process Model | |
| quadrat.test.splitppp | Dispersion Test of CSR for Split Point Pattern Based on Quadrat Counts | |
| plot.quadratcount | Plot Quadrat Counts | |
| rescale.owin | Convert Window to Another Unit of Length | |
| raster.x | Cartesian Coordinates for a Pixel Raster | |
| rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
| sessionLibs | Print Names and Version Numbers of Libraries Loaded | |
| spatstat-package | The Spatstat Package | |
| unitname | Name for Unit of Length | |
| spatstat-internal | Internal spatstat functions | |
| scan.test | Spatial Scan Test | |
| spruces | Spruces Point Pattern | |
| summary.ppm | Summarizing a Fitted Point Process Model | |
| spatstat-deprecated | Deprecated spatstat functions | |
| rCauchy | Simulate Neyman-Scott Point Process with Cauchy cluster kernel | |
| sharpen | Data Sharpening of Point Pattern | |
| plot.quadrattest | Display the result of a quadrat counting test. | |
| model.frame.ppm | Extract the Variables in a Point Process Model | |
| plot.fasp | Plot a Function Array | |
| rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
| range.fv | Range of Function Values | |
| nndensity.ppp | Estimate Intensity of Point Pattern Using Nearest Neighbour Distances | |
| summary.listof | Summary of a List of Things | |
| rho2hat | Smoothed Relative Density of Pairs of Covariate Values | |
| spokes | Spokes pattern of dummy points | |
| tiles | Extract List of Tiles in a Tessellation | |
| rMaternI | Simulate Matern Model I | |
| ppp | Create a Point Pattern | |
| rMosaicField | Mosaic Random Field | |
| update.ppm | Update a Fitted Point Process Model | |
| rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
| rMosaicSet | Mosaic Random Set | |
| rmpoispp | Generate Multitype Poisson Point Pattern | |
| sidelengths.owin | Side Lengths of Enclosing Rectangle of a Window | |
| rPoissonCluster | Simulate Poisson Cluster Process | |
| transect.im | Pixel Values Along a Transect | |
| rshift.psp | Randomly Shift a Line Segment Pattern | |
| rmh.ppm | Simulate from a Fitted Point Process Model | |
| moribund | Outdated Functions | |
| rjitter | Random Perturbation of a Point Pattern | |
| density.psp | Kernel Smoothing of Line Segment Pattern | |
| rmpoint | Generate N Random Multitype Points | |
| solist | List of Two-Dimensional Spatial Objects | |
| nncross | Nearest Neighbours Between Two Patterns | |
| spatstat.options | Internal Options in Spatstat Package | |
| residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
| plot.anylist | Plot a List of Things | |
| rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
| subset.ppp | Subset of Point Pattern Satisfying A Condition | |
| rknn | Theoretical Distribution of Nearest Neighbour Distance | |
| superimpose | Superimpose Several Geometric Patterns | |
| rotate.im | Rotate a Pixel Image | |
| square | Square Window | |
| rounding | Detect Numerical Rounding | |
| sumouter | Compute Quadratic Forms | |
| predict.lppm | Predict Point Process Model on Linear Network | |
| rshift.splitppp | Randomly Shift a List of Point Patterns | |
| runiflpp | Uniform Random Points on a Linear Network | |
| pixellate.psp | Convert Line Segment Pattern to Pixel Image | |
| rVarGamma | Simulate Neyman-Scott Point Process with Variance Gamma cluster kernel | |
| runifpointx | Generate N Uniform Random Points in Any Dimensions | |
| with.fv | Evaluate an Expression in a Function Table | |
| union.quad | Union of Data and Dummy Points | |
| rstrat | Simulate Stratified Random Point Pattern | |
| symbolmap | Graphics Symbol Map | |
| rMatClust | Simulate Matern Cluster Process | |
| scanpp | Read Point Pattern From Data File | |
| summary.owin | Summary of a Spatial Window | |
| residuals.mppm | Residuals for Point Process Model Fitted to Multiple Point Patterns | |
| rcell | Simulate Baddeley-Silverman Cell Process | |
| unmark | Remove Marks | |
| scaletointerval | Rescale Data to Lie Between Specified Limits | |
| waka | Trees in Waka national park | |
| relrisk | Nonparametric Estimate of Spatially-Varying Relative Risk | |
| pppdist | Distance Between Two Point Patterns | |
| ripras | Estimate window from points alone | |
| timed | Record the Computation Time | |
| vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
| rgbim | Create Colour-Valued Pixel Image | |
| simplenet | Simple Example of Linear Network | |
| rsyst | Simulate systematic random point pattern | |
| valid.ppm | Check Whether Point Process Model is Valid | |
| eroded.areas | Areas of Morphological Erosions | |
| dirichlet.vertices | Vertices of Dirichlet Tessellation | |
| plot.lppm | Plot a Fitted Point Process Model on a Linear Network | |
| update.rmhcontrol | Update Control Parameters of Metropolis-Hastings Algorithm | |
| with.hyperframe | Evaluate an Expression in Each Row of a Hyperframe | |
| rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |
| vargamma.estpcf | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |
| rshift.ppp | Randomly Shift a Point Pattern | |
| slrm | Spatial Logistic Regression | |
| waterstriders | Waterstriders data. Three independent replications of a point pattern formed by insects. | |
| quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
| simulate.slrm | Simulate a Fitted Spatial Logistic Regression Model | |
| rescue.rectangle | Convert Window Back To Rectangle | |
| shift | Apply Vector Translation | |
| setcov | Set Covariance of a Window | |
| summary.quad | Summarizing a Quadrature Scheme | |
| will.expand | Test Expansion Rule | |
| round.ppp | Apply Numerical Rounding to Spatial Coordinates | |
| simplepanel | Simple Point-and-Click Interface Panels | |
| simulate.kppm | Simulate a Fitted Cluster Point Process Model | |
| summary.psp | Summary of a Line Segment Pattern Dataset | |
| stieltjes | Compute Integral of Function Against Cumulative Distribution | |
| superimpose.lpp | Superimpose Several Point Patterns on Linear Network | |
| swedishpines | Swedish Pines Point Pattern | |
| Ksector | Sector K-function | |
| varblock | Estimate Variance of Summary Statistic by Subdivision | |
| methods.ppx | Methods for Multidimensional Space-Time Point Patterns | |
| simulate.ppm | Simulate a Fitted Gibbs Point Process Model | |
| vcov.mppm | Calculate Variance-Covariance Matrix for Fitted Multiple Point Process Model | |
| sporophores | Sporophores Data | |
| Smooth.fv | Apply Smoothing to Function Values | |
| selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
| rotmean | Rotational Average of a Pixel Image | |
| shift.ppp | Apply Vector Translation To Point Pattern | |
| split.ppx | Divide Multidimensional Point Pattern into Sub-patterns | |
| anova.slrm | Analysis of Deviance for Spatial Logistic Regression Models | |
| tilenames | Names of Tiles in a Tessellation | |
| as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |
| shapley | Galaxies in the Shapley Supercluster | |
| quadratcount | Quadrat counting for a point pattern | |
| coef.slrm | Coefficients of Fitted Spatial Logistic Regression Model | |
| trim.rectangle | Cut margins from rectangle | |
| tile.areas | Compute Areas of Tiles in a Tessellation | |
| stratrand | Stratified random point pattern | |
| vcov.slrm | Variance-Covariance Matrix for a Fitted Spatial Logistic Regression | |
| owin | Create a Window | |
| formula.fv | Extract or Change the Plot Formula for a Function Value Table | |
| shift.psp | Apply Vector Translation To Line Segment Pattern | |
| summary.anylist | Summary of a List of Things | |
| nnmark | Mark of Nearest Neighbour | |
| suffstat | Sufficient Statistic of Point Process Model | |
| unnormdensity | Weighted kernel smoother | |
| dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
| update.symbolmap | Update a Graphics Symbol Map. | |
| ellipse | Elliptical Window. | |
| diameter.boxx | Geometrical Calculations for Multi-Dimensional Box | |
| istat | Point and Click Interface for Exploratory Analysis of Point Pattern | |
| expand.owin | Apply Expansion Rule | |
| summary.ppp | Summary of a Point Pattern Dataset | |
| whist | Weighted Histogram | |
| fitted.mppm | Fitted Conditional Intensity for Multiple Point Process Model | |
| pairdist.ppp | Pairwise distances | |
| fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
| is.ppp | Test Whether An Object Is A Point Pattern | |
| km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
| logLik.mppm | Log Likelihood for Poisson Point Process Model | |
| im | Create a Pixel Image Object | |
| pairdist.lpp | Pairwise shortest-path distances between points on a linear network | |
| perspPoints | Draw Points or Lines on a Surface Viewed in Perspective | |
| opening | Morphological Opening | |
| plot.layered | Layered Plot | |
| predict.slrm | Predicted or Fitted Values from Spatial Logistic Regression | |
| rHardcore | Perfect Simulation of the Hardcore Process | |
| rmhexpand | Specify Simulation Window or Expansion Rule | |
| spatialcdf | Spatial Cumulative Distribution Function | |
| summary.im | Summarizing a Pixel Image | |
| logLik.ppm | Log Likelihood and AIC for Point Process Model | |
| methods.funxy | Methods for Spatial Functions | |
| Extract.psp | Extract Subset of Line Segment Pattern | |
| Fest | Estimate the Empty Space Function or its Hazard Rate | |
| as.linim | Convert to Pixel Image on Linear Network | |
| boundingbox | Bounding Box of a Window, Image, or Point Pattern | |
| bw.ppl | Likelihood Cross Validation Bandwidth Selection for Kernel Density | |
| cauchy.estK | Fit the Neyman-Scott cluster process with Cauchy kernel | |
| data.ppm | Extract Original Data from a Fitted Point Process Model | |
| chorley | Chorley-Ribble Cancer Data | |
| diameter.linnet | Circumradius and Diameter of a Linear Network | |
| distmap | Distance Map | |
| distcdf | Distribution Function of Interpoint Distance | |
| gordon | People in Gordon Square | |
| funxy | Spatial Function Class | |
| fv.object | Function Value Table | |
| gridweights | Compute Quadrature Weights Based on Grid Counts | |
| identify.psp | Identify Segments in a Line Segment Pattern | |
| improve.kppm | Improve Intensity Estimate of Fitted Cluster Point Process Model | |
| hamster | Aherne's hamster tumour data | |
| intensity | Intensity of a Dataset or a Model | |
| linearKcross | Multitype K Function (Cross-type) for Linear Point Pattern | |
| matclust.estpcf | Fit the Matern Cluster Point Process by Minimum Contrast Using Pair Correlation | |
| matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
| nncross.lpp | Nearest Neighbours on a Linear Network | |
| pcf.fv | Pair Correlation Function obtained from K Function | |
| pcfmulti | Marked pair correlation function | |
| plot.colourmap | Plot a Colour Map | |
| panel.contour | Panel Plots using Colour Image or Contour Lines | |
| nndist.ppx | Nearest Neighbour Distances in Any Dimensions | |
| plot.owin | Plot a Spatial Window | |
| plot.slrm | Plot a Fitted Spatial Logistic Regression | |
| quadrats | Divide Region into Quadrats | |
| rLGCP | Simulate Log-Gaussian Cox Process | |
| scalardilate | Apply Scalar Dilation | |
| rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |
| unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
| thomas.estpcf | Fit the Thomas Point Process by Minimum Contrast | |
| vargamma.estK | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |
| Finhom | Inhomogeneous Empty Space Function | |
| LambertW | Lambert's W Function | |
| OrdThresh | Ord's Interaction model | |
| angles.psp | Orientation Angles of Line Segments | |
| as.data.frame.hyperframe | Coerce Hyperframe to Data Frame | |
| as.polygonal | Convert a Window to a Polygonal Window | |
| cbind.hyperframe | Combine Hyperframes by Rows or by Columns | |
| as.layered | Convert Data To Layered Object | |
| Concom | The Connected Component Process Model | |
| Extract.ppp | Extract or Replace Subset of Point Pattern | |
| Gcom | Model Compensator of Nearest Neighbour Function | |
| Gest | Nearest Neighbour Distance Function G | |
| K3est | K-function of a Three-Dimensional Point Pattern | |
| Extract.leverage.ppm | Extract Subset of Leverage Object | |
| Kcross | Multitype K Function (Cross-type) | |
| affine.owin | Apply Affine Transformation To Window | |
| ants | Harkness-Isham ants' nests data | |
| cdf.test.mppm | Spatial Distribution Test for Multiple Point Process Model | |
| clusterset | Allard-Fraley Estimator of Cluster Feature | |
| demohyper | Demonstration Example of Hyperframe of Spatial Data | |
| discretise | Safely Convert Point Pattern Window to Binary Mask | |
| edges2triangles | List Triangles in a Graph | |
| hextess | Hexagonal Grid or Tessellation | |
| levelset | Level Set of a Pixel Image | |
| lohboot | Bootstrap Confidence Bands for Summary Function | |
| markcorrint | Mark Correlation Integral | |
| methods.box3 | Methods for Three-Dimensional Box | |
| model.matrix.ppm | Extract Design Matrix from Point Process Model | |
| msr | Signed or Vector-Valued Measure | |
| pairdist | Pairwise distances | |
| owin.object | Class owin | |
| pairwise.family | Pairwise Interaction Process Family | |
| pcf.fasp | Pair Correlation Function obtained from array of K functions | |
| pcfcross | Multitype pair correlation function (cross-type) | |
| plot.influence.ppm | Plot Influence Measure | |
| plot.leverage.ppm | Plot Leverage Function | |
| pool | Pool Data | |
| psp.object | Class of Line Segment Patterns | |
| crossdist.ppp | Pairwise distances between two different point patterns | |
| psstA | Pseudoscore Diagnostic For Fitted Model against Area-Interaction Alternative | |
| compatible.im | Test Whether Pixel Images Are Compatible | |
| rGaussPoisson | Simulate Gauss-Poisson Process | |
| contour.listof | Plot a List of Things | |
| dclf.progress | Progress Plot of Test of Spatial Pattern | |
| crossdist.lpp | Pairwise distances between two point patterns on a linear network | |
| boxx | Multi-Dimensional Box | |
| flu | Influenza Virus Proteins | |
| humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
| inforder.family | Infinite Order Interaction Family | |
| infline | Infinite Straight Lines | |
| is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
| pairdist.ppx | Pairwise Distances in Any Dimensions | |
| pcf | Pair Correlation Function | |
| paracou | Kimboto trees at Paracou, French Guiana | |
| ppm.ppp | Fit Point Process Model to Point Pattern Data | |
| solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
| split.hyperframe | Divide Hyperframe Into Subsets and Reassemble | |
| thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
| update.kppm | Update a Fitted Cluster Point Process Model | |
| is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
| rcellnumber | Generate Random Numbers of Points for Cell Process | |
| rDGS | Perfect Simulation of the Diggle-Gates-Stibbard Process | |
| reflect | Reflect In Origin | |
| rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |
| Extract.hyperframe | Extract or Replace Subset of Hyperframe | |
| Jmulti | Marked J Function | |
| Hest | Spherical Contact Distribution Function | |
| as.function.fv | Convert Function Value Table to Function | |
| clmfires | Castilla-La Mancha Forest Fires | |
| default.expand | Default Expansion Rule for Simulation of Model | |
| demopat | Artificial Data Point Pattern | |
| fasp.object | Function Arrays for Spatial Patterns | |
| formula.ppm | Model Formulae for Gibbs Point Process Models | |
| is.marked.ppp | Test Whether A Point Pattern is Marked | |
| localpcf | Local pair correlation function | |
| linnet | Create a Linear Network | |
| markconnect | Mark Connection Function | |
| markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
| nnwhich.ppx | Nearest Neighbours in Any Dimensions | |
| plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
| pool.rat | Pool Data from Several Ratio Objects | |
| pp3 | Three Dimensional Point Pattern | |
| ppp.object | Class of Point Patterns | |
| print.ppm | Print a Fitted Point Process Model | |
| print.im | Print Brief Details of an Image | |
| quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
| rStrauss | Perfect Simulation of the Strauss Process | |
| quadscheme.logi | Generate a Logistic Regression Quadrature Scheme from a Point Pattern | |
| rpoislpp | Poisson Point Process on a Linear Network | |
| simulate.lppm | Simulate a Fitted Point Process Model on a Linear Network | |
| vertices | Vertices of a Window | |
| stienen | Stienen Diagram | |
| zapsmall.im | Rounding of Pixel Values | |
| mppm | Fit Point Process Model to Several Point Patterns | |
| rotate | Rotate | |
| rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |
| run.simplepanel | Run Point-and-Click Interface | |
| rshift | Random Shift | |
| split.ppp | Divide Point Pattern into Sub-patterns | |
| rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |
| vesicles | Vesicles Data | |
| periodify | Make Periodic Copies of a Spatial Pattern | |
| print.ppp | Print Brief Details of a Point Pattern Dataset | |
| is.multitype | Test whether Object is Multitype | |
| No Results! | ||
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Details
| Nickname | Wrath of Grapes |
| Date | 2014-10-24 |
| License | GPL (>= 2) |
| URL | http://www.spatstat.org |
| LazyData | true |
| NeedsCompilation | yes |
| ByteCompile | true |
| Packaged | 2014-10-24 07:10:11 UTC; adrian |
| Repository | CRAN |
| Date/Publication | 2014-10-24 10:52:35 |
| imports | abind , deldir (>= 0.0-21) , goftest , mgcv , polyclip (>= 1.3-0) , tensor |
| depends | base (>= 3.1.1) , graphics , grDevices , R (>= 3.1.1) , stats , utils |
| suggests | gsl , locfit , maptools , Matrix , RandomFields (>= 3.0.0) , rpanel , scatterplot3d , sm , spatial , tkrplot |
| Contributors | Rolf Turner, Adrian Baddeley, Ege Rubak |
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