spatstat v1.40-0
0
Monthly downloads
Spatial Point Pattern Analysis, Model-fitting, Simulation, Tests
Comprehensive toolbox 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 | |
| rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |
| rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |
| rpoint | Generate N Random Points | |
| rshift | Random Shift | |
| residuals.mppm | Residuals for Point Process Model Fitted to Multiple Point Patterns | |
| runifdisc | Generate N Uniform Random Points in a Disc | |
| runiflpp | Uniform Random Points on a Linear Network | |
| rhohat | Smoothing Estimate of Covariate Transformation | |
| shift.im | Apply Vector Translation To Pixel Image | |
| rmh.ppm | Simulate from a Fitted Point Process Model | |
| rmhexpand | Specify Simulation Window or Expansion Rule | |
| sidelengths.owin | Side Lengths of Enclosing Rectangle of a Window | |
| subset.ppp | Subset of Point Pattern Satisfying A Condition | |
| sessionLibs | Print Names and Version Numbers of Libraries Loaded | |
| tweak.colourmap | Change Colour Values in a Colour Map | |
| rpoislpp | Poisson Point Process on a Linear Network | |
| valid.ppm | Check Whether Point Process Model is Valid | |
| Extract.fv | Extract or Replace Subset of Function Values | |
| rshift.splitppp | Randomly Shift a List of Point Patterns | |
| shift.owin | Apply Vector Translation To Window | |
| simulate.slrm | Simulate a Fitted Spatial Logistic Regression Model | |
| sporophores | Sporophores Data | |
| spatstat-package | The Spatstat Package | |
| simplify.owin | Approximate a Polygon by a Simpler Polygon | |
| Extract.hyperframe | Extract or Replace Subset of Hyperframe | |
| rescale.owin | Convert Window to Another Unit of Length | |
| spatialcdf | Spatial Cumulative Distribution Function | |
| spatstat-deprecated | Deprecated spatstat functions | |
| split.im | Divide Image Into Sub-images | |
| Jmulti | Marked J Function | |
| rounding | Detect Numerical Rounding | |
| Kmulti.inhom | Inhomogeneous Marked K-Function | |
| affine | Apply Affine Transformation | |
| update.ppm | Update a Fitted Point Process Model | |
| simulate.lppm | Simulate a Fitted Point Process Model on a Linear Network | |
| spatstat-internal | Internal spatstat functions | |
| Geyer | Geyer's Saturation Point Process Model | |
| summary.solist | Summary of a List of Spatial Objects | |
| Hybrid | Hybrid Interaction Point Process Model | |
| anova.mppm | ANOVA for Fitted Multiple Point Process Models | |
| rescale.ppp | Convert Point Pattern to Another Unit of Length | |
| summary.ppm | Summarizing a Fitted Point Process Model | |
| Kmodel.kppm | K Function or Pair Correlation Function of Cluster Model or Cox model | |
| solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
| as.data.frame.hyperframe | Coerce Hyperframe to Data Frame | |
| Kcom | Model Compensator of K Function | |
| slrm | Spatial Logistic Regression | |
| tilenames | Names of Tiles in a Tessellation | |
| rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
| round.ppp | Apply Numerical Rounding to Spatial Coordinates | |
| Kest.fft | K-function using FFT | |
| Ldot | Multitype L-function (i-to-any) | |
| update.symbolmap | Update a Graphics Symbol Map. | |
| relrisk | Estimate of Spatially-Varying Relative Risk | |
| volume | Volume of an Object | |
| tiles | Extract List of Tiles in a Tessellation | |
| with.fv | Evaluate an Expression in a Function Table | |
| rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
| Extract.ppx | Extract Subset of Multidimensional Point Pattern | |
| scaletointerval | Rescale Data to Lie Between Specified Limits | |
| runifpointx | Generate N Uniform Random Points in Any Dimensions | |
| trim.rectangle | Cut margins from rectangle | |
| rpoisline | Generate Poisson Random Line Process | |
| BadGey | Hybrid Geyer Point Process Model | |
| varblock | Estimate Variance of Summary Statistic by Subdivision | |
| split.ppx | Divide Multidimensional Point Pattern into Sub-patterns | |
| as.rectangle | Window Frame | |
| square | Square Window | |
| beginner | Print Introduction For Beginners | |
| vertices | Vertices of a Window | |
| MultiHard | The Multitype Hard Core Point Process Model | |
| redwood | California Redwoods Point Pattern (Ripley's Subset) | |
| redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
| summary.ppp | Summary of a Point Pattern Dataset | |
| WindowOnly | Extract Window of Spatial Object | |
| closepairs | Close Pairs of Points | |
| residuals.ppm | Residuals for Fitted Point Process Model | |
| summary.im | Summarizing a Pixel Image | |
| berman.test | Berman's Tests for Point Process Model | |
| waka | Trees in Waka national park | |
| Pairwise | Generic Pairwise Interaction model | |
| bw.smoothppp | Cross Validated Bandwidth Selection for Spatial Smoothing | |
| areaGain | Difference of Disc Areas | |
| tess | Create a Tessellation | |
| rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |
| clarkevans | Clark and Evans Aggregation Index | |
| Extract.im | Extract Subset of Image | |
| run.simplepanel | Run Point-and-Click Interface | |
| boundingbox | Bounding Box of a Window, Image, or Point Pattern | |
| coef.ppm | Coefficients of Fitted Point Process Model | |
| methods.pp3 | Methods for three-dimensional point patterns | |
| rescale | Convert dataset to another unit of length | |
| reload.or.compute | Compute Unless Previously Saved | |
| residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
| Iest | Estimate the I-function | |
| rotate.ppp | Rotate a Point Pattern | |
| convexhull | Convex Hull | |
| rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |
| rcell | Simulate Baddeley-Silverman Cell Process | |
| vcov.kppm | Variance-Covariance Matrix for a Fitted Cluster Point Process Model | |
| runifpoint | Generate N Uniform Random Points | |
| summary.anylist | Summary of a List of Things | |
| G3est | Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern | |
| Smooth.ppp | Spatial smoothing of observations at irregular points | |
| reflect | Reflect In Origin | |
| rotate | Rotate | |
| rotate.im | Rotate a Pixel Image | |
| Kdot | Multitype K Function (i-to-any) | |
| simba | Simulated data from a two-group experiment with replication within each group. | |
| tile.areas | Compute Areas of Tiles in a Tessellation | |
| bw.frac | Bandwidth Selection Based on Window Geometry | |
| rshift.ppp | Randomly Shift a Point Pattern | |
| append.psp | Combine Two Line Segment Patterns | |
| cauchy.estK | Fit the Neyman-Scott cluster process with Cauchy kernel | |
| Fiksel | The Fiksel Interaction | |
| rlinegrid | Generate grid of parallel lines with random displacement | |
| Extract.solist | Extract or Replace Subset of a List of Spatial Objest | |
| DiggleGratton | Diggle-Gratton model | |
| bw.ppl | Likelihood Cross Validation Bandwidth Selection for Kernel Density | |
| timed | Record the Computation Time | |
| rpoispp | Generate Poisson Point Pattern | |
| Extract.listof | Extract or Replace Subset of a List of Things | |
| rpoislinetess | Poisson Line Tessellation | |
| as.fv | Convert Data To Class fv | |
| rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |
| Jcross | Multitype J Function (i-to-j) | |
| subfits | Extract List of Individual Point Process Models | |
| nbfires | Point Patterns of New Brunswick Forest Fires | |
| panel.contour | Panel Plots using Colour Image or Contour Lines | |
| LambertW | Lambert's W Function | |
| Kmulti | Marked K-Function | |
| scanpp | Read Point Pattern From Data File | |
| sharpen | Data Sharpening of Point Pattern | |
| Kscaled | Locally Scaled K-function | |
| Kest | K-function | |
| Lest | L-function | |
| symbolmap | Graphics Symbol Map | |
| delaunay.distance | Distance on Delaunay Triangulation | |
| affine.linnet | Apply Geometrical Transformations to a Linear Network | |
| unitname | Name for Unit of Length | |
| rescale.im | Convert Pixel Image to Another Unit of Length | |
| cauchy.estpcf | Fit the Neyman-Scott cluster process with Cauchy kernel | |
| clip.infline | Intersect Infinite Straight Lines with a Window | |
| rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |
| npfun | Dummy Function Returns Number of Points | |
| density.ppp | Kernel Smoothed Intensity of Point Pattern | |
| Tstat | Third order summary statistic | |
| corners | Corners of a rectangle | |
| pcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-Type) | |
| whist | Weighted Histogram | |
| diameter | Diameter of an Object | |
| plot.listof | Plot a List of Things | |
| scalardilate | Apply Scalar Dilation | |
| Extract.linnet | Extract Subset of Linear Network | |
| dummify | Convert Data to Numeric Values by Constructing Dummy Variables | |
| scanLRTS | Likelihood Ratio Test Statistic for Scan Test | |
| dirichlet.vertices | Vertices of Dirichlet Tessellation | |
| relrisk.ppm | Parametric Estimate of Spatially-Varying Relative Risk | |
| rsyst | Simulate systematic random point pattern | |
| runifpointOnLines | Generate N Uniform Random Points On Line Segments | |
| rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |
| PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
| Extract.leverage.ppm | Extract Subset of Leverage Object | |
| StraussHard | The Strauss / Hard Core Point Process Model | |
| shift.ppp | Apply Vector Translation To Point Pattern | |
| eval.fv | Evaluate Expression Involving Functions | |
| applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
| anova.slrm | Analysis of Deviance for Spatial Logistic Regression Models | |
| Strauss | The Strauss Point Process Model | |
| suffstat | Sufficient Statistic of Point Process Model | |
| as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |
| rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
| shift | Apply Vector Translation | |
| stratrand | Stratified random point pattern | |
| Extract.quad | Subset of Quadrature Scheme | |
| spatstat.options | Internal Options in Spatstat Package | |
| split.hyperframe | Divide Hyperframe Into Subsets and Reassemble | |
| border | Border Region of a Window | |
| crossdist.lpp | Pairwise distances between two point patterns on a linear network | |
| diameter.owin | Diameter of a Window | |
| superimpose.lpp | Superimpose Several Point Patterns on Linear Network | |
| Frame | Extract or Change the Containing Rectangle of a Spatial Object | |
| thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
| dirichlet | Dirichlet Tessellation of Point Pattern | |
| Gres | Residual G Function | |
| split.ppp | Divide Point Pattern into Sub-patterns | |
| clmfires | Castilla-La Mancha Forest Fires | |
| as.data.frame.im | Convert Pixel Image to Data Frame | |
| by.ppp | Apply a Function to a Point Pattern Broken Down by Factor | |
| rmpoint | Generate N Random Multitype Points | |
| textureplot | Plot Image Using Texture Fill | |
| envelope.pp3 | Simulation Envelopes of Summary Function for 3D Point Pattern | |
| rotate.psp | Rotate a Line Segment Pattern | |
| pp3 | Three Dimensional Point Pattern | |
| formula.fv | Extract or Change the Plot Formula for a Function Value Table | |
| bdist.pixels | Distance to Boundary of Window | |
| rmpoispp | Generate Multitype Poisson Point Pattern | |
| summary.listof | Summary of a List of Things | |
| as.owin | Convert Data To Class owin | |
| rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
| summary.splitppp | Summary of a Split Point Pattern | |
| endpoints.psp | Endpoints of Line Segment Pattern | |
| sumouter | Compute Quadratic Forms | |
| compatible.fv | Test Whether Function Objects Are Compatible | |
| Saturated | Saturated Pairwise Interaction model | |
| Hest | Spherical Contact Distribution Function | |
| clickpoly | Interactively Define a Polygon | |
| eval.im | Evaluate Expression Involving Pixel Images | |
| bw.scott | Scott's Rule for Bandwidth Selection for Kernel Density | |
| shift.psp | Apply Vector Translation To Line Segment Pattern | |
| rthin | Random Thinning | |
| vcov.mppm | Calculate Variance-Covariance Matrix for Fitted Multiple Point Process Model | |
| idw | Inverse-distance weighted smoothing of observations at irregular points | |
| as.linim | Convert to Pixel Image on Linear Network | |
| hyytiala | Scots pines and other trees at Hyytiala | |
| as.data.frame.psp | Coerce Line Segment Pattern to a Data Frame | |
| edge.Ripley | Ripley's Isotropic Edge Correction | |
| texturemap | Texture Map | |
| affine.tess | Apply Geometrical Transformation To Tessellation | |
| solist | List of Two-Dimensional Spatial Objects | |
| finpines | Pine saplings in Finland. | |
| unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
| Extract.msr | Extract Subset of Signed or Vector Measure | |
| letterR | Window in Shape of Letter R | |
| expand.owin | Apply Expansion Rule | |
| markcorrint | Mark Correlation Integral | |
| vargamma.estK | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |
| chicago | Chicago Street Crime Data | |
| runifpoint3 | Generate N Uniform Random Points in Three Dimensions | |
| cells | Biological Cells Point Pattern | |
| is.convex | Test Whether a Window is Convex | |
| HierStrauss | The Hierarchical Strauss Point Process Model | |
| yardstick | Text, Arrow or Scale Bar in a Diagram | |
| bw.stoyan | Stoyan's Rule of Thumb for Bandwidth Selection | |
| AreaInter | The Area Interaction Point Process Model | |
| will.expand | Test Expansion Rule | |
| marks.psp | Marks of a Line Segment Pattern | |
| concatxy | Concatenate x,y Coordinate Vectors | |
| Gcom | Model Compensator of Nearest Neighbour Function | |
| Linhom | L-function | |
| distmap | Distance Map | |
| nearestsegment | Find Line Segment Nearest to Each Point | |
| compareFit | Residual Diagnostics for Multiple Fitted Models | |
| Gmulti | Marked Nearest Neighbour Distance Function | |
| Emark | Diagnostics for random marking | |
| coef.slrm | Coefficients of Fitted Spatial Logistic Regression Model | |
| Lcross.inhom | Inhomogeneous Cross Type L Function | |
| coords | Extract or Change Coordinates of a Spatial or Spatiotemporal Point Pattern | |
| F3est | Empty Space Function of a Three-Dimensional Point Pattern | |
| LennardJones | The Lennard-Jones Potential | |
| waterstriders | Waterstriders data. Three independent replications of a point pattern formed by insects. | |
| Extract.owin | Extract Subset of Window | |
| contour.imlist | Array of Contour Plots | |
| MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
| summary.owin | Summary of a Spatial Window | |
| is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
| kppm | Fit Cluster or Cox Point Process Model | |
| fitted.mppm | Fitted Conditional Intensity for Multiple Point Process Model | |
| Fest | Estimate the Empty Space Function or its Hazard Rate | |
| crossing.psp | Crossing Points of Two Line Segment Patterns | |
| Lcross | Multitype L-function (cross-type) | |
| intersect.owin | Intersection, Union or Set Subtraction of Two Windows | |
| Smooth.msr | Smooth a Signed or Vector-Valued Measure | |
| Smooth.fv | Apply Smoothing to Function Values | |
| linfun | Function on a Linear Network | |
| discpartarea | Area of Part of Disc | |
| unmark | Remove Marks | |
| zapsmall.im | Rounding of Pixel Values | |
| crossdist.psp | Pairwise distances between two different line segment patterns | |
| grow.rectangle | Add margins to rectangle | |
| Finhom | Inhomogeneous Empty Space Function | |
| rho2hat | Smoothed Relative Density of Pairs of Covariate Values | |
| Kmodel | K Function or Pair Correlation Function of a Point Process Model | |
| connected.ppp | Connected components of a point pattern | |
| scan.test | Spatial Scan Test | |
| fvnames | Abbreviations for Groups of Columns in Function Value Table | |
| rshift.psp | Randomly Shift a Line Segment Pattern | |
| kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
| Jest | Estimate the J-function | |
| distfun.lpp | Distance Map on Linear Network | |
| default.rmhcontrol | Set Default Control Parameters for Metropolis-Hastings Algorithm. | |
| affine.lpp | Apply Geometrical Transformations to Point Pattern on a Linear Network | |
| add.texture | Fill Plot With Texture | |
| rjitter | Random Perturbation of a Point Pattern | |
| is.marked | Test Whether Marks Are Present | |
| shapley | Galaxies in the Shapley Supercluster | |
| adaptive.density | Intensity Estimate of Point Pattern Using Tessellation | |
| rotate.owin | Rotate a Window | |
| logLik.slrm | Loglikelihood of Spatial Logistic Regression | |
| DiggleGatesStibbard | Diggle-Gates-Stibbard Point Process Model | |
| integral.im | Integral of a Pixel Image | |
| nndist.pp3 | Nearest neighbour distances in three dimensions | |
| selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
| Poisson | Poisson Point Process Model | |
| layered | Create List of Plotting Layers | |
| stieltjes | Compute Integral of Function Against Cumulative Distribution | |
| latest.news | Print News About Latest Version of Package | |
| Window | Extract or Change the Window of a Spatial Object | |
| addvar | Added Variable Plot for Point Process Model | |
| amacrine | Hughes' Amacrine Cell Data | |
| nnorient | Nearest Neighbour Orientation Distribution | |
| Extract.psp | Extract Subset of Line Segment Pattern | |
| superimpose | Superimpose Several Geometric Patterns | |
| crossdist.pp3 | Pairwise distances between two different three-dimensional point patterns | |
| model.images | Compute Images of Constructed Covariates | |
| plot.ppp | plot a Spatial Point Pattern | |
| pool.quadrattest | Pool Several Quadrat Tests | |
| affine.im | Apply Affine Transformation To Pixel Image | |
| area.owin | Area of a Window | |
| lppm | Fit Point Process Model to Point Pattern on Linear Network | |
| affine.owin | Apply Affine Transformation To Window | |
| Extract.splitppp | Extract or Replace Sub-Patterns | |
| simplepanel | Simple Point-and-Click Interface Panels | |
| envelope.envelope | Recompute Envelopes | |
| iplot | Point and Click Interface for Displaying Spatial Data | |
| layout.boxes | Generate a Row or Column Arrangement of Rectangles. | |
| foo | Foo is Not a Variable | |
| anylist | List of Objects | |
| rknn | Theoretical Distribution of Nearest Neighbour Distance | |
| pairs.im | Scatterplot Matrix for Pixel Images | |
| anova.lppm | ANOVA for Fitted Point Process Models on Linear Network | |
| rlabel | Random Re-Labelling of Point Pattern | |
| anova.ppm | ANOVA for Fitted Point Process Models | |
| heather | Diggle's Heather Data | |
| deriv.fv | Calculate Derivative of Function Values | |
| eroded.areas | Areas of Morphological Erosions | |
| transect.im | Pixel Values Along a Transect | |
| print.ppp | Print Brief Details of a Point Pattern Dataset | |
| methods.objsurf | Methods for Objective Function Surfaces | |
| project2set | Find Nearest Point in a Region | |
| diameter.boxx | Geometrical Calculations for Multi-Dimensional Box | |
| as.hyperframe.ppx | Extract coordinates and marks of multidimensional point pattern | |
| rose | Rose Diagram | |
| eval.linim | Evaluate Expression Involving Pixel Images on Linear Network | |
| dilation | Morphological Dilation | |
| boxx | Multi-Dimensional Box | |
| closing | Morphological Closing | |
| as.polygonal | Convert a Window to a Polygonal Window | |
| Kmodel.ppm | K Function or Pair Correlation Function of Gibbs Point Process model | |
| as.solist | Convert List of Two-Dimensional Spatial Objects | |
| Math.im | S3 Group Generic methods for images | |
| Jdot | Multitype J Function (i-to-any) | |
| as.function.fv | Convert Function Value Table to Function | |
| domain | Extract the Domain of any Spatial Object | |
| im | Create a Pixel Image Object | |
| bramblecanes | Hutchings' Bramble Canes data | |
| is.empty | Test Whether An Object Is Empty | |
| OrdThresh | Ord's Interaction model | |
| K3est | K-function of a Three-Dimensional Point Pattern | |
| Kovesi | Colour Sequences with Uniform Perceptual Contrast | |
| lengths.psp | Lengths of Line Segments | |
| clarkevans.test | Clark and Evans Test | |
| is.multitype | Test whether Object is Multitype | |
| is.marked.ppm | Test Whether A Point Process Model is Marked | |
| convolve.im | Convolution of Pixel Images | |
| pairdist.ppx | Pairwise Distances in Any Dimensions | |
| owin.object | Class owin | |
| levelset | Level Set of a Pixel Image | |
| localpcf | Local pair correlation function | |
| as.box3 | Convert Data to Three-Dimensional Box | |
| thomas.estpcf | Fit the Thomas Point Process by Minimum Contrast | |
| bw.relrisk | Cross Validated Bandwidth Selection for Relative Risk Estimation | |
| markconnect | Mark Connection Function | |
| matchingdist | Distance for a Point Pattern Matching | |
| update.kppm | Update a Fitted Cluster Point Process Model | |
| as.hyperframe | Convert Data to Hyperframe | |
| Gfox | Foxall's Distance Functions | |
| edges2vees | List Dihedral Triples in a Graph | |
| areaLoss | Difference of Disc Areas | |
| union.quad | Union of Data and Dummy Points | |
| distcdf | Distribution Function of Interpoint Distance | |
| is.lpp | Test Whether An Object Is A Point Pattern on a Linear Network | |
| midpoints.psp | Midpoints of Line Segment Pattern | |
| Kres | Residual K Function | |
| vesicles | Vesicles Data | |
| matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
| circumradius | Circumradius of a Window | |
| Ksector | Sector K-function | |
| as.ppp | Convert Data To Class ppp | |
| distfun | Distance Map as a Function | |
| maxnndist | Compute Minimum or Maximum Nearest-Neighbour Distance | |
| Concom | The Connected Component Process Model | |
| psp | Create a Line Segment Pattern | |
| markvario | Mark Variogram | |
| as.ppm | Extract Fitted Point Process Model | |
| beachcolours | Create Colour Scheme for a Range of Numbers | |
| pool.rat | Pool Data from Several Ratio Objects | |
| pairdist.default | Pairwise distances | |
| Extract.layered | Extract or Replace Subset of a Layered Object | |
| edge.Trans | Translation Edge Correction | |
| fasp.object | Function Arrays for Spatial Patterns | |
| circdensity | Density Estimation for Circular Data | |
| rMosaicSet | Mosaic Random Set | |
| Extract.fasp | Extract Subset of Function Array | |
| is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
| pcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Type-i-To-Any-Type) | |
| methods.boxx | Methods for Multi-Dimensional Box | |
| Smoothfun.ppp | Smooth Interpolation of Marks as a Spatial Function | |
| nearest.raster.point | Find Pixel Nearest to a Given Point | |
| centroid.owin | Centroid of a window | |
| longleaf | Longleaf Pines Point Pattern | |
| dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
| multiplicity.ppp | Count Multiplicity of Duplicate Points | |
| Softcore | The Soft Core Point Process Model | |
| Extract.lpp | Extract Subset of Point Pattern on Linear Network | |
| affine.ppp | Apply Affine Transformation To Point Pattern | |
| pairdist.psp | Pairwise distances between line segments | |
| Extract.tess | Extract or Replace Subset of Tessellation | |
| pppmatching.object | Class of Point Matchings | |
| lgcp.estpcf | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| diameter.box3 | Geometrical Calculations for Three-Dimensional Box | |
| ppp | Create a Point Pattern | |
| ppx | Multidimensional Space-Time Point Pattern | |
| clickbox | Interactively Define a Rectangle | |
| compatible | Test Whether Objects Are Compatible | |
| cut.ppp | Classify Points in a Point Pattern | |
| alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern | |
| harmonise.fv | Make Function Tables Compatible | |
| markcorr | Mark Correlation Function | |
| Jinhom | Inhomogeneous J-function | |
| cdf.test | Spatial Distribution Test for Point Pattern or Point Process Model | |
| coef.mppm | Coefficients of Point Process Model Fitted to Multiple Point Patterns | |
| im.apply | Apply Function Pixelwise to List of Images | |
| intensity.ppp | Empirical Intensity of Point Pattern | |
| discretise | Safely Convert Point Pattern Window to Binary Mask | |
| angles.psp | Orientation Angles of Line Segments | |
| compatible.im | Test Whether Pixel Images Are Compatible | |
| as.im | Convert to Pixel Image | |
| methods.fii | Methods for Fitted Interactions | |
| nndensity.ppp | Estimate Intensity of Point Pattern Using Nearest Neighbour Distances | |
| linearpcfdot | Multitype Pair Correlation Function (Dot-type) for Linear Point Pattern | |
| mean.im | Maximum, Minimum, Mean, Median, Range or Sum of Pixel Values in an Image | |
| anemones | Beadlet Anemones Data | |
| harmonise.im | Make Pixel Images Compatible | |
| Extract.influence.ppm | Extract Subset of Influence Object | |
| edges2triangles | List Triangles in a Graph | |
| erosion | Morphological Erosion | |
| nndist | Nearest neighbour distances | |
| predict.mppm | Prediction for Fitted Multiple Point Process Model | |
| demohyper | Demonstration Example of Hyperframe of Spatial Data | |
| methods.rhohat | Methods for Intensity Functions of Spatial Covariate | |
| nncorr | Nearest-Neighbour Correlation Indices of Marked Point Pattern | |
| print.owin | Print Brief Details of a Spatial Window | |
| lansing | Lansing Woods Point Pattern | |
| copper | Berman-Huntington points and lines data | |
| model.matrix.slrm | Extract Design Matrix from Spatial Logistic Regression Model | |
| quadrat.test.splitppp | Dispersion Test of CSR for Split Point Pattern Based on Quadrat Counts | |
| as.interact | Extract Interaction Structure | |
| nnclean | Nearest Neighbour Clutter Removal | |
| Triplets | The Triplet Point Process Model | |
| cut.im | Convert Pixel Image from Numeric to Factor | |
| bdist.points | Distance to Boundary of Window | |
| data.ppm | Extract Original Data from a Fitted Point Process Model | |
| pairdist.ppp | Pairwise distances | |
| default.expand | Default Expansion Rule for Simulation of Model | |
| bei | Tropical rain forest trees | |
| crossdist | Pairwise distances | |
| intensity.quadratcount | Intensity Estimates Using Quadrat Counts | |
| ants | Harkness-Isham ants' nests data | |
| linnet | Create a Linear Network | |
| as.lpp | Convert Data to a Point Pattern on a Linear Network | |
| nndist.ppx | Nearest Neighbour Distances in Any Dimensions | |
| dmixpois | Mixed Poisson Distribution | |
| is.im | Test Whether An Object Is A Pixel Image | |
| nsegments | Number of Line Segments in a Line Segment Pattern | |
| nztrees | New Zealand Trees Point Pattern | |
| quantile.ewcdf | Quantiles of Weighted Empirical Cumulative Distribution Function | |
| methods.ppx | Methods for Multidimensional Space-Time Point Patterns | |
| distmap.owin | Distance Map of Window | |
| pairorient | Point Pair Orientation Distribution | |
| flipxy | Exchange X and Y Coordinates | |
| rGaussPoisson | Simulate Gauss-Poisson Process | |
| crossdist.ppp | Pairwise distances between two different point patterns | |
| as.matrix.owin | Convert Pixel Image to Matrix | |
| paracou | Kimboto trees at Paracou, French Guiana | |
| density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
| chorley | Chorley-Ribble Cancer Data | |
| clickppp | Interactively Add Points | |
| pixellate.owin | Convert Window to Pixel Image | |
| bw.diggle | Cross Validated Bandwidth Selection for Kernel Density | |
| fitted.slrm | Fitted Probabilities for Spatial Logistic Regression | |
| fryplot | Fry Plot of Point Pattern | |
| rat | Ratio object | |
| gridcentres | Rectangular grid of points | |
| as.layered | Convert Data To Layered Object | |
| colourtools | Convert and Compare Colours in Different Formats | |
| collapse.fv | Collapse Several Function Tables into One | |
| box3 | Three-Dimensional Box | |
| incircle | Find Largest Circle Inside Window | |
| diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
| fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
| layerplotargs | Extract or Replace the Plot Arguments of a Layered Object | |
| linim | Create Pixel Image on Linear Network | |
| plot.cdftest | Plot a Spatial Distribution Test | |
| fardist | Farthest Distance to Boundary of Window | |
| relrisk.ppp | Nonparametric Estimate of Spatially-Varying Relative Risk | |
| localKinhom | Inhomogeneous Neighbourhood Density Function | |
| overlap.owin | Compute Area of Overlap | |
| linearpcfcross | Multitype Pair Correlation Function (Cross-type) for Linear Point Pattern | |
| pool.fasp | Pool Data from Several Function Arrays | |
| identify.psp | Identify Segments in a Line Segment Pattern | |
| discs | Union of Discs | |
| as.tess | Convert Data To Tessellation | |
| osteo | Osteocyte Lacunae Data: Replicated Three-Dimensional Point Patterns | |
| closepairs.pp3 | Close Pairs of Points in 3 Dimensions | |
| msr | Signed or Vector-Valued Measure | |
| bind.fv | Combine Function Value Tables | |
| funxy | Spatial Function Class | |
| plot.pp3 | Plot a three-dimensional point pattern | |
| rescue.rectangle | Convert Window Back To Rectangle | |
| profilepl | Profile Maximum Pseudolikelihood or AIC | |
| nnfun | Nearest Neighbour Index Map as a Function | |
| bdist.tiles | Distance to Boundary of Window | |
| opening | Morphological Opening | |
| quadrat.test | Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
| fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |
| gorillas | Gorilla Nesting Sites | |
| plot.ppm | plot a Fitted Point Process Model | |
| linearmarkconnect | Mark Connection Function for Multitype Point Pattern on Linear Network | |
| rQuasi | Generate Quasirandom Point Pattern in Given Window | |
| hopskel | Hopkins-Skellam Test | |
| crossdist.ppx | Pairwise Distances Between Two Different Multi-Dimensional Point Patterns | |
| objsurf | Objective Function Surface | |
| diameter.linnet | Circumradius and Diameter of a Linear Network | |
| increment.fv | Increments of a Function | |
| rStrauss | Perfect Simulation of the Strauss Process | |
| plot.leverage.ppm | Plot Leverage Function | |
| hextess | Hexagonal Grid or Tessellation | |
| plot.colourmap | Plot a Colour Map | |
| dclf.test | Diggle-Cressie-Loosmore-Ford and Maximum Absolute Deviation Tests | |
| gauss.hermite | Gauss-Hermite Quadrature Approximation to Expectation for Normal Distribution | |
| deltametric | Delta Metric | |
| rgbim | Create Colour-Valued Pixel Image | |
| im.object | Class of Images | |
| pixelquad | Quadrature Scheme Based on Pixel Grid | |
| ppm.object | Class of Fitted Point Process Models | |
| intensity.lpp | Empirical Intensity of Point Pattern on Linear Network | |
| simulate.ppm | Simulate a Fitted Gibbs Point Process Model | |
| linearKdot.inhom | Inhomogeneous multitype K Function (Dot-type) for Linear Point Pattern | |
| model.frame.ppm | Extract the Variables in a Point Process Model | |
| distmap.ppp | Distance Map of Point Pattern | |
| dilated.areas | Areas of Morphological Dilations | |
| eval.fasp | Evaluate Expression Involving Function Arrays | |
| summary.psp | Summary of a Line Segment Pattern Dataset | |
| disc | Circular Window | |
| linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |
| inforder.family | Infinite Order Interaction Family | |
| invoke.symbolmap | Plot Data Using Graphics Symbol Map | |
| methods.box3 | Methods for Three-Dimensional Box | |
| pairsat.family | Saturated Pairwise Interaction Point Process Family | |
| is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
| murchison | Murchison gold deposits | |
| japanesepines | Japanese Pines Point Pattern | |
| plot.linim | Plot Pixel Image on Linear Network | |
| linearK | Linear K Function | |
| inside.owin | Test Whether Points Are Inside A Window | |
| nncross.pp3 | Nearest Neighbours Between Two Patterns in 3D | |
| demopat | Artificial Data Point Pattern | |
| ponderosa | Ponderosa Pine Tree Point Pattern | |
| rDiggleGratton | Perfect Simulation of the Diggle-Gratton Process | |
| hybrid.family | Hybrid Interaction Family | |
| intensity.ppm | Intensity of Fitted Point Process Model | |
| infline | Infinite Straight Lines | |
| plot.kppm | Plot a fitted cluster point process | |
| eem | Exponential Energy Marks | |
| summary.quad | Summarizing a Quadrature Scheme | |
| lpp | Create Point Pattern on Linear Network | |
| rCauchy | Simulate Neyman-Scott Point Process with Cauchy cluster kernel | |
| plot.quadratcount | Plot Quadrat Counts | |
| influence.ppm | Influence Measure for Spatial Point Process Model | |
| intersect.tess | Intersection of Two Tessellations | |
| rSSI | Simulate Simple Sequential Inhibition | |
| linearKinhom | Inhomogeneous Linear K Function | |
| rPoissonCluster | Simulate Poisson Cluster Process | |
| is.rectangle | Determine Type of Window | |
| ippm | Fit Point Process Model Involving Irregular Trend Parameters | |
| update.rmhcontrol | Update Control Parameters of Metropolis-Hastings Algorithm | |
| ewcdf | Weighted Empirical Cumulative Distribution Function | |
| formula.ppm | Model Formulae for Gibbs Point Process Models | |
| methods.kppm | Methods for Cluster Point Process Models | |
| psstA | Pseudoscore Diagnostic For Fitted Model against Area-Interaction Alternative | |
| methods.slrm | Methods for Spatial Logistic Regression Models | |
| rMosaicField | Mosaic Random Field | |
| localK | Neighbourhood density function | |
| is.ppp | Test Whether An Object Is A Point Pattern | |
| is.owin | Test Whether An Object Is A Window | |
| methods.rho2hat | Methods for Intensity Functions of Two Spatial Covariates | |
| lohboot | Bootstrap Confidence Bands for Summary Function | |
| logLik.ppm | Log Likelihood and AIC for Point Process Model | |
| methods.layered | Methods for Layered Objects | |
| nndist.lpp | Nearest neighbour distances on a linear network | |
| padimage | Pad the Border of a Pixel Image | |
| vcov.slrm | Variance-Covariance Matrix for a Fitted Spatial Logistic Regression | |
| with.hyperframe | Evaluate an Expression in Each Row of a Hyperframe | |
| pairwise.family | Pairwise Interaction Process Family | |
| gordon | People in Gordon Square | |
| perspPoints | Draw Points or Lines on a Surface Viewed in Perspective | |
| rMatClust | Simulate Matern Cluster Process | |
| npoints | Number of Points in a Point Pattern | |
| hierpair.family | Hierarchical Pairwise Interaction Process Family | |
| range.fv | Range of Function Values | |
| Extract.anylist | Extract or Replace Subset of a List of Things | |
| plot.layered | Layered Plot | |
| pcfcross | Multitype pair correlation function (cross-type) | |
| model.depends | Identify Covariates Involved in each Model Term | |
| nnmap | K-th Nearest Point Map | |
| plot.msr | Plot a Signed or Vector-Valued Measure | |
| mucosa | Cells in Gastric Mucosa | |
| nncross.lpp | Nearest Neighbours on a Linear Network | |
| linearpcf | Linear Pair Correlation Function | |
| nnwhich.ppx | Nearest Neighbours in Any Dimensions | |
| Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
| nnwhich.pp3 | Nearest neighbours in three dimensions | |
| pairdist.pp3 | Pairwise distances in Three Dimensions | |
| nnwhich.lpp | Identify Nearest Neighbours on a Linear Network | |
| pixellate.ppp | Convert Point Pattern to Pixel Image | |
| Hardcore | The Hard Core Point Process Model | |
| identify.ppp | Identify Points in a Point Pattern | |
| linearpcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Dot-type) for Linear Point Pattern | |
| pixellate.psp | Convert Line Segment Pattern to Pixel Image | |
| logLik.mppm | Log Likelihood for Poisson Point Process Model | |
| imcov | Spatial Covariance of a Pixel Image | |
| persp.im | Perspective Plot of Pixel Image | |
| is.subset.owin | Determine Whether One Window is Contained In Another | |
| pixellate | Convert Spatial Object to Pixel Image | |
| methods.lpp | Methods for Point Patterns on a Linear Network | |
| plot.fv | Plot Function Values | |
| pcf.ppp | Pair Correlation Function of Point Pattern | |
| plot.quad | Plot a Spatial Quadrature Scheme | |
| plot.psp | plot a Spatial Line Segment Pattern | |
| plot.anylist | Plot a List of Things | |
| plot.yardstick | Plot a Yardstick or Scale Bar | |
| ord.family | Ord Interaction Process Family | |
| quad.object | Class of Quadrature Schemes | |
| pppdist | Distance Between Two Point Patterns | |
| nnfun.lpp | Nearest Neighbour Map on Linear Network | |
| pool.envelope | Pool Data from Several Envelopes | |
| psp.object | Class of Line Segment Patterns | |
| pcf | Pair Correlation Function | |
| Kcross.inhom | Inhomogeneous Cross K Function | |
| plot.solist | Plot a List of Spatial Objects | |
| MultiStrauss | The Multitype Strauss Point Process Model | |
| Replace.im | Reset Values in Subset of Image | |
| quasirandom | Quasirandom Patterns | |
| project.ppm | Force Point Process Model to be Valid | |
| plot.scan.test | Plot Result of Scan Test | |
| quadrat.test.mppm | Chi-Squared Test for Multiple Point Process Model Based on Quadrat Counts | |
| pixelcentres | Extract Pixel Centres as Point Pattern | |
| rMaternI | Simulate Matern Model I | |
| pool | Pool Data | |
| dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
| psst | Pseudoscore Diagnostic For Fitted Model against General Alternative | |
| plot.lpp | Plot Point Pattern on Linear Network | |
| pairdist | Pairwise distances | |
| edges | Extract Boundary Edges of a Window. | |
| ellipse | Elliptical Window. | |
| allstats | Calculate four standard summary functions of a point pattern. | |
| plot.owin | Plot a Spatial Window | |
| as.matrix.im | Convert Pixel Image to Matrix or Array | |
| exactMPLEstrauss | Exact Maximum Pseudolikelihood Estimate for Stationary Strauss Process | |
| rMaternII | Simulate Matern Model II | |
| plot.lppm | Plot a Fitted Point Process Model on a Linear Network | |
| pcfdot | Multitype pair correlation function (i-to-any) | |
| perimeter | Perimeter Length of Window | |
| print.quad | Print a Quadrature Scheme | |
| pointsOnLines | Place Points Evenly Along Specified Lines | |
| plot.textstring | Plot a Text String | |
| gridweights | Compute Quadrature Weights Based on Grid Counts | |
| pyramidal | Pyramidal Neurons in Cingulate Cortex | |
| project2segment | Move Point To Nearest Line | |
| predict.kppm | Prediction from a Fitted Cluster Point Process Model | |
| quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
| print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
| quadscheme.logi | Generate a Logistic Regression Quadrature Scheme from a Point Pattern | |
| predict.ppm | Prediction from a Fitted Point Process Model | |
| rLGCP | Simulate Log-Gaussian Cox Process | |
| as.mask | Pixel Image Approximation of a Window | |
| blur | Apply Gaussian Blur to a Pixel Image | |
| by.im | Apply Function to Image Broken Down by Factor | |
| quadratcount | Quadrat counting for a point pattern | |
| harmonise | Make Objects Compatible | |
| interp.im | Interpolate a Pixel Image | |
| clickjoin | Interactively join vertices on a plot | |
| convexhull.xy | Convex Hull of Points | |
| km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
| linearKcross | Multitype K Function (Cross-type) for Linear Point Pattern | |
| rDGS | Perfect Simulation of the Diggle-Gates-Stibbard Process | |
| rThomas | Simulate Thomas Process | |
| plot.quadrattest | Display the result of a quadrat counting test. | |
| linearKcross.inhom | Inhomogeneous multitype K Function (Cross-type) for Linear Point Pattern | |
| fv | Create a Function Value Table | |
| fv.object | Function Value Table | |
| leverage.ppm | Leverage Measure for Spatial Point Process Model | |
| linearpcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-type) for Linear Point Pattern | |
| istat | Point and Click Interface for Exploratory Analysis of Point Pattern | |
| is.marked.ppp | Test Whether A Point Pattern is Marked | |
| lurking | Lurking variable plot | |
| marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern | |
| methods.funxy | Methods for Spatial Functions | |
| methods.linfun | Methods for Functions on Linear Network | |
| marks | Marks of a Point Pattern | |
| moribund | Outdated Functions | |
| plot.mppm | plot a Fitted Multiple Point Process Model | |
| methods.units | Methods for Units | |
| plot.texturemap | Plot a Texture Map | |
| linearKdot | Multitype K Function (Dot-type) for Linear Point Pattern | |
| owin | Create a Window | |
| quantile.im | Sample Quantiles of Pixel Image | |
| periodify | Make Periodic Copies of a Spatial Pattern | |
| plot.hyperframe | Plot Entries in a Hyperframe | |
| pcfinhom | Inhomogeneous Pair Correlation Function | |
| plot.symbolmap | Plot a Graphics Symbol Map | |
| plot.tess | Plot a tessellation | |
| quadrats | Divide Region into Quadrats | |
| rHardcore | Perfect Simulation of the Hardcore Process | |
| psstG | Pseudoscore Diagnostic For Fitted Model against Saturation Alternative | |
| quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
| humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
| reduced.sample | Reduced Sample Estimator using Histogram Data | |
| ripras | Estimate window from points alone | |
| rotmean | Rotational Average of a Pixel Image | |
| swedishpines | Swedish Pines Point Pattern | |
| Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
| Gest | Nearest Neighbour Distance Function G | |
| vargamma.estpcf | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |
| cbind.hyperframe | Combine Hyperframes by Rows or by Columns | |
| cdf.test.mppm | Spatial Distribution Test for Multiple Point Process Model | |
| bounding.box.xy | Convex Hull of Points | |
| complement.owin | Take Complement of a Window | |
| crossdist.default | Pairwise distances between two different sets of points | |
| dfbetas.ppm | Parameter influence measure | |
| distmap.psp | Distance Map of Line Segment Pattern | |
| envelope.lpp | Envelope for Point Patterns on Linear Network | |
| integral.msr | Integral of a Measure | |
| lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| model.matrix.ppm | Extract Design Matrix from Point Process Model | |
| methods.lppm | Methods for Fitted Point Process Models on a Linear Network | |
| methods.linnet | Methods for Linear Networks | |
| parres | Partial Residuals for Point Process Model | |
| plot.onearrow | Plot an Arrow | |
| plot.splitppp | Plot a List of Point Patterns | |
| pppmatching | Create a Point Matching | |
| quadratresample | Resample a Point Pattern by Resampling Quadrats | |
| rStraussHard | Perfect Simulation of the Strauss-Hardcore Process | |
| reach | Interaction Distance of a Point Process | |
| rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
| spruces | Spruces Point Pattern | |
| unnormdensity | Weighted kernel smoother | |
| stienen | Stienen Diagram | |
| Ginhom | Inhomogeneous Nearest Neighbour Function | |
| Extract.ppp | Extract or Replace Subset of Point Pattern | |
| Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
| Kcross | Multitype K Function (Cross-type) | |
| Kmeasure | Reduced Second Moment Measure | |
| bdspots | Breakdown Spots in Microelectronic Materials | |
| contour.im | Contour plot of pixel image | |
| dclf.progress | Progress Plot of Test of Spatial Pattern | |
| delaunay | Delaunay Triangulation of Point Pattern | |
| flu | Influenza Virus Proteins | |
| hyperframe | Hyper Data Frame | |
| improve.kppm | Improve Intensity Estimate of Fitted Cluster Point Process Model | |
| is.stationary | Recognise Stationary and Poisson Point Process Models | |
| lut | Lookup Tables | |
| markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
| mppm | Fit Point Process Model to Several Point Patterns | |
| lineardisc | Compute Disc of Given Radius in Linear Network | |
| nnwhich | Nearest neighbour | |
| pcfmulti | Marked pair correlation function | |
| plot.fasp | Plot a Function Array | |
| plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
| rcellnumber | Generate Random Numbers of Points for Cell Process | |
| rstrat | Simulate Stratified Random Point Pattern | |
| setcov | Set Covariance of a Window | |
| simplenet | Simple Example of Linear Network | |
| simdat | Simulated Point Pattern | |
| vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
| Ldot.inhom | Inhomogeneous Multitype L Dot Function | |
| as.mask.psp | Convert Line Segment Pattern to Binary Pixel Mask | |
| compatible.fasp | Test Whether Function Arrays Are Compatible | |
| default.dummy | Generate a Default Pattern of Dummy Points | |
| duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
| effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model | |
| hamster | Aherne's hamster tumour data | |
| envelope | Simulation Envelopes of Summary Function | |
| harmonic | Basis for Harmonic Functions | |
| intensity | Intensity of a Dataset or a Model | |
| is.hybrid | Test Whether Object is a Hybrid | |
| ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
| matclust.estpcf | Fit the Matern Cluster Point Process by Minimum Contrast Using Pair Correlation | |
| mincontrast | Method of Minimum Contrast | |
| linearmarkequal | Mark Connection Function for Multitype Point Pattern on Linear Network | |
| nncross | Nearest Neighbours Between Two Patterns | |
| nndist.psp | Nearest neighbour distances between line segments | |
| nnmark | Mark of Nearest Neighbour | |
| plot.envelope | Plot a Simulation Envelope | |
| plot.im | Plot a Pixel Image | |
| ppm.ppp | Fit Point Process Model to Point Pattern Data | |
| print.ppm | Print a Fitted Point Process Model | |
| rVarGamma | Simulate Neyman-Scott Point Process with Variance Gamma cluster kernel | |
| predict.lppm | Predict Point Process Model on Linear Network | |
| plot.imlist | Plot a List of Images | |
| simulate.kppm | Simulate a Fitted Cluster Point Process Model | |
| spokes | Spokes pattern of dummy points | |
| triplet.family | Triplet Interaction Family | |
| urkiola | Urkiola Woods Point Pattern | |
| Kinhom | Inhomogeneous K-function | |
| Smooth | Spatial smoothing of data | |
| SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model | |
| Ord | Generic Ord Interaction model | |
| affine.psp | Apply Affine Transformation To Line Segment Pattern | |
| as.psp | Convert Data To Class psp | |
| betacells | Beta Ganglion Cells in Cat Retina | |
| bronzefilter | Bronze gradient filter data | |
| chop.tess | Subdivide a Window or Tessellation using a Set of Lines | |
| commonGrid | Determine A Common Spatial Domain And Pixel Resolution | |
| colourmap | Colour Lookup Tables | |
| connected | Connected components | |
| clusterset | Allard-Fraley Estimator of Cluster Feature | |
| density.psp | Kernel Smoothing of Line Segment Pattern | |
| hist.im | Histogram of Pixel Values in an Image | |
| interp.colourmap | Interpolate smoothly between specified colours | |
| miplot | Morisita Index Plot | |
| is.dppm | Recognise Fitted Determinantal Point Process Models | |
| pairdist.lpp | Pairwise shortest-path distances between points on a linear network | |
| pcf.fasp | Pair Correlation Function obtained from array of K functions | |
| pcf.fv | Pair Correlation Function obtained from K Function | |
| pcf3est | Pair Correlation Function of a Three-Dimensional Point Pattern | |
| plot.bermantest | Plot Result of Berman Test | |
| plot.influence.ppm | Plot Influence Measure | |
| plot.linnet | Plot a linear network | |
| predict.slrm | Predicted or Fitted Values from Spatial Logistic Regression | |
| print.im | Print Brief Details of an Image | |
| progressreport | Print Progress Reports | |
| rNeymanScott | Simulate Neyman-Scott Process | |
| plot.slrm | Plot a Fitted Spatial Logistic Regression | |
| ppm | Fit Point Process Model to Data | |
| ppp.object | Class of Point Patterns | |
| qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
| raster.x | Cartesian Coordinates for a Pixel Raster | |
| No Results! | ||
Last month downloads
Details
| Nickname | Do The Maths |
| Date | 2014-12-31 |
| License | GPL (>= 2) |
| URL | http://www.spatstat.org |
| LazyData | true |
| NeedsCompilation | yes |
| ByteCompile | true |
| Packaged | 2014-12-31 04:28:53 UTC; adrian |
| Repository | CRAN |
| Date/Publication | 2014-12-31 10:17:05 |
| 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 |
Include our badge in your README
[](http://www.rdocumentation.org/packages/spatstat)