spatstat v1.39-0
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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 | |
| Jcross | Multitype J Function (i-to-j) | |
| F3est | Empty Space Function of a Three-Dimensional Point Pattern | |
| Extract.fv | Extract or Replace Subset of Function Values | |
| append.psp | Combine Two Line Segment Patterns | |
| Extract.ppp | Extract or Replace Subset of Point Pattern | |
| Extract.quad | Subset of Quadrature Scheme | |
| Extract.msr | Extract Subset of Signed or Vector Measure | |
| Ginhom | Inhomogeneous Nearest Neighbour Function | |
| Concom | The Connected Component Process Model | |
| dilation | Morphological Dilation | |
| BadGey | Hybrid Geyer Point Process Model | |
| LambertW | Lambert's W Function | |
| compatible.im | Test Whether Pixel Images Are Compatible | |
| allstats | Calculate four standard summary functions of a point pattern. | |
| Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
| Ord | Generic Ord Interaction model | |
| Extract.linnet | Extract Subset of Linear Network | |
| coef.ppm | Coefficients of Fitted Point Process Model | |
| affine.tess | Apply Geometrical Transformation To Tessellation | |
| Gest | Nearest Neighbour Distance Function G | |
| envelope.lpp | Envelope for Point Patterns on Linear Network | |
| affine.psp | Apply Affine Transformation To Line Segment Pattern | |
| Extract.leverage.ppm | Extract Subset of Leverage Object | |
| eval.im | Evaluate Expression Involving Pixel Images | |
| Extract.owin | Extract Subset of Window | |
| clarkevans.test | Clark and Evans Test | |
| edges2triangles | List Triangles in a Graph | |
| Strauss | The Strauss Point Process Model | |
| colourmap | Colour Lookup Tables | |
| Geyer | Geyer's Saturation Point Process Model | |
| concatxy | Concatenate x,y Coordinate Vectors | |
| anova.mppm | ANOVA for Fitted Multiple Point Process Models | |
| as.function.fv | Convert Function Value Table to Function | |
| cut.ppp | Classify Points in a Point Pattern | |
| Extract.hyperframe | Extract or Replace Subset of Hyperframe | |
| bronzefilter | Bronze gradient filter data | |
| identify.psp | Identify Segments in a Line Segment Pattern | |
| Linhom | L-function | |
| Ldot.inhom | Inhomogeneous Multitype L Dot Function | |
| eval.fasp | Evaluate Expression Involving Function Arrays | |
| Ldot | Multitype L-function (i-to-any) | |
| edge.Trans | Translation Edge Correction | |
| Kmodel | K Function or Pair Correlation Function of a Point Process Model | |
| affine.ppp | Apply Affine Transformation To Point Pattern | |
| Tstat | Third order summary statistic | |
| Fest | Estimate the Empty Space Function or its Hazard Rate | |
| bei | Tropical rain forest trees | |
| fv.object | Function Value Table | |
| areaLoss | Difference of Disc Areas | |
| OrdThresh | Ord's Interaction model | |
| intersect.tess | Intersection of Two Tessellations | |
| coef.slrm | Coefficients of Fitted Spatial Logistic Regression Model | |
| effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model | |
| as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |
| dmixpois | Mixed Poisson Distribution | |
| Hybrid | Hybrid Interaction Point Process Model | |
| as.mask.psp | Convert Line Segment Pattern to Binary Pixel Mask | |
| affine.linnet | Apply Geometrical Transformations to a Linear Network | |
| K3est | K-function of a Three-Dimensional Point Pattern | |
| hist.im | Histogram of Pixel Values in an Image | |
| anova.slrm | Analysis of Deviance for Spatial Logistic Regression Models | |
| bdist.tiles | Distance to Boundary of Window | |
| dilated.areas | Areas of Morphological Dilations | |
| beginner | Print Introduction For Beginners | |
| affine | Apply Affine Transformation | |
| dummify | Convert Data to Numeric Values by Constructing Dummy Variables | |
| anemones | Beadlet Anemones Data | |
| box3 | Three-Dimensional Box | |
| applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
| Extract.splitppp | Extract or Replace Sub-Patterns | |
| Extract.layered | Extract Subset of a Layered Object | |
| Hardcore | The Hard Core Point Process Model | |
| berman.test | Berman's Tests for Point Process Model | |
| Kcross.inhom | Inhomogeneous Cross K Function | |
| DiggleGatesStibbard | Diggle-Gates-Stibbard Point Process Model | |
| hopskel | Hopkins-Skellam Test | |
| Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
| affine.lpp | Apply Geometrical Transformations to Point Pattern on a Linear Network | |
| Extract.solist | Extract or Replace Subset of a List of Spatial Objest | |
| density.ppp | Kernel Smoothed Intensity of Point Pattern | |
| dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
| im.object | Class of Images | |
| fryplot | Fry Plot of Point Pattern | |
| closepairs | Close Pairs of Points | |
| fv | Create a Function Value Table | |
| dirichlet | Dirichlet Tessellation of Point Pattern | |
| Lcross | Multitype L-function (cross-type) | |
| Extract.im | Extract Subset of Image | |
| clusterset | Allard-Fraley Estimator of Cluster Feature | |
| bounding.box.xy | Convex Hull of Points | |
| clip.infline | Intersect Infinite Straight Lines with a Window | |
| Smooth.msr | Smooth a Signed or Vector-Valued Measure | |
| bdist.points | Distance to Boundary of Window | |
| ewcdf | Weighted Empirical Cumulative Distribution Function | |
| dirichlet.vertices | Vertices of Dirichlet Tessellation | |
| AreaInter | The Area Interaction Point Process Model | |
| Smooth.fv | Apply Smoothing to Function Values | |
| Kest | K-function | |
| as.polygonal | Convert a Window to a Polygonal Window | |
| cdf.test | Spatial Distribution Test for Point Pattern or Point Process Model | |
| by.ppp | Apply a Function to a Point Pattern Broken Down by Factor | |
| areaGain | Difference of Disc Areas | |
| exactMPLEstrauss | Exact Maximum Pseudolikelihood Estimate for Stationary Strauss Process | |
| bw.ppl | Likelihood Cross Validation Bandwidth Selection for Kernel Density | |
| im | Create a Pixel Image Object | |
| ants | Harkness-Isham ants' nests data | |
| gridweights | Compute Quadrature Weights Based on Grid Counts | |
| bw.smoothppp | Cross Validated Bandwidth Selection for Spatial Smoothing | |
| harmonic | Basis for Harmonic Functions | |
| as.hyperframe.ppx | Extract coordinates and marks of multidimensional point pattern | |
| clickpoly | Interactively Define a Polygon | |
| as.mask | Pixel Image Approximation of a Window | |
| bw.frac | Bandwidth Selection Based on Window Geometry | |
| crossdist.default | Pairwise distances between two different sets of points | |
| cut.im | Convert Pixel Image from Numeric to Factor | |
| DiggleGratton | Diggle-Gratton model | |
| Jmulti | Marked J Function | |
| integral.msr | Integral of a Measure | |
| crossdist.pp3 | Pairwise distances between two different three-dimensional point patterns | |
| Saturated | Saturated Pairwise Interaction model | |
| funxy | Spatial Function Class | |
| dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
| linearmarkequal | Mark Connection Function for Multitype Point Pattern on Linear Network | |
| dfbetas.ppm | Parameter influence measure | |
| Lcross.inhom | Inhomogeneous Cross Type L Function | |
| duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
| gridcentres | Rectangular grid of points | |
| crossdist.psp | Pairwise distances between two different line segment patterns | |
| as.owin | Convert Data To Class owin | |
| fvnames | Abbreviations for Groups of Columns in Function Value Table | |
| boxx | Multi-Dimensional Box | |
| envelope.envelope | Recompute Envelopes | |
| clmfires | Castilla-La Mancha Forest Fires | |
| diameter.linnet | Circumradius and Diameter of a Linear Network | |
| kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
| anova.ppm | ANOVA for Fitted Point Process Models | |
| closing | Morphological Closing | |
| edge.Ripley | Ripley's Isotropic Edge Correction | |
| affine.owin | Apply Affine Transformation To Window | |
| corners | Corners of a rectangle | |
| as.interact | Extract Interaction Structure | |
| deriv.fv | Calculate Derivative of Function Values | |
| bdist.pixels | Distance to Boundary of Window | |
| linearpcfcross | Multitype Pair Correlation Function (Cross-type) for Linear Point Pattern | |
| influence.ppm | Influence Measure for Spatial Point Process Model | |
| diameter.owin | Diameter of a Window | |
| fardist | Farthest Distance to Boundary of Window | |
| hamster | Aherne's hamster tumour data | |
| add.texture | Fill Plot With Texture | |
| area.owin | Area of a Window | |
| inforder.family | Infinite Order Interaction Family | |
| cauchy.estpcf | Fit the Neyman-Scott cluster process with Cauchy kernel | |
| dclf.progress | Progress Plot of Test of Spatial Pattern | |
| WindowOnly | Extract Window of Spatial Object | |
| collapse.fv | Collapse Several Function Tables into One | |
| as.fv | Convert Data To Class fv | |
| LennardJones | The Lennard-Jones Potential | |
| as.matrix.owin | Convert Pixel Image to Matrix | |
| as.data.frame.hyperframe | Coerce Hyperframe to Data Frame | |
| integral.im | Integral of a Pixel Image | |
| as.box3 | Convert Data to Three-Dimensional Box | |
| interp.colourmap | Interpolate smoothly between specified colours | |
| as.layered | Convert Data To Layered Object | |
| Softcore | The Soft Core Point Process Model | |
| blur | Apply Gaussian Blur to a Pixel Image | |
| Kcom | Model Compensator of K Function | |
| erosion | Morphological Erosion | |
| as.ppp | Convert Data To Class ppp | |
| hyperframe | Hyper Data Frame | |
| border | Border Region of a Window | |
| convexhull.xy | Convex Hull of Points | |
| distcdf | Distribution Function of Interpoint Distance | |
| Kres | Residual K Function | |
| formula.ppm | Model Formulae for Gibbs Point Process Models | |
| interp.im | Interpolate a Pixel Image | |
| colourtools | Convert and Compare Colours in Different Formats | |
| bramblecanes | Hutchings' Bramble Canes data | |
| is.owin | Test Whether An Object Is A Window | |
| is.rectangle | Determine Type of Window | |
| Window | Extract or Change the Window of a Spatial Object | |
| distmap.psp | Distance Map of Line Segment Pattern | |
| coords | Extract or Change Coordinates of a Spatial or Spatiotemporal Point Pattern | |
| harmonise | Make Objects Compatible | |
| commonGrid | Determine A Common Spatial Domain And Pixel Resolution | |
| lgcp.estpcf | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| grow.rectangle | Add margins to rectangle | |
| Kest.fft | K-function using FFT | |
| delaunay | Delaunay Triangulation of Point Pattern | |
| domain | Extract the Domain of any Spatial Object | |
| density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
| is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
| clickbox | Interactively Define a Rectangle | |
| discs | Union of Discs | |
| markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
| Kmeasure | Reduced Second Moment Measure | |
| methods.rho2hat | Methods for Intensity Functions of Two Spatial Covariates | |
| as.hyperframe | Convert Data to Hyperframe | |
| linearKcross | Multitype K Function (Cross-type) for Linear Point Pattern | |
| intensity.lpp | Empirical Intensity of Point Pattern on Linear Network | |
| imcov | Spatial Covariance of a Pixel Image | |
| demopat | Artificial Data Point Pattern | |
| lpp | Create Point Pattern on Linear Network | |
| nnfun | Nearest Neighbour Index Map as a Function | |
| fitted.slrm | Fitted Probabilities for Spatial Logistic Regression | |
| crossdist.lpp | Pairwise distances between two point patterns on a linear network | |
| distmap | Distance Map | |
| crossdist.ppx | Pairwise Distances Between Two Different Multi-Dimensional Point Patterns | |
| invoke.symbolmap | Plot Data Using Graphics Symbol Map | |
| diameter.box3 | Geometrical Calculations for Three-Dimensional Box | |
| compatible.fv | Test Whether Function Objects Are Compatible | |
| copper | Berman-Huntington points and lines data | |
| linearmarkconnect | Mark Connection Function for Multitype Point Pattern on Linear Network | |
| is.marked.ppp | Test Whether A Point Pattern is Marked | |
| increment.fv | Increments of a Function | |
| as.ppm | Extract Fitted Point Process Model | |
| linearpcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Dot-type) for Linear Point Pattern | |
| methods.boxx | Methods for Multi-Dimensional Box | |
| clickppp | Interactively Add Points | |
| is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
| density.psp | Kernel Smoothing of Line Segment Pattern | |
| msr | Signed or Vector-Valued Measure | |
| linearpcfdot | Multitype Pair Correlation Function (Dot-type) for Linear Point Pattern | |
| nndist | Nearest neighbour distances | |
| pixellate.ppp | Convert Point Pattern to Pixel Image | |
| bw.diggle | Cross Validated Bandwidth Selection for Kernel Density | |
| moribund | Outdated Functions | |
| Fiksel | The Fiksel Interaction | |
| intensity.ppm | Intensity of Fitted Point Process Model | |
| SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model | |
| chicago | Chicago Street Crime Data | |
| linearKdot.inhom | Inhomogeneous multitype K Function (Dot-type) for Linear Point Pattern | |
| cauchy.estK | Fit the Neyman-Scott cluster process with Cauchy kernel | |
| miplot | Morisita Index Plot | |
| nnclean | Nearest Neighbour Clutter Removal | |
| distfun.lpp | Distance Map on Linear Network | |
| lohboot | Bootstrap Confidence Bands for Summary Function | |
| as.im | Convert to Pixel Image | |
| formula.fv | Extract or Change the Plot Formula for a Function Value Table | |
| Frame | Extract or Change the Containing Rectangle of a Spatial Object | |
| as.data.frame.im | Convert Pixel Image to Data Frame | |
| methods.rhohat | Methods for Intensity Functions of Spatial Covariate | |
| is.convex | Test Whether a Window is Convex | |
| nearest.raster.point | Find Pixel Nearest to a Given Point | |
| coef.mppm | Coefficients of Point Process Model Fitted to Multiple Point Patterns | |
| km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
| pcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Type-i-To-Any-Type) | |
| matchingdist | Distance for a Point Pattern Matching | |
| as.tess | Convert Data To Tessellation | |
| as.rectangle | Window Frame | |
| Kmodel.kppm | K Function or Pair Correlation Function of Cluster Model or Cox model | |
| lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
| nndensity.ppp | Estimate Intensity of Point Pattern Using Nearest Neighbour Distances | |
| angles.psp | Orientation Angles of Line Segments | |
| lurking | Lurking variable plot | |
| methods.funxy | Methods for Spatial Functions | |
| centroid.owin | Centroid of a window | |
| model.matrix.ppm | Extract Design Matrix from Point Process Model | |
| delaunay.distance | Distance on Delaunay Triangulation | |
| edges | Extract Boundary Edges of a Window. | |
| as.data.frame.psp | Coerce Line Segment Pattern to a Data Frame | |
| layerplotargs | Extract or Replace the Plot Arguments of a Layered Object | |
| im.apply | Apply Function Pixelwise to List of Images | |
| flipxy | Exchange X and Y Coordinates | |
| nncorr | Nearest-Neighbour Correlation Indices of Marked Point Pattern | |
| linearK | Linear K Function | |
| letterR | Window in Shape of Letter R | |
| Kinhom | Inhomogeneous K-function | |
| markcorrint | Mark Correlation Integral | |
| cdf.test.mppm | Spatial Distribution Test for Multiple Point Process Model | |
| edges2vees | List Dihedral Triples in a Graph | |
| G3est | Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern | |
| linearKcross.inhom | Inhomogeneous multitype K Function (Cross-type) for Linear Point Pattern | |
| nndist.psp | Nearest neighbour distances between line segments | |
| model.images | Compute Images of Constructed Covariates | |
| logLik.mppm | Log Likelihood for Poisson Point Process Model | |
| eroded.areas | Areas of Morphological Erosions | |
| chop.tess | Subdivide a Window or Tessellation using a Set of Lines | |
| default.rmhcontrol | Set Default Control Parameters for Metropolis-Hastings Algorithm. | |
| hextess | Hexagonal Grid or Tessellation | |
| demohyper | Demonstration Example of Hyperframe of Spatial Data | |
| contour.listof | Plot a List of Things | |
| harmonise.im | Make Pixel Images Compatible | |
| lineardisc | Compute Disc of Given Radius in Linear Network | |
| bind.fv | Combine Function Value Tables | |
| is.multitype | Test whether Object is Multitype | |
| deltametric | Delta Metric | |
| anylist | List of Objects | |
| bw.stoyan | Stoyan's Rule of Thumb for Bandwidth Selection | |
| layout.boxes | Generate a Row or Column Arrangement of Rectangles. | |
| nnfun.lpp | Nearest Neighbour Map on Linear Network | |
| MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
| fasp.object | Function Arrays for Spatial Patterns | |
| localKinhom | Inhomogeneous Neighbourhood Density Function | |
| expand.owin | Apply Expansion Rule | |
| npfun | Dummy Function Returns Number of Points | |
| by.im | Apply Function to Image Broken Down by Factor | |
| is.subset.owin | Determine Whether One Window is Contained In Another | |
| pairsat.family | Saturated Pairwise Interaction Point Process Family | |
| cbind.hyperframe | Combine Hyperframes by Rows or by Columns | |
| gorillas | Gorilla Nesting Sites | |
| gordon | People in Gordon Square | |
| clickjoin | Interactively join vertices on a plot | |
| is.marked | Test Whether Marks Are Present | |
| plot.ppm | plot a Fitted Point Process Model | |
| methods.lpp | Methods for Point Patterns on a Linear Network | |
| eem | Exponential Energy Marks | |
| model.depends | Identify Covariates Involved in each Model Term | |
| markconnect | Mark Connection Function | |
| Extract.psp | Extract Subset of Line Segment Pattern | |
| plot.influence.ppm | Plot Influence Measure | |
| linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |
| is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
| nnwhich.pp3 | Nearest neighbours in three dimensions | |
| ellipse | Elliptical Window. | |
| pairwise.family | Pairwise Interaction Process Family | |
| japanesepines | Japanese Pines Point Pattern | |
| nncross.lpp | Nearest Neighbours on a Linear Network | |
| plot.msr | Plot a Signed or Vector-Valued Measure | |
| psp | Create a Line Segment Pattern | |
| is.im | Test Whether An Object Is A Pixel Image | |
| methods.fii | Methods for Fitted Interactions | |
| hyytiala | Scots pines and other trees at Hyytiala | |
| convolve.im | Convolution of Pixel Images | |
| intensity.ppp | Empirical Intensity of Point Pattern | |
| persp.im | Perspective Plot of Pixel Image | |
| rDGS | Perfect Simulation of the Diggle-Gates-Stibbard Process | |
| plot.solist | Plot a List of Spatial Objects | |
| as.lpp | Convert Data to a Point Pattern on a Linear Network | |
| istat | Point and Click Interface for Exploratory Analysis of Point Pattern | |
| lppm | Fit Point Process Model to Point Pattern on Linear Network | |
| distmap.ppp | Distance Map of Point Pattern | |
| gauss.hermite | Gauss-Hermite Quadrature Approximation to Expectation for Normal Distribution | |
| linnet | Create a Linear Network | |
| pairdist.ppx | Pairwise Distances in Any Dimensions | |
| nnmap | K-th Nearest Point Map | |
| lut | Lookup Tables | |
| print.ppp | Print Brief Details of a Point Pattern Dataset | |
| ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
| discpartarea | Area of Part of Disc | |
| mppm | Fit Point Process Model to Several Point Patterns | |
| betacells | Beta Ganglion Cells in Cat Retina | |
| methods.units | Methods for Units | |
| model.matrix.slrm | Extract Design Matrix from Spatial Logistic Regression Model | |
| crossdist.ppp | Pairwise distances between two different point patterns | |
| as.solist | Convert List of Two-Dimensional Spatial Objects | |
| pcfdot | Multitype pair correlation function (i-to-any) | |
| longleaf | Longleaf Pines Point Pattern | |
| intersect.owin | Intersection, Union or Set Subtraction of Two Windows | |
| eval.fv | Evaluate Expression Involving Functions | |
| pairdist | Pairwise distances | |
| nnwhich.ppx | Nearest Neighbours in Any Dimensions | |
| plot.envelope | Plot a Simulation Envelope | |
| complement.owin | Take Complement of a Window | |
| plot.linim | Plot Pixel Image on Linear Network | |
| methods.kppm | Methods for Cluster Point Process Models | |
| methods.linfun | Methods for Functions on Linear Network | |
| nndist.ppx | Nearest Neighbour Distances in Any Dimensions | |
| scaletointerval | Rescale Data to Lie Between Specified Limits | |
| plot.mppm | plot a Fitted Multiple Point Process Model | |
| quadrat.test | Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
| nncross.pp3 | Nearest Neighbours Between Two Patterns in 3D | |
| rCauchy | Simulate Neyman-Scott Point Process with Cauchy cluster kernel | |
| multiplicity.ppp | Count Multiplicity of Duplicate Points | |
| is.lpp | Test Whether An Object Is A Point Pattern on a Linear Network | |
| Kscaled | Locally Scaled K-function | |
| heather | Diggle's Heather Data | |
| clarkevans | Clark and Evans Aggregation Index | |
| rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
| linim | Create Pixel Image on Linear Network | |
| marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern | |
| perimeter | Perimeter Length of Window | |
| Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
| layered | Create List of Plotting Layers | |
| localpcf | Local pair correlation function | |
| nnwhich.lpp | Identify Nearest Neighbours on a Linear Network | |
| pairorient | Point Pair Orientation Distribution | |
| envelope | Simulation Envelopes of Summary Function | |
| boundingbox | Bounding Box of a Window, Image, or Point Pattern | |
| closepairs.pp3 | Close Pairs of Points in 3 Dimensions | |
| is.dppm | Recognise Fitted Determinantal Point Process Models | |
| rMosaicField | Mosaic Random Field | |
| osteo | Osteocyte Lacunae Data: Replicated Three-Dimensional Point Patterns | |
| hybrid.family | Hybrid Interaction Family | |
| predict.kppm | Prediction from a Fitted Cluster Point Process Model | |
| Iest | Estimate the I-function | |
| levelset | Level Set of a Pixel Image | |
| default.expand | Default Expansion Rule for Simulation of Model | |
| predict.lppm | Predict Point Process Model on Linear Network | |
| rHardcore | Perfect Simulation of the Hardcore Process | |
| incircle | Find Largest Circle Inside Window | |
| pairdist.default | Pairwise distances | |
| Ksector | Sector K-function | |
| is.marked.ppm | Test Whether A Point Process Model is Marked | |
| is.ppp | Test Whether An Object Is A Point Pattern | |
| compatible | Test Whether Objects Are Compatible | |
| methods.ppx | Methods for Multidimensional Space-Time Point Patterns | |
| linearKdot | Multitype K Function (Dot-type) for Linear Point Pattern | |
| redwood | California Redwoods Point Pattern (Ripley's Subset) | |
| reduced.sample | Reduced Sample Estimator using Histogram Data | |
| nndist.lpp | Nearest neighbour distances on a linear network | |
| markcorr | Mark Correlation Function | |
| plot.kppm | Plot a fitted cluster point process | |
| is.stationary | Recognise Stationary and Poisson Point Process Models | |
| connected.ppp | Connected components of a point pattern | |
| mincontrast | Method of Minimum Contrast | |
| plot.hyperframe | Plot Entries in a Hyperframe | |
| fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
| envelope.pp3 | Simulation Envelopes of Summary Function for 3D Point Pattern | |
| harmonise.fv | Make Function Tables Compatible | |
| plot.lpp | Plot Point Pattern on Linear Network | |
| rmh.ppm | Simulate from a Fitted Point Process Model | |
| pcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-Type) | |
| padimage | Pad the Border of a Pixel Image | |
| circumradius | Circumradius of a Window | |
| rGaussPoisson | Simulate Gauss-Poisson Process | |
| Kmulti | Marked K-Function | |
| lengths.psp | Lengths of Line Segments | |
| beachcolours | Create Colour Scheme for a Range of Numbers | |
| runifpoint3 | Generate N Uniform Random Points in Three Dimensions | |
| panel.contour | Panel Plots using Colour Image or Contour Lines | |
| Extract.lpp | Extract Subset of Point Pattern on Linear Network | |
| logLik.slrm | Loglikelihood of Spatial Logistic Regression | |
| linearpcf | Linear Pair Correlation Function | |
| split.ppx | Divide Multidimensional Point Pattern into Sub-patterns | |
| methods.box3 | Methods for Three-Dimensional Box | |
| lansing | Lansing Woods Point Pattern | |
| fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |
| rotate.im | Rotate a Pixel Image | |
| pcf.ppp | Pair Correlation Function of Point Pattern | |
| intensity | Intensity of a Dataset or a Model | |
| nncross | Nearest Neighbours Between Two Patterns | |
| connected | Connected components | |
| plot.slrm | Plot a Fitted Spatial Logistic Regression | |
| predict.ppm | Prediction from a Fitted Point Process Model | |
| improve.kppm | Improve Intensity Estimate of Fitted Cluster Point Process Model | |
| pcfmulti | Marked pair correlation function | |
| alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern | |
| paracou | Kimboto trees at Paracou, French Guiana | |
| plot.pp3 | Plot a three-dimensional point pattern | |
| logLik.ppm | Log Likelihood and AIC for Point Process Model | |
| Extract.fasp | Extract Subset of Function Array | |
| matclust.estpcf | Fit the Matern Cluster Point Process by Minimum Contrast Using Pair Correlation | |
| rMaternI | Simulate Matern Model I | |
| perspPoints | Draw Points or Lines on a Surface Viewed in Perspective | |
| rStrauss | Perfect Simulation of the Strauss Process | |
| subset.ppp | Subset of Point Pattern Satisfying A Condition | |
| pppmatching.object | Class of Point Matchings | |
| rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |
| rescale | Convert dataset to another unit of length | |
| linfun | Function on a Linear Network | |
| Jinhom | Inhomogeneous J-function | |
| nnmark | Mark of Nearest Neighbour | |
| rshift.ppp | Randomly Shift a Point Pattern | |
| murchison | Murchison gold deposits | |
| owin | Create a Window | |
| round.ppp | Apply Numerical Rounding to Spatial Coordinates | |
| simplepanel | Simple Point-and-Click Interface Panels | |
| qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
| will.expand | Test Expansion Rule | |
| plot.listof | Plot a List of Things | |
| plot.im | Plot a Pixel Image | |
| ppm.ppp | Fit Point Process Model to Point Pattern Data | |
| progressreport | Print Progress Reports | |
| Kmulti.inhom | Inhomogeneous Marked K-Function | |
| pyramidal | Pyramidal Neurons in Cingulate Cortex | |
| Pairwise | Generic Pairwise Interaction model | |
| pairdist.ppp | Pairwise distances | |
| plot.ppp | plot a Spatial Point Pattern | |
| Emark | Diagnostics for random marking | |
| plot.fv | Plot Function Values | |
| rescale.ppp | Convert Point Pattern to Another Unit of Length | |
| Smooth.ppp | Spatial smoothing of observations at irregular points | |
| plot.anylist | Plot a List of Things | |
| simulate.slrm | Simulate a Fitted Spatial Logistic Regression Model | |
| pool.envelope | Pool Data from Several Envelopes | |
| dclf.test | Diggle-Cressie-Loosmore-Ford and Maximum Absolute Deviation Tests | |
| plot.layered | Layered Plot | |
| predict.mppm | Prediction for Fitted Multiple Point Process Model | |
| linearpcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-type) for Linear Point Pattern | |
| pool.rat | Pool Data from Several Ratio Objects | |
| maxnndist | Compute Minimum or Maximum Nearest-Neighbour Distance | |
| mean.im | Maximum, Minimum, Mean, Median, Range or Sum of Pixel Values in an Image | |
| contour.im | Contour plot of pixel image | |
| pairdist.pp3 | Pairwise distances in Three Dimensions | |
| rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |
| volume | Volume of an Object | |
| valid.ppm | Check Whether Point Process Model is Valid | |
| rhohat | Smoothing Estimate of Covariate Transformation | |
| ppx | Multidimensional Space-Time Point Pattern | |
| setcov | Set Covariance of a Window | |
| pixelquad | Quadrature Scheme Based on Pixel Grid | |
| plot.scan.test | Plot Result of Scan Test | |
| quadrat.test.mppm | Chi-Squared Test for Multiple Point Process Model Based on Quadrat Counts | |
| is.hybrid | Test Whether Object is a Hybrid | |
| spatstat-deprecated | Deprecated spatstat functions | |
| rThomas | Simulate Thomas Process | |
| quadratcount | Quadrat counting for a point pattern | |
| Lest | L-function | |
| methods.pp3 | Methods for three-dimensional point patterns | |
| ppm.object | Class of Fitted Point Process Models | |
| runifdisc | Generate N Uniform Random Points in a Disc | |
| simulate.ppm | Simulate a Fitted Gibbs Point Process Model | |
| plot.symbolmap | Plot a Graphics Symbol Map | |
| simdat | Simulated Point Pattern | |
| rVarGamma | Simulate Neyman-Scott Point Process with Variance Gamma cluster kernel | |
| plot.psp | plot a Spatial Line Segment Pattern | |
| rMatClust | Simulate Matern Cluster Process | |
| methods.objsurf | Methods for Objective Function Surfaces | |
| is.empty | Test Whether An Object Is Empty | |
| predict.slrm | Predicted or Fitted Values from Spatial Logistic Regression | |
| anova.lppm | ANOVA for Fitted Point Process Models on Linear Network | |
| shift.psp | Apply Vector Translation To Line Segment Pattern | |
| ppp | Create a Point Pattern | |
| reach | Interaction Distance of a Point Process | |
| spatstat-internal | Internal spatstat functions | |
| rounding | Detect Numerical Rounding | |
| texturemap | Texture Map | |
| convexhull | Convex Hull | |
| project.ppm | Force Point Process Model to be Valid | |
| psstA | Pseudoscore Diagnostic For Fitted Model against Area-Interaction Alternative | |
| iplot | Point and Click Interface for Displaying Spatial Data | |
| with.hyperframe | Evaluate an Expression in Each Row of a Hyperframe | |
| urkiola | Urkiola Woods Point Pattern | |
| nsegments | Number of Line Segments in a Line Segment Pattern | |
| methods.lppm | Methods for Fitted Point Process Models on a Linear Network | |
| vcov.slrm | Variance-Covariance Matrix for a Fitted Spatial Logistic Regression | |
| superimpose.lpp | Superimpose Several Point Patterns on Linear Network | |
| plot.splitppp | Plot a List of Point Patterns | |
| raster.x | Cartesian Coordinates for a Pixel Raster | |
| rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
| plot.quad | Plot a Spatial Quadrature Scheme | |
| rpoispp | Generate Poisson Point Pattern | |
| bw.scott | Scott's Rule for Bandwidth Selection for Kernel Density | |
| summary.im | Summarizing a Pixel Image | |
| quadrat.test.splitppp | Dispersion Test of CSR for Split Point Pattern Based on Quadrat Counts | |
| rjitter | Random Perturbation of a Point Pattern | |
| plot.fasp | Plot a Function Array | |
| localK | Neighbourhood density function | |
| rPoissonCluster | Simulate Poisson Cluster Process | |
| rpoint | Generate N Random Points | |
| nnwhich | Nearest neighbour | |
| update.symbolmap | Update a Graphics Symbol Map. | |
| pixellate.owin | Convert Window to Pixel Image | |
| plot.texturemap | Plot a Texture Map | |
| with.fv | Evaluate an Expression in a Function Table | |
| plot.quadrattest | Display the result of a quadrat counting test. | |
| matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
| update.rmhcontrol | Update Control Parameters of Metropolis-Hastings Algorithm | |
| fitted.mppm | Fitted Conditional Intensity for Multiple Point Process Model | |
| nbfires | Point Patterns of New Brunswick Forest Fires | |
| symbolmap | Graphics Symbol Map | |
| nearestsegment | Find Line Segment Nearest to Each Point | |
| print.owin | Print Brief Details of a Spatial Window | |
| relrisk | Nonparametric Estimate of Spatially-Varying Relative Risk | |
| rmpoispp | Generate Multitype Poisson Point Pattern | |
| sessionLibs | Print Names and Version Numbers of Libraries Loaded | |
| summary.solist | Summary of a List of Spatial Objects | |
| ppp.object | Class of Point Patterns | |
| rlinegrid | Generate grid of parallel lines with random displacement | |
| unitname | Name for Unit of Length | |
| sharpen | Data Sharpening of Point Pattern | |
| rotmean | Rotational Average of a Pixel Image | |
| psp.object | Class of Line Segment Patterns | |
| pool | Pool Data | |
| rgbim | Create Colour-Valued Pixel Image | |
| Hest | Spherical Contact Distribution Function | |
| rotate.owin | Rotate a Window | |
| rotate.psp | Rotate a Line Segment Pattern | |
| shapley | Galaxies in the Shapley Supercluster | |
| superimpose | Superimpose Several Geometric Patterns | |
| plot.colourmap | Plot a Colour Map | |
| rcellnumber | Generate Random Numbers of Points for Cell Process | |
| mucosa | Cells in Gastric Mucosa | |
| pixellate.psp | Convert Line Segment Pattern to Pixel Image | |
| psstG | Pseudoscore Diagnostic For Fitted Model against Saturation Alternative | |
| plot.lppm | Plot a Fitted Point Process Model on a Linear Network | |
| pairdist.lpp | Pairwise shortest-path distances between points on a linear network | |
| idw | Inverse-distance weighted smoothing of observations at irregular points | |
| summary.quad | Summarizing a Quadrature Scheme | |
| residuals.mppm | Residuals for Point Process Model Fitted to Multiple Point Patterns | |
| quadrats | Divide Region into Quadrats | |
| simulate.lppm | Simulate a Fitted Point Process Model on a Linear Network | |
| scanLRTS | Likelihood Ratio Test Statistic for Scan Test | |
| ppm | Fit Point Process Model to Data | |
| pairs.im | Scatterplot Matrix for Pixel Images | |
| timed | Record the Computation Time | |
| triplet.family | Triplet Interaction Family | |
| scan.test | Spatial Scan Test | |
| rshift | Random Shift | |
| summary.owin | Summary of a Spatial Window | |
| zapsmall.im | Rounding of Pixel Values | |
| selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
| midpoints.psp | Midpoints of Line Segment Pattern | |
| rescue.rectangle | Convert Window Back To Rectangle | |
| pcfinhom | Inhomogeneous Pair Correlation Function | |
| spatstat.options | Internal Options in Spatstat Package | |
| rstrat | Simulate Stratified Random Point Pattern | |
| rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
| rsyst | Simulate systematic random point pattern | |
| square | Square Window | |
| quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
| summary.anylist | Summary of a List of Things | |
| rpoislpp | Poisson Point Process on a Linear Network | |
| plot.tess | Plot a tessellation | |
| spatialcdf | Spatial Cumulative Distribution Function | |
| rlabel | Random Re-Labelling of Point Pattern | |
| rotate.ppp | Rotate a Point Pattern | |
| rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
| addvar | Added Variable Plot for Point Process Model | |
| stratrand | Stratified random point pattern | |
| spruces | Spruces Point Pattern | |
| split.ppp | Divide Point Pattern into Sub-patterns | |
| PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
| rSSI | Simulate Simple Sequential Inhibition | |
| print.im | Print Brief Details of an Image | |
| summary.ppp | Summary of a Point Pattern Dataset | |
| unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
| quantile.ewcdf | Quantiles of Weighted Empirical Cumulative Distribution Function | |
| ponderosa | Ponderosa Pine Tree Point Pattern | |
| Poisson | Poisson Point Process Model | |
| runifpointx | Generate N Uniform Random Points in Any Dimensions | |
| rpoisline | Generate Poisson Random Line Process | |
| varblock | Estimate Variance of Summary Statistic by Subdivision | |
| whist | Weighted Histogram | |
| suffstat | Sufficient Statistic of Point Process Model | |
| rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |
| Kdot | Multitype K Function (i-to-any) | |
| pool.quadrattest | Pool Several Quadrat Tests | |
| pp3 | Three Dimensional Point Pattern | |
| tess | Create a Tessellation | |
| Smooth | Spatial smoothing of data | |
| scalardilate | Apply Scalar Dilation | |
| runifpoint | Generate N Uniform Random Points | |
| MultiHard | The Multitype Hard Core Point Process Model | |
| pcf | Pair Correlation Function | |
| shift.ppp | Apply Vector Translation To Point Pattern | |
| rQuasi | Generate Quasirandom Point Pattern in Given Window | |
| ripras | Estimate window from points alone | |
| summary.listof | Summary of a List of Things | |
| sporophores | Sporophores Data | |
| psst | Pseudoscore Diagnostic For Fitted Model against General Alternative | |
| rNeymanScott | Simulate Neyman-Scott Process | |
| quadratresample | Resample a Point Pattern by Resampling Quadrats | |
| slrm | Spatial Logistic Regression | |
| pixellate | Convert Spatial Object to Pixel Image | |
| disc | Circular Window | |
| update.kppm | Update a Fitted Cluster Point Process Model | |
| quad.object | Class of Quadrature Schemes | |
| quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
| model.frame.ppm | Extract the Variables in a Point Process Model | |
| rmhexpand | Specify Simulation Window or Expansion Rule | |
| thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
| tiles | Extract List of Tiles in a Tessellation | |
| diameter | Diameter of an Object | |
| plot.leverage.ppm | Plot Leverage Function | |
| rLGCP | Simulate Log-Gaussian Cox Process | |
| vesicles | Vesicles Data | |
| rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |
| project2set | Find Nearest Point in a Region | |
| summary.splitppp | Summary of a Split Point Pattern | |
| simulate.kppm | Simulate a Fitted Cluster Point Process Model | |
| spatstat-package | The Spatstat Package | |
| solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
| Jest | Estimate the J-function | |
| pointsOnLines | Place Points Evenly Along Specified Lines | |
| stienen | Stienen Diagram | |
| adaptive.density | Intensity Estimate of Point Pattern Using Tessellation | |
| finpines | Pine saplings in Finland. | |
| pcf3est | Pair Correlation Function of a Three-Dimensional Point Pattern | |
| vargamma.estK | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |
| affine.im | Apply Affine Transformation To Pixel Image | |
| nztrees | New Zealand Trees Point Pattern | |
| stieltjes | Compute Integral of Function Against Cumulative Distribution | |
| swedishpines | Swedish Pines Point Pattern | |
| plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
| waka | Trees in Waka national park | |
| reflect | Reflect In Origin | |
| vertices | Vertices of a Window | |
| textureplot | Plot Image Using Texture Fill | |
| split.hyperframe | Divide Hyperframe Into Subsets and Reassemble | |
| rescale.owin | Convert Window to Another Unit of Length | |
| Extract.tess | Extract or Replace Subset of Tessellation | |
| thomas.estpcf | Fit the Thomas Point Process by Minimum Contrast | |
| rmpoint | Generate N Random Multitype Points | |
| transect.im | Pixel Values Along a Transect | |
| unnormdensity | Weighted kernel smoother | |
| Smoothfun.ppp | Smooth Interpolation of Marks as a Spatial Function | |
| sumouter | Compute Quadratic Forms | |
| vargamma.estpcf | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |
| rknn | Theoretical Distribution of Nearest Neighbour Distance | |
| MultiStrauss | The Multitype Strauss Point Process Model | |
| update.ppm | Update a Fitted Point Process Model | |
| shift | Apply Vector Translation | |
| rMosaicSet | Mosaic Random Set | |
| rStraussHard | Perfect Simulation of the Strauss-Hardcore Process | |
| tilenames | Names of Tiles in a Tessellation | |
| print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
| vcov.kppm | Variance-Covariance Matrix for a Fitted Cluster Point Process Model | |
| pppmatching | Create a Point Matching | |
| Kcross | Multitype K Function (Cross-type) | |
| Gmulti | Marked Nearest Neighbour Distance Function | |
| reload.or.compute | Compute Unless Previously Saved | |
| trim.rectangle | Cut margins from rectangle | |
| rcell | Simulate Baddeley-Silverman Cell Process | |
| pool.fasp | Pool Data from Several Function Arrays | |
| simplenet | Simple Example of Linear Network | |
| Extract.ppx | Extract Subset of Multidimensional Point Pattern | |
| opening | Morphological Opening | |
| summary.ppm | Summarizing a Fitted Point Process Model | |
| rho2hat | Smoothed Relative Density of Pairs of Covariate Values | |
| sidelengths.owin | Side Lengths of Enclosing Rectangle of a Window | |
| run.simplepanel | Run Point-and-Click Interface | |
| profilepl | Profile Maximum Pseudolikelihood | |
| pixelcentres | Extract Pixel Centres as Point Pattern | |
| leverage.ppm | Leverage Measure for Spatial Point Process Model | |
| simplify.owin | Approximate a Polygon by a Simpler Polygon | |
| union.quad | Union of Data and Dummy Points | |
| rshift.splitppp | Randomly Shift a List of Point Patterns | |
| subfits | Extract List of Individual Point Process Models | |
| rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
| Triplets | The Triplet Point Process Model | |
| chorley | Chorley-Ribble Cancer Data | |
| rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |
| rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |
| range.fv | Range of Function Values | |
| Extract.listof | Extract or Replace Subset of a List of Things | |
| split.im | Divide Image Into Sub-images | |
| rshift.psp | Randomly Shift a Line Segment Pattern | |
| runifpointOnLines | Generate N Uniform Random Points On Line Segments | |
| tile.areas | Compute Areas of Tiles in a Tessellation | |
| StraussHard | The Strauss / Hard Core Point Process Model | |
| data.ppm | Extract Original Data from a Fitted Point Process Model | |
| Finhom | Inhomogeneous Empty Space Function | |
| compatible.fasp | Test Whether Function Arrays Are Compatible | |
| as.psp | Convert Data To Class psp | |
| identify.ppp | Identify Points in a Point Pattern | |
| inside.owin | Test Whether Points Are Inside A Window | |
| diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
| distmap.owin | Distance Map of Window | |
| linearKinhom | Inhomogeneous Linear K Function | |
| as.linim | Convert to Pixel Image on Linear Network | |
| ippm | Fit Point Process Model Involving Irregular Trend Parameters | |
| markvario | Mark Variogram | |
| latest.news | Print News About Latest Version of Package | |
| Gfox | Foxall's Distance Functions | |
| plot.quadratcount | Plot Quadrat Counts | |
| pcf.fasp | Pair Correlation Function obtained from array of K functions | |
| plot.cdftest | Plot a Spatial Distribution Test | |
| quasirandom | Quasirandom Patterns | |
| rDiggleGratton | Perfect Simulation of the Diggle-Gratton Process | |
| overlap.owin | Compute Area of Overlap | |
| residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
| npoints | Number of Points in a Point Pattern | |
| scanpp | Read Point Pattern From Data File | |
| shift.im | Apply Vector Translation To Pixel Image | |
| runiflpp | Uniform Random Points on a Linear Network | |
| solist | List of Two-Dimensional Spatial Objects | |
| plot.linnet | Plot a linear network | |
| print.ppm | Print a Fitted Point Process Model | |
| Extract.anylist | Extract or Replace Subset of a List of Things | |
| Gres | Residual G Function | |
| cells | Biological Cells Point Pattern | |
| compareFit | Residual Diagnostics for Multiple Fitted Models | |
| bw.relrisk | Cross Validated Bandwidth Selection for Relative Risk Estimation | |
| diameter.boxx | Geometrical Calculations for Multi-Dimensional Box | |
| crossing.psp | Crossing Points of Two Line Segment Patterns | |
| intensity.quadratcount | Intensity Estimates Using Quadrat Counts | |
| marks.psp | Marks of a Line Segment Pattern | |
| marks | Marks of a Point Pattern | |
| methods.slrm | Methods for Spatial Logistic Regression Models | |
| Extract.influence.ppm | Extract Subset of Influence Object | |
| Replace.im | Reset Values in Subset of Image | |
| methods.layered | Methods for Layered Objects | |
| plot.owin | Plot a Spatial Window | |
| pcf.fv | Pair Correlation Function obtained from K Function | |
| nndist.pp3 | Nearest neighbour distances in three dimensions | |
| Kmodel.ppm | K Function or Pair Correlation Function of Gibbs Point Process model | |
| periodify | Make Periodic Copies of a Spatial Pattern | |
| quantile.im | Sample Quantiles of Pixel Image | |
| project2segment | Move Point To Nearest Line | |
| print.quad | Print a Quadrature Scheme | |
| rMaternII | Simulate Matern Model II | |
| redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
| shift.owin | Apply Vector Translation To Window | |
| rthin | Random Thinning | |
| ord.family | Ord Interaction Process Family | |
| endpoints.psp | Endpoints of Line Segment Pattern | |
| summary.psp | Summary of a Line Segment Pattern Dataset | |
| waterstriders | Waterstriders data. Three independent replications of a point pattern formed by insects. | |
| vcov.mppm | Calculate Variance-Covariance Matrix for Fitted Multiple Point Process Model | |
| spokes | Spokes pattern of dummy points | |
| pairdist.psp | Pairwise distances between line segments | |
| distfun | Distance Map as a Function | |
| amacrine | Hughes' Amacrine Cell Data | |
| Gcom | Model Compensator of Nearest Neighbour Function | |
| Jdot | Multitype J Function (i-to-any) | |
| discretise | Safely Convert Point Pattern Window to Binary Mask | |
| default.dummy | Generate a Default Pattern of Dummy Points | |
| as.matrix.im | Convert Pixel Image to Matrix or Array | |
| eval.linim | Evaluate Expression Involving Pixel Images on Linear Network | |
| flu | Influenza Virus Proteins | |
| foo | Foo is Not a Variable | |
| infline | Infinite Straight Lines | |
| crossdist | Pairwise distances | |
| humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
| kppm | Fit Cluster or Cox Point Process Model | |
| methods.linnet | Methods for Linear Networks | |
| owin.object | Class owin | |
| objsurf | Objective Function Surface | |
| plot.bermantest | Plot Result of Berman Test | |
| parres | Partial Residuals for Point Process Model | |
| rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |
| rotate | Rotate | |
| rpoislinetess | Poisson Line Tessellation | |
| rat | Ratio object | |
| residuals.ppm | Residuals for Fitted Point Process Model | |
| simba | Simulated data from a two-group experiment with replication within each group. | |
| rescale.im | Convert Pixel Image to Another Unit of Length | |
| pcfcross | Multitype pair correlation function (cross-type) | |
| quadscheme.logi | Generate a Logistic Regression Quadrature Scheme from a Point Pattern | |
| unmark | Remove Marks | |
| vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
| tweak.colourmap | Change Colour Values in a Colour Map | |
| pppdist | Distance Between Two Point Patterns | |
| No Results! | ||
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Details
| Nickname | Smoke and Mirrors |
| Date | 2014-10-23 |
| License | GPL (>= 2) |
| URL | http://www.spatstat.org |
| LazyData | true |
| NeedsCompilation | yes |
| ByteCompile | true |
| Packaged | 2014-10-23 01:47:26 UTC; adrian |
| Repository | CRAN |
| Date/Publication | 2014-10-23 08:43:49 |
| 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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