# spatstat v1.14-10

Monthly downloads

## Spatial Point Pattern analysis, model-fitting, simulation, tests

A package for analysing spatial data,
mainly Spatial Point Patterns, including multitype/marked points
and spatial covariates, in any two-dimensional spatial region.
Contains functions for 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, and
pixel images. Point process models can be
fitted to point pattern data. Cluster type models are fitted
by the method of minimum contrast. Very general Gibbs point
process models can be fitted to point pattern data
using a function ppm similar to lm or glm. Models may
include dependence on covariates, interpoint interaction
and dependence on marks. Fitted models can be simulated automatically.
Also provides facilities for formal inference (such as chi-squared
tests) and model diagnostics (including simulation
envelopes, residuals, residual plots and Q-Q plots).

## Functions in spatstat

Name | Description | |

AreaInter | The Area Interaction Point Process Model | |

Geyer | Geyer's Saturation Point Process Model | |

Kest.fft | K-function using FFT | |

by.im | Apply Function to Image Broken Down by Factor | |

Fest | Estimate the empty space function F | |

Kinhom | Inhomogeneous K-function | |

as.im | Convert to Pixel Image | |

as.matrix.im | Convert Pixel Image to Matrix | |

Kcross | Multitype K Function (Cross-type) | |

fv.object | Data Frames of Function Values | |

convexhull.xy | Convex Hull of Points | |

affine | Apply Affine Transformation | |

crossdist.ppp | Pairwise distances between two different point patterns | |

duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |

LennardJones | The Lennard-Jones Potential | |

harmonic | Basis for Harmonic Functions | |

Pairwise | Generic Pairwise Interaction model | |

DiggleGratton | Diggle-Gratton model | |

Jmulti | Marked J Function | |

matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |

compatible.fasp | Test Whether Two Function Arrays Are Compatible | |

blur | Apply Gaussian Blur to a Pixel Image | |

pixelquad | Quadrature Scheme Based on Pixel Grid | |

spatstat | The Spatstat Package | |

compatible.im | Test Whether Two Pixel Images Are Compatible | |

StraussHard | The Strauss / Hard Core Point Process Model | |

dirichlet | Dirichlet Tessellation of Point Pattern | |

append.psp | Combine Two Line Segment Patterns | |

adaptive.density | Intensity Estimate of Point Pattern Using Tessellation | |

Gmulti | Marked Nearest Neighbour Distance Function | |

is.im | Test Whether An Object Is A Pixel Image | |

nztrees | New Zealand Trees Point Pattern | |

affine.psp | Apply Affine Transformation To Line Segment Pattern | |

alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern | |

pairdist.ppp | Pairwise distances | |

plot.hyperframe | Plot Entries in a Hyperframe | |

clickpoly | Interactively Define a Polygon | |

BadGey | Hybrid Geyer Point Process Model | |

Kest | K-function | |

finpines | Pine saplings in Finland. | |

im | Create a Pixel Image Object | |

kppm | Fit cluster point process model | |

plot.psp | plot a Spatial Line Segment Pattern | |

disc | Circular Window | |

Lest | L-function | |

ewcdf | Weighted Empirical Cumulative Distribution Function | |

Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |

Jest | Estimate the J-function | |

levelset | Level Set of a Pixel Image | |

eval.hyper | Evaluate an Expression in Each Row of a Hyperframe | |

plot.owin | Plot a Spatial Window | |

Gest | Nearest Neighbour Distance Function G | |

gridweights | Compute Quadrature Weights Based on Grid Counts | |

density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |

Linhom | L-function | |

qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |

nearestsegment | Find Line Segment Nearest to Each Point | |

rMaternI | Simulate Matern Model I | |

coef.ppm | Coefficients of Fitted Point Process Model | |

bdist.points | Distance to Boundary of Window | |

MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |

model.images | Compute Images of Constructed Covariates | |

eval.im | Evaluate Expression Involving Pixel Images | |

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

cells | Biological Cells Point Pattern | |

bounding.box | Bounding Box of a Window or Point Pattern | |

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

distmap.owin | Distance Map of Window | |

Strauss | The Strauss Point Process Model | |

as.tess | Convert Data To Tessellation | |

Kmeasure | Reduced Second Moment Measure | |

print.owin | Print Brief Details of a Spatial Window | |

spatstat-internal | Internal spatstat functions | |

Kdot | Multitype K Function (i-to-any) | |

as.mask | Pixel Image Approximation of a Window | |

quantile.im | Sample Quantiles of Pixel Image | |

affine.ppp | Apply Affine Transformation To Point Pattern | |

anova.ppm | ANOVA for Fitted Point Process Models | |

bramblecanes | Hutchings' Bramble Canes data | |

fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |

rescale | Convert dataset to another unit of length | |

nnwhich | Nearest neighbour | |

density.ppp | Kernel Smoothed Intensity of Point Pattern | |

opening.owin | Morphological Opening of a Window | |

delaunay | Delaunay Triangulation of Point Pattern | |

hamster | Aherne's hamster tumour data | |

pairdist.psp | Pairwise distances between line segments | |

Lcross | Multitype L-function (cross-type) | |

cut.ppp | Classify Points in a Point Pattern | |

Ldot | Multitype L-function (i-to-any) | |

anemones | Beadlet Anemones Data | |

thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |

owin | Create a Window | |

rotate.psp | Rotate a Line Segment Pattern | |

rMatClust | Simulate Matern Cluster Process | |

Ord | Generic Ord Interaction model | |

ants | Harkness-Isham ants' nests data | |

identify.ppp | Identify Points in a Point Pattern | |

density.psp | Kernel Smoothing of Line Segment Pattern | |

is.owin | Test Whether An Object Is A Window | |

bounding.box.xy | Convex Hull of Points | |

complement.owin | Take Complement of a Window | |

mean.im | Mean, Median and Range of Pixel Values in an Image | |

affine.owin | Apply Affine Transformation To Window | |

centroid.owin | Centroid of a window | |

closing.owin | Morphological Closing of a Window | |

rlabel | Random Re-Labelling of Point Pattern | |

by.ppp | Apply a Function to a Point Pattern Broken Down by Factor | |

contour.im | Contour plot of pixel image | |

chorley | Chorley-Ribble Cancer Data | |

letterR | Window in Shape of Letter R | |

ppp.object | Class of Point Patterns | |

nndist.psp | Nearest neighbour distances between line segments | |

pointsOnLines | Place Points Evenly Along Specified Lines | |

Jcross | Multitype J Function (i-to-j) | |

rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |

Iest | Estimate the I-function | |

hist.im | Histogram of Pixel Values in an Image | |

rthin | Random Thinning | |

Kcross.inhom | Inhomogeneous Cross K Function | |

rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |

clarkevans | Clark and Evans Aggregation Index | |

runifdisc | Generate N Uniform Random Points in a Disc | |

gpc2owin | Convert Polygonal Region into Different Format | |

diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |

dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |

envelope | Simulation envelopes of summary function | |

areadiff | Difference of Disc Areas | |

pcf.fv | Pair Correlation Function obtained from K Function | |

PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |

pcf.ppp | Pair Correlation Function of Point Pattern | |

compatible.fv | Test Whether Two Function Objects Are Compatible | |

as.rectangle | Window Frame | |

Softcore | The Soft Core Point Process Model | |

endpoints.psp | Endpoints of Line Segment Pattern | |

ppm.object | Class of Fitted Point Process Models | |

cut.im | Convert Pixel Image from Numeric to Factor | |

clickppp | Interactively Add Points | |

rNeymanScott | Simulate Neyman-Scott Process | |

diameter | Diameter of a Window | |

is.ppp | Test Whether An Object Is A Point Pattern | |

distmap.psp | Distance Map of Line Segment Pattern | |

effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model | |

plot.im | Plot a Pixel Image | |

summary.im | Summarizing a Pixel Image | |

rStrauss | Perfect Simulation of the Strauss Process | |

Saturated | Saturated Pairwise Interaction model | |

discretise | Safely Convert Point Pattern Window to Binary Mask | |

concatxy | Concatenate x,y Coordinate Vectors | |

bei | Tropical rain forest trees | |

Kmulti | Marked K-Function | |

corners | Corners of a rectangle | |

expand.owin | Expand Window By Factor | |

plot.splitppp | Plot a List of Point Patterns | |

pppmatching.object | Class of Point Matchings | |

nearest.raster.point | Find Pixel Nearest to a Given Point | |

angles.psp | Orientation Angles of Line Segments | |

copper | Berman-Huntington points and lines data | |

nbfires | Point Patterns of New Brunswick Forest Fires | |

simulate.kppm | Simulate a fitted cluster point process model. | |

quadscheme | Generate a Quadrature Scheme from a Point Pattern | |

default.dummy | Generate a Default Pattern of Dummy Points | |

crossing.psp | Crossing Points of Two Line Segment Patterns | |

square | Square Window | |

quad.object | Class of Quadrature Schemes | |

erode.owin | Erode a Window | |

gridcentres | Rectangular grid of points | |

eroded.areas | Areas of Morphological Erosions | |

Jdot | Multitype J Function (i-to-any) | |

ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |

dilate.owin | Dilate a Window | |

rmpoint | Generate N Random Multitype Points | |

interp.im | Interpolate a Pixel Image | |

ponderosa | Ponderosa Pine Tree Point Pattern | |

fasp.object | Function Arrays for Spatial Patterns | |

is.ppm | Test Whether An Object Is A Fitted Point Process Model | |

MultiStrauss | The Multitype Strauss Point Process Model | |

simdat | Simulated Point Pattern | |

OrdThresh | Ord's Interaction model | |

SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model | |

[.quad | Subset of Quadrature Scheme | |

Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |

applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |

summary.listof | Summary of a List of Things | |

as.owin | Convert Data To Class owin | |

inside.owin | Test Whether Points Are Inside A Window | |

pairdist | Pairwise distances | |

eval.fasp | Evaluate Expression Involving Function Arrays | |

redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |

lengths.psp | Lengths of Line Segments | |

as.psp | Convert Data To Class psp | |

data.ppm | Extract Original Data from a Fitted Point Process Model | |

print.im | Print Brief Details of an Image | |

as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |

crossdist.psp | Pairwise distances between two different line segment patterns | |

dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |

eem | Exponential Energy Marks | |

incircle | Find Largest Circle Inside Window | |

fitted.ppm | Fitted Conditional Intensity for Point Process Model | |

betacells | Beta Ganglion Cells in Cat Retina | |

lansing | Lansing Woods Point Pattern | |

is.subset.owin | Determine Whether One Window is Contained In Another | |

rescale.ppp | Convert Point Pattern to Another Unit of Length | |

eval.fv | Evaluate Expression Involving Functions | |

area.owin | Area of a Window | |

setcov | Set Covariance of a Window | |

rshift.psp | Randomly Shift a Line Segment Pattern | |

profilepl | Profile Maximum Pseudolikelihood | |

ripras | Estimate window from points alone | |

quadrat.test | Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |

rSSI | Simulate Simple Sequential Inhibition | |

hyperframe | Hyper Data Frame | |

urkiola | Urkiola Woods Point Pattern | |

is.multitype.ppm | Test Whether A Point Process Model is Multitype | |

spokes | Spokes pattern of dummy points | |

lurking | Lurking variable plot | |

selfcrossing.psp | Crossing Points in a Line Segment Pattern | |

is.marked.ppm | Test Whether A Point Process Model is Marked | |

subset.listof | Extract or Replace Subset of a List of Things | |

subset.im | Extract Subset of Image | |

rstrat | Simulate Stratified Random Point Pattern | |

demopat | Artificial Data Point Pattern | |

km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |

is.multitype | Test whether Object is Multitype | |

rsyst | Simulate systematic random point pattern | |

bdist.pixels | Distance to Boundary of Window | |

summary.quad | Summarizing a Quadrature Scheme | |

kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |

ppp | Create a Point Pattern | |

union.quad | Union of Data and Dummy Points | |

as.ppp | Convert Data To Class ppp | |

inforder.family | Infinite Order Interaction Family | |

plot.fasp | Plot a Function Array | |

plot.listof | Plot a List of Things | |

amacrine | Hughes' Amacrine Cell Data | |

pppdist | Distance Between Two Point Patterns | |

stieltjes | Compute Integral of Function Against Cumulative Distribution | |

midpoints.psp | Midpoints of Line Segment Pattern | |

pcf.fasp | Pair Correlation Function obtained from array of K functions | |

update.kppm | Update a Fitted Cluster Point Process Model | |

crossdist | Pairwise distances | |

matchingdist | Distance for a Point Pattern Matching | |

plot.ppp | plot a Spatial Point Pattern | |

superimposePSP | Superimpose Several Line Segment Patterns | |

im.object | Class of Images | |

marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern | |

quadratcount | Quadrat counting for a point pattern | |

logLik.ppm | Log Likelihood for Poisson Point Process Model | |

lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |

as.data.frame.psp | Coerce Line Segment Pattern to a Data Frame | |

rjitter | Random Perturbation of a Point Pattern | |

markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |

predict.kppm | Prediction from a Fitted Cluster Point Process Model | |

intersect.tess | Intersection of Two Tessellations | |

markcorr | Mark Correlation Function | |

distmap | Distance Map | |

pairwise.family | Pairwise Interaction Process Family | |

print.ppm | Print a Fitted Point Process Model | |

rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |

pixellate | Convert Point Pattern to Pixel Image | |

superimpose | Superimpose Several Point Patterns | |

pcfcross | Multitype pair correlation function | |

fryplot | Fry Plot of Point Pattern | |

longleaf | Longleaf Pines Point Pattern | |

localK | Neighbourhood density function | |

unique.ppp | Extract Unique Points from a Spatial Point Pattern | |

miplot | Morishita Index Plot | |

ppm | Fit Point Process Model to Data | |

plot.ppm | plot a Fitted Point Process Model | |

plot.quad | plot a Spatial Quadrature Scheme | |

nncross | Nearest Neighbour in Another Point Pattern | |

plot.tess | Plot a tessellation | |

progressreport | Print Progress Reports | |

nncorr | Nearest-Neighbour Correlation of Marked Point Pattern | |

predict.ppm | Prediction from a Fitted Point Process Model | |

summary.psp | Summary of a Line Segment Pattern Dataset | |

distmap.ppp | Distance Map of Point Pattern | |

psp | Create a Line Segment Pattern | |

ord.family | Ord Interaction Process Family | |

intersect.owin | Intersection or Union of Two Windows | |

residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

plot.kppm | Plot a fitted cluster point process | |

is.marked | Test Whether Marks Are Present | |

quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |

mincontrast | Method of Minimum Contrast | |

murchison | Murchison gold deposits | |

plot.plotppm | Plot a plotppm Object Created by plot.ppm | |

residuals.ppm | Residuals for Fitted Point Process Model | |

project2segment | Move Point To Nearest Line | |

rotate.owin | Rotate a Window | |

print.psp | Print Brief Details of a Line Segment Pattern Dataset | |

print.ppp | Print Brief Details of a Point Pattern Dataset | |

rThomas | Simulate Thomas Process | |

runifpointOnLines | Generate N Uniform Random Points On Line Segments | |

kstest.ppm | Kolmogorov-Smirnov Test for Point Process Model | |

model.matrix.ppm | Extract Design Matrix from Point Process Model | |

pppmatching | Create a Point Matching | |

psp.object | Class of Line Segment Patterns | |

rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |

rmh.ppm | Simulate from a Fitted Point Process Model | |

is.marked.ppp | Test Whether A Point Pattern is Marked | |

quadrats | Divide Region into Quadrats | |

is.multitype.ppp | Test Whether A Point Pattern is Multitype | |

rpoisline | Generate Poisson Random Line Process | |

subsetget.im | Reset Values in Subset of Image | |

rcell | Simulate Baddeley-Silverman Cell Process | |

rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |

reduced.sample | Reduced Sample Estimator using Histogram Data | |

quadrat.test.splitppp | Chi-Squared Test of CSR for Split Point Pattern | |

rescale.owin | Convert Window to Another Unit of Length | |

rlinegrid | Generate grid of parallel lines with random displacement | |

update.ppm | Update a Fitted Point Process Model | |

summary.splitppp | Summary of a Split Point Pattern | |

quadratresample | Resample a Point Pattern by Resampling Quadrats | |

redwood | California Redwoods Point Pattern (Ripley's Subset) | |

rGaussPoisson | Simulate Gauss-Poisson Process | |

rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |

rescale.im | Convert Pixel Image to Another Unit of Length | |

runifpoint | Generate N Uniform Random Points | |

rshift.splitppp | Randomly Shift a List of Point Patterns | |

owin.object | Class owin | |

nndist | Nearest neighbour distances | |

shift.owin | Apply Vector Translation To Window | |

japanesepines | Japanese Pines Point Pattern | |

rmpoispp | Generate Multitype Poisson Point Pattern | |

rpoispp | Generate Poisson Point Pattern | |

shift.im | Apply Vector Translation To Pixel Image | |

shift.psp | Apply Vector Translation To Line Segment Pattern | |

rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |

rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |

persp.im | Perspective Plot of Pixel Image | |

rshift.ppp | Randomly Shift a Point Pattern | |

pairsat.family | Saturated Pairwise Interaction Point Process Family | |

pairdist.default | Pairwise distances | |

solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |

swedishpines | Swedish Pines Point Pattern | |

rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |

split.ppp | Divide Point Pattern into Sub-patterns | |

smooth.ppp | Spatial smoothing of observations at irregular points | |

split.im | Divide Image Into Sub-images | |

spatstat.options | Internal Options in Spatstat Package | |

subset.fasp | Extract Subset of Function Array | |

rescue.rectangle | Convert Window Back To Rectangle | |

[.tess | Extract or Replace Subset of Tessellation | |

subset.psp | Extract Subset of Line Segment Pattern | |

summary.owin | Summary of a Spatial Window | |

suffstat | Sufficient Statistic of Point Process Model | |

spruces | Spruces Point Pattern | |

unmark | Remove Marks | |

tess | Create a Tessellation | |

print.quad | Print a Quadrature Scheme | |

trim.rectangle | Cut margins from rectangle | |

raster.x | Cartesian Coordinates for a Pixel Raster | |

rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |

unitname | Name for Unit of Length | |

Poisson | Poisson Point Process Model | |

allstats | Calculate four standard summary functions of a point pattern. | |

vertices | Vertices of a Window | |

subset.fv | Extract Subset of Function Values | |

reach | Interaction Distance of a Point Process | |

rotate | Rotate | |

spatstat-deprecated | Deprecated spatstat functions | |

crossdist.default | Pairwise distances between two different sets of points | |

rshift | Random Shift | |

scanpp | Read Point Pattern From Data File | |

plot.fv | Plot Function Valuesn | |

summary.ppm | Summarizing a Fitted Point Process Model | |

summary.ppp | Summary of a Point Pattern Dataset | |

rpoint | Generate N Random Points | |

subset.ppp | Extract or Replace Subset of Point Pattern | |

with.fv | Evaluate an Expression in a Function Table | |

tiles | Extract List of Tiles in a Tessellation | |

shift | Apply Vector Translation | |

shift.ppp | Apply Vector Translation To Point Pattern | |

rMaternII | Simulate Matern Model II | |

rotate.ppp | Rotate a Point Pattern | |

setmarks | Set or Reset the Marks in a Point Pattern | |

vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |

subset.splitppp | Extract or Replace Sub-Patterns | |

pcf | Pair Correlation Function | |

No Results! |

## Last month downloads

## Details

Date | 30 January 2009 |

License | GPL (>= 2) |

URL | http://www.spatstat.org |

Packaged | Sat Jan 31 10:38:21 2009; adrian |

depends | base (>= 2.7.0) , deldir (>= 0.0-7) , gpclib , graphics , mgcv , R (>= 2.7.0) , stats , utils |

suggests | maptools , sm |

Contributors | Rolf Turner, Adrian Baddeley |

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