# spatstat v1.11-7

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 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 | |

Kmeasure | Reduced Second Moment Measure | |

affine | Apply Affine Transformation | |

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

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

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

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

fv.object | Data Frames of Function Values | |

Kmulti | Marked K-Function | |

ewcdf | Weighted Empirical Cumulative Distribution Function | |

Geyer | Geyer's Saturation Point Process Model | |

spatstat | The Spatstat Package | |

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

Gest | Nearest Neighbour Distance Function G | |

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

cells | Biological Cells Point Pattern | |

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

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

append.psp | Combine Two Line Segment Patterns | |

cut.ppp | Convert Point Pattern Marks from Numeric to Factor | |

area.owin | Area of a Window | |

affine.owin | Apply Affine Transformation To Window | |

Iest | Estimate the I-function | |

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

gridcentres | Rectangular grid of points | |

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

as.ppp | Convert Data To Class ppp | |

DiggleGratton | Diggle-Gratton model | |

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

diameter | Diameter of a Window | |

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

quad.object | Class of Quadrature Schemes | |

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

disc | Circular Window | |

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

owin | Create a Window | |

rMaternI | Simulate Matern Model I | |

clickppp | Interactively Add Points | |

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

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

interp.im | Interpolate a Pixel Image | |

spatstat-deprecated | Deprecated spatstat functions | |

plot.ppp | plot a Spatial Point Pattern | |

betacells | Beta Ganglion Cells in Cat Retina | |

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

distmap | Distance Map | |

eem | Exponential Energy Marks | |

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

copper | Berman-Huntington points and lines data | |

im.object | Class of Images | |

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

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

Saturated | Saturated Pairwise Interaction model | |

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

gridweights | Compute Quadrature Weights Based on Grid Counts | |

rcell | Simulate Baddeley-Silverman Cell Process | |

rMaternII | Simulate Matern Model II | |

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

im | Create a Pixel Image Object | |

rMatClust | Simulate Matern Cluster Process | |

rotate.ppp | Rotate a Point Pattern | |

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

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

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

rThomas | Simulate Thomas Process | |

ripras | Estimate window from points alone | |

rsyst | Simulate systematic random point pattern | |

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

rStrauss | Perfect Simulation of the Strauss Process | |

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

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

ppm | Fit Point Process Model to Data | |

rSSI | Simulate Simple Sequential Inhibition | |

mean.im | Mean Pixel Value in an Image | |

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

simdat | Simulated Point Pattern | |

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

rshift | Random Shift | |

is.marked | Test Whether Marks Are Present | |

pairdist | Pairwise distances | |

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

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

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

pairwise.family | Pairwise Interaction Process Family | |

pairdist.ppp | Pairwise distances | |

ord.family | Ord Interaction Process Family | |

pppdist | Optimal Match Between Two Point Patterns | |

psp.object | Class of Line Segment Patterns | |

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

Jest | Estimate the J-function | |

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

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

plot.im | Plot a Pixel Image | |

psp | Create a Line Segment Pattern | |

levelset | Level Set of a Pixel Image | |

rescue.rectangle | Convert Window Back To Rectangle | |

plot.quad | plot a Spatial Quadrature Scheme | |

Kest | K-function | |

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

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

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

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

rotate.psp | Rotate a Line Segment Pattern | |

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

spruces | Spruces Point Pattern | |

rpoisline | Generate Poisson Random Line Process | |

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

Kest.fft | K-function using FFT | |

square | Square Window | |

clickpoly | Interactively Define a Polygon | |

rmpoispp | Generate Multitype Poisson Point Pattern | |

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

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

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

angles.psp | Orientation Angles of Line Segments | |

owin.object | Class owin | |

print.quad | Print a Quadrature Scheme | |

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

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

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

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

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

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

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

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

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

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

persp.im | Perspective Plot of Pixel Image | |

Pairwise | Generic Pairwise Interaction model | |

crossdist | Pairwise distances | |

expand.owin | Expand Window By Factor | |

corners | Corners of a rectangle | |

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

midpoints.psp | Midpoints of Line Segment Pattern | |

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

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

endpoints.psp | Endpoints of Line Segment Pattern | |

ks.test.ppm | Kolmogorov-Smirnov Test for Point Process Model | |

lengths.psp | Lengths of Line Segments | |

japanesepines | Japanese Pines Point Pattern | |

pcf | Pair Correlation Function | |

nztrees | New Zealand Trees Point Pattern | |

centroid.owin | Centroid of a window | |

subset.fv | Extract Subset of Function Values | |

reach | Interaction Distance of a Point Process | |

rshift.ppp | Randomly Shift a Point Pattern | |

convexhull.xy | Convex Hull of Points | |

subset.im | Extract Subset of Image | |

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

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

mincontrast | Method of Minimum Contrast | |

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

rpoispp | Generate Poisson Point Pattern | |

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

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

envelope | Simulation envelopes of summary function | |

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

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

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

runifpoint | Generate N Uniform Random Points | |

plot.owin | Plot a Spatial Window | |

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

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

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

is.multitype | Test whether Object is Multitype | |

trim.rectangle | Cut margins from rectangle | |

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

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

rescale | Convert dataset to another unit of length | |

rotate | Rotate | |

subset.fasp | Extract Subset of Function Array | |

rthin | Random Thinning | |

rstrat | Simulate Stratified Random Point Pattern | |

vertices | Vertices of a Window | |

swedishpines | Swedish Pines Point Pattern | |

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

as.im | Convert to Pixel Image | |

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

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

lansing | Lansing Woods Point Pattern | |

plot.fasp | Plot a Function Array | |

ppp | Create a Point Pattern | |

Gmulti | Marked Nearest Neighbour Distance Function | |

Jmulti | Marked J Function | |

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

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

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

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

Kinhom | Inhomogeneous K-function | |

LennardJones | The Lennard-Jones Potential | |

distmap.owin | Distance Map of Window | |

contour.im | Contour plot of pixel image | |

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

scanpp | Read Point Pattern From Data File | |

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

as.owin | Convert Data To Class owin | |

demopat | Artificial Data Point Pattern | |

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

concatxy | Concatenate x,y Coordinate Vectors | |

distmap.ppp | Distance Map of Point Pattern | |

ants | Harkness-Isham ants' nests data | |

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

longleaf | Longleaf Pines Point Pattern | |

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

hamster | Aherne's hamster tumour data | |

profilepl | Profile Maximum Pseudolikelihood | |

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

letterR | Window in Shape of Letter R | |

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

lurking | Lurking variable plot | |

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

shift | Apply Vector Translation | |

superimpose | Superimpose Several Point Patterns | |

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

setcov | Set Covariance of a Window | |

progressreport | Print Progress Reports | |

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

spatstat.options | Internal Options in Spatstat Package | |

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

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

shift.owin | Apply Vector Translation To Window | |

unmark | Remove Marks from a Marked Point Pattern | |

Strauss | The Strauss Point Process Model | |

bdist.points | Distance to Boundary of Window | |

erode.owin | Erode a Window | |

markcorr | Mark Correlation Function | |

dilate.owin | Dilate a Window | |

eval.fv | Evaluate Expression Involving Functions | |

harmonic | Basis for Harmonic Functions | |

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

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

nncross | Nearest Neighbour in Another Point Pattern | |

rNeymanScott | Simulate Neyman-Scott Process | |

nnwhich | Nearest neighbour | |

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

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

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

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

summary.owin | Summary of a Spatial Window | |

as.psp | Convert Data To Class psp | |

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

eval.im | Evaluate Expression Involving Pixel Images | |

plot.listof | Plot a List of Things | |

rmpoint | Generate N Random Multitype Points | |

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

units | Name for Unit of Length | |

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

Fest | Estimate the empty space function F | |

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

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

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

Softcore | The Soft Core Point Process Model | |

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

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

spatstat-internal | Internal spatstat functions | |

pairdist.default | Pairwise distances | |

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

plot.fv | Plot Function Valuesn | |

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

rlabel | Random Re-Labelling of Point Pattern | |

rpoint | Generate N Random Points | |

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

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

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

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

bei | Tropical rain forest trees | |

Kcross.inhom | Inhomogeneous Cross K Function | |

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

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

amacrine | Hughes' Amacrine Cell Data | |

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

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

Poisson | Poisson Point Process Model | |

rotate.owin | Rotate a Window | |

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

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

anemones | Beadlet Anemones Data | |

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

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

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

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

as.rectangle | Window Frame | |

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

summary.im | Summarizing a Pixel Image | |

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

quantile.im | Sample Quantiles of Pixel Image | |

Ord | Generic Ord Interaction model | |

chorley | Chorley-Ribble Cancer Data | |

MultiStrauss | The Multitype Strauss Point Process Model | |

pairdist.psp | Pairwise distances between line segments | |

bdist.pixels | Distance to Boundary of Window | |

nbfires | Point Patterns of New Brunswick Forest Fires | |

fasp.object | Function Arrays for Spatial Patterns | |

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

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

spokes | Spokes pattern of dummy points | |

OrdThresh | Ord's Interaction model | |

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

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

finpines | Pine saplings in Finland. | |

clarkevans | Clark and Evans Aggregation Index | |

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

eroded.areas | Areas of Morphological Erosions | |

nndist | Nearest neighbour distances | |

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

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

ppp.object | Class of Point Patterns | |

summary.quad | Summarizing a Quadrature Scheme | |

suffstat | Sufficient Statistic of Point Process Model | |

bramblecanes | Hutchings' Bramble Canes data | |

complement.owin | Take Complement of a Window | |

quadratcount | Quadrat counting for a point pattern | |

No Results! |

## Last month downloads

## Details

Date | 9 June 2007 |

License | GPL version 2 or newer |

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

Packaged | Tue Jun 12 02:00:25 2007; adrian |

depends | base (>= 2.4.0) , graphics , mgcv , R (>= 2.4.0) , stats |

suggests | deldir , sm |

Contributors | Rolf Turner, Adrian Baddeley |

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