# spatstat v1.8-9

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

Spatial Point Pattern data analysis, modelling and simulation
including multitype/marked points and spatial covariates

## Functions in spatstat

Name | Description | |

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

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

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

betacells | Beta Ganglion Cells in Cat Retina | |

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

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

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

plot.owin | Plot a Spatial Window | |

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

Fest | Estimate the empty space function F | |

Ord | Generic Ord Interaction model | |

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

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

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

angles.psp | Orientation Angles of Line Segments | |

ppm | Fit Point Process Model to Data | |

im.object | Class of Images | |

bramblecanes | Hutchings' Bramble Canes data | |

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

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

Kcross.inhom | Inhomogeneous Cross K Function | |

is.marked | Test Whether Marks Are Present | |

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

Kest.fft | K-function using FFT | |

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

erode.owin | Erode a Window | |

affine.owin | Apply Affine Transformation To Window | |

midpoints.psp | Midpoints of Line Segment Pattern | |

DiggleGratton | Diggle-Gratton model | |

amacrine | Hughes' Amacrine Cell Data | |

centroid.owin | Centroid of a window | |

fv.object | Data Frames of Function Values | |

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

bdist.points | Distance to Boundary of Window | |

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

MultiStrauss | The Multitype Strauss Point Process Model | |

spruces | Spruces Point Pattern | |

spatstat | The Spatstat Package | |

rsyst | Systematic random point pattern | |

as.rectangle | Window Frame | |

levelset | Level Set of a Pixel Image | |

Gmulti | Marked Nearest Neighbour Distance Function | |

Softcore | The Soft Core Point Process Model | |

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

Saturated | Saturated Pairwise Interaction model | |

Iest | Estimate the I-function | |

lurking | Lurking variable plot | |

Poisson | Poisson Point Process Model | |

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

affine | Apply Affine Transformation | |

subset.fasp | Extract Subset of Function Array | |

Gest | Nearest Neighbour Distance Function G | |

append.psp | Combine Two Line Segment Patterns | |

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

cells | Biological Cells Point Pattern | |

corners | Corners of a rectangle | |

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

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

Pairwise | Generic Pairwise Interaction model | |

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

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

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

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

harmonic | Basis for Harmonic Functions | |

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

longleaf | Longleaf Pines Point Pattern | |

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

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

distmap.ppp | Distance Map of Point Pattern | |

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

markcorr | Mark Correlation Function | |

nztrees | New Zealand Trees Point Pattern | |

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

concatxy | Concatenate x,y Coordinate Vectors | |

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

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

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

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

Strauss | The Strauss Point Process Model | |

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

pairdist.default | Pairwise distances | |

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

square | Square Window | |

nndist | Nearest neighbour distances | |

rThomas | Simulate Thomas Process | |

rpoint | Generate N Random Points | |

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

pairdist.psp | Pairwise distances between line segments | |

Jest | Estimate the J-function | |

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

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

rescue.rectangle | Convert Window Back To Rectangle | |

ppp | Create a Point Pattern | |

ripras | Estimate window from points alone | |

japanesepines | Japanese Pines Point Pattern | |

eem | Exponential Energy Marks | |

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

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

rmpoispp | Generate Multitype Poisson Point Pattern | |

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

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

rmpoint | Generate N Random Multitype Points | |

as.im | Convert to Pixel Image | |

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

as.psp | Convert Data To Class psp | |

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

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

rotate.psp | Rotate a Line Segment Pattern | |

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

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

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

simdat | Simulated Point Pattern | |

Kest | K-function | |

bounding.box | Bounding Box of a Window | |

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

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

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

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

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

pairwise.family | Pairwise Interaction Process Family | |

rSSI | Simple Sequential Inhibition | |

plot.fasp | Plot a Function Array | |

distmap | Distance Map | |

pairdist.ppp | Pairwise distances | |

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

eval.fv | Evaluate Expression Involving Functions | |

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

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

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

area.owin | Area of a Window | |

swedishpines | Swedish Pines Point Pattern | |

rMaternII | Simulate Matern Model II | |

complement.owin | Take Complement of a Window | |

rotate | Rotate | |

plot.quad | plot a Spatial Quadrature Scheme | |

expand.owin | Expand Window By Factor | |

envelope | Simulation envelopes of summary function | |

summary.owin | Summary of a Spatial Window | |

ppp.object | Class of Point Patterns | |

lansing | Lansing Woods Point Pattern | |

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

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

quadratcount | Quadrat counting for a point pattern | |

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

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

diameter | Diameter of a Window Frame | |

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

setcov | Set Covariance of a Window | |

pcf | Pair Correlation Function | |

summary.im | Summarizing a Pixel Image | |

chorley | Chorley-Ribble Cancer Data | |

copper | Berman-Huntington points and lines data | |

dilate.owin | Dilate a Window | |

Jmulti | Marked J Function | |

rpoispp | Generate Poisson Point Pattern | |

subset.fv | Extract Subset of Function Values | |

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

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

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

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

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

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

LennardJones | The Lennard-Jones Potential | |

ants | Harkness-Isham ants' nests data | |

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

owin | Create a Window | |

bdist.pixels | Distance to Boundary of Window | |

unmark | Remove Marks from a Marked Point Pattern | |

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

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

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

rlabel | Random Re-Labelling of Point Pattern | |

distmap.owin | Distance Map of Window | |

reach | Interaction Distance of a Point Process | |

quantile.im | Sample Quantiles of Pixel Image | |

eroded.areas | Areas of Morphological Erosions | |

crossdist | Pairwise distances | |

Geyer | Geyer's Saturation Point Process Model | |

Kmulti | Marked K-Function | |

rotate.ppp | Rotate a Point Pattern | |

endpoints.psp | Endpoints of Line Segment Pattern | |

lengths.psp | Lengths of Line Segments | |

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

rotate.owin | Rotate a Window | |

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

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

rshift.ppp | Randomly Shift a Point Pattern | |

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

im | Create a Pixel Image Object | |

rstrat | Stratified random point pattern | |

Kmeasure | Reduced Second Moment Measure | |

as.ppp | Convert Data To Class ppp | |

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

print.quad | Print a Quadrature Scheme | |

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

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

fasp.object | Function Arrays for Spatial Patterns | |

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

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

psp | Create a Line Segment Pattern | |

spatstat-deprecated | Deprecated spatstat functions | |

spokes | Spokes pattern of dummy points | |

plot.im | Plot a Pixel Image | |

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

nnwhich | Nearest neighbour | |

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

ord.family | Ord Interaction Process Family | |

finpines | Pine saplings in Finland. | |

psp.object | Class of Line Segment Patterns | |

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

plot.fv | Plot Function Valuesn | |

hamster | Aherne's hamster tumour data | |

owin.object | Class owin | |

rMaternI | Simulate Matern Model I | |

scanpp | Read Point Pattern From Data File | |

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

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

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

spatstat-internal | Internal spatstat functions | |

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

gridweights | Compute Quadrature Weights Based on Grid Counts | |

rMatClust | Simulate Matern Cluster Process | |

superimpose | Superimpose Several Point Patterns | |

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

Kinhom | Inhomogeneous K-function | |

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

eval.im | Evaluate Expression Involving Pixel Images | |

spatstat.options | Internal Options in Spatstat Package | |

letterR | Window in Shape of Letter R | |

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

OrdThresh | Ord's Interaction model | |

demopat | Artificial Data Point Pattern | |

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

suffstat | Sufficient Statistic of Point Process Model | |

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

gridcentres | Rectangular grid of points | |

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

as.owin | Convert Data To Class owin | |

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

shift | Apply Vector Translation | |

pairdist | Pairwise distances | |

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

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

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

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

rpoisline | Generate Poisson Random Line Process | |

plot.ppp | plot a Spatial Point Pattern | |

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

rshift | Random Shift | |

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

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

subset.im | Extract Subset of Image | |

summary.quad | Summarizing a Quadrature Scheme | |

quad.object | Class of Quadrature Schemes | |

rcell | Simulate Baddeley-Silverman Cell Process | |

runifpoint | Generate N Uniform Random Points | |

shift.owin | Apply Vector Translation To Window | |

rNeymanScott | Simulate Neyman-Scott Process | |

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

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## Last month downloads

## Details

Date | 18 April 2006 |

License | GPL version 2 or newer |

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

Packaged | Wed Apr 19 16:18:48 2006; adrian |

depends | base (>= 2.2.0) , mgcv , R (>= 2.2.0) , sm |

Contributors | Rolf Turner, Adrian Baddeley |

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