# spatstat v1.9-2

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, 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 | |

betacells | Beta Ganglion Cells in Cat Retina | |

as.rectangle | Window Frame | |

append.psp | Combine Two Line Segment Patterns | |

midpoints.psp | Midpoints of Line Segment Pattern | |

Saturated | Saturated Pairwise Interaction model | |

corners | Corners of a rectangle | |

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

Gmulti | Marked Nearest Neighbour Distance Function | |

pairwise.family | Pairwise Interaction Process Family | |

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

eem | Exponential Energy Marks | |

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

centroid.owin | Centroid of a window | |

rmpoispp | Generate Multitype Poisson Point Pattern | |

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

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

distmap.ppp | Distance Map of Point Pattern | |

markcorr | Mark Correlation Function | |

Iest | Estimate the I-function | |

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

Strauss | The Strauss Point Process Model | |

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

eval.fv | Evaluate Expression Involving Functions | |

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

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

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

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

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

owin | Create a Window | |

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

rotate.psp | Rotate a Line Segment Pattern | |

Gest | Nearest Neighbour Distance Function G | |

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

rshift | Random Shift | |

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

copper | Berman-Huntington points and lines data | |

suffstat | Sufficient Statistic of Point Process Model | |

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

angles.psp | Orientation Angles of Line Segments | |

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

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

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

Jest | Estimate the J-function | |

as.im | Convert to Pixel Image | |

bdist.points | Distance to Boundary of Window | |

complement.owin | Take Complement of a Window | |

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

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

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

diameter | Diameter of a Window Frame | |

ppp.object | Class of Point Patterns | |

rlabel | Random Re-Labelling of Point Pattern | |

Ord | Generic Ord Interaction model | |

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

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

rotate.owin | Rotate a Window | |

cells | Biological Cells Point Pattern | |

longleaf | Longleaf Pines Point Pattern | |

runifpoint | Generate N Uniform Random Points | |

erode.owin | Erode a Window | |

Kest | K-function | |

finpines | Pine saplings in Finland. | |

spatstat | The Spatstat Package | |

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

crossdist | Pairwise distances | |

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

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

profilepl | Profile Maximum Pseudolikelihood | |

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

pairdist.psp | Pairwise distances between line segments | |

levelset | Level Set of a Pixel Image | |

rMaternII | Simulate Matern Model II | |

reach | Interaction Distance of a Point Process | |

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

Fest | Estimate the empty space function F | |

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

LennardJones | The Lennard-Jones Potential | |

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

psp | Create a Line Segment Pattern | |

rstrat | Stratified random point pattern | |

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

DiggleGratton | Diggle-Gratton model | |

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

Pairwise | Generic Pairwise Interaction model | |

Kmeasure | Reduced Second Moment Measure | |

expand.owin | Expand Window By Factor | |

Poisson | Poisson Point Process Model | |

dilate.owin | Dilate a Window | |

mincontrast | Method of Minimum Contrast | |

area.owin | Area of a Window | |

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

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

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

print.quad | Print a Quadrature Scheme | |

as.psp | Convert Data To Class psp | |

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

rSSI | Simple Sequential Inhibition | |

rMaternI | Simulate Matern Model I | |

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

plot.fasp | Plot a Function Array | |

swedishpines | Swedish Pines Point Pattern | |

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

summary.quad | Summarizing a Quadrature Scheme | |

fv.object | Data Frames of Function Values | |

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

harmonic | Basis for Harmonic Functions | |

gridweights | Compute Quadrature Weights Based on Grid Counts | |

subset.fv | Extract Subset of Function Values | |

ripras | Estimate window from points alone | |

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

im | Create a Pixel Image Object | |

nndist | Nearest neighbour distances | |

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

OrdThresh | Ord's Interaction model | |

demopat | Artificial Data Point Pattern | |

quad.object | Class of Quadrature Schemes | |

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

pairdist.default | Pairwise distances | |

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

setcov | Set Covariance of a Window | |

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

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

envelope | Simulation envelopes of summary function | |

ppp | Create a Point Pattern | |

ppm | Fit Point Process Model to Data | |

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

spruces | Spruces Point Pattern | |

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

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

rpoint | Generate N Random Points | |

Geyer | Geyer's Saturation Point Process Model | |

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

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

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

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

subset.im | Extract Subset of Image | |

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

MultiStrauss | The Multitype Strauss Point Process Model | |

rThomas | Simulate Thomas Process | |

Kinhom | Inhomogeneous K-function | |

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

eroded.areas | Areas of Morphological Erosions | |

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

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

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

Kmulti | Marked K-Function | |

bramblecanes | Hutchings' Bramble Canes data | |

subset.fasp | Extract Subset of Function Array | |

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

as.owin | Convert Data To Class owin | |

pairdist | Pairwise distances | |

lurking | Lurking variable plot | |

affine | Apply Affine Transformation | |

plot.ppp | plot a Spatial Point Pattern | |

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

pcf | Pair Correlation Function | |

concatxy | Concatenate x,y Coordinate Vectors | |

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

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

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

spatstat-deprecated | Deprecated spatstat functions | |

hamster | Aherne's hamster tumour data | |

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

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

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

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

rNeymanScott | Simulate Neyman-Scott Process | |

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

affine.owin | Apply Affine Transformation To Window | |

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

lengths.psp | Lengths of Line Segments | |

rpoisline | Generate Poisson Random Line Process | |

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

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

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

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

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

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

rcell | Simulate Baddeley-Silverman Cell Process | |

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

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

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

Kest.fft | K-function using FFT | |

gridcentres | Rectangular grid of points | |

distmap.owin | Distance Map of Window | |

endpoints.psp | Endpoints of Line Segment Pattern | |

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

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

square | Square Window | |

is.marked | Test Whether Marks Are Present | |

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

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

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

summary.im | Summarizing a Pixel Image | |

plot.im | Plot a Pixel Image | |

japanesepines | Japanese Pines Point Pattern | |

Kcross.inhom | Inhomogeneous Cross K Function | |

simdat | Simulated Point Pattern | |

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

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

pairdist.ppp | Pairwise distances | |

spokes | Spokes pattern of dummy points | |

as.ppp | Convert Data To Class ppp | |

plot.quad | plot a Spatial Quadrature Scheme | |

bounding.box | Bounding Box of a Window | |

quadratcount | Quadrat counting for a point pattern | |

summary.owin | Summary of a Spatial Window | |

owin.object | Class owin | |

im.object | Class of Images | |

spatstat-internal | Internal spatstat functions | |

nztrees | New Zealand Trees Point Pattern | |

rotate | Rotate | |

lansing | Lansing Woods Point Pattern | |

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

letterR | Window in Shape of Letter R | |

chorley | Chorley-Ribble Cancer Data | |

unmark | Remove Marks from a Marked Point Pattern | |

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

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

rshift.ppp | Randomly Shift a Point Pattern | |

plot.owin | Plot a Spatial Window | |

rpoispp | Generate Poisson Point Pattern | |

nnwhich | Nearest neighbour | |

superimpose | Superimpose Several Point Patterns | |

eval.im | Evaluate Expression Involving Pixel Images | |

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

Jmulti | Marked J Function | |

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

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

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

rmpoint | Generate N Random Multitype Points | |

shift | Apply Vector Translation | |

shift.owin | Apply Vector Translation To Window | |

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

amacrine | Hughes' Amacrine Cell Data | |

distmap | Distance Map | |

rMatClust | Simulate Matern Cluster Process | |

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

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

rthin | Random Thinning | |

spatstat.options | Internal Options in Spatstat Package | |

rsyst | Systematic random point pattern | |

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

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

persp.im | Perspective Plot of Pixel Image | |

plot.fv | Plot Function Valuesn | |

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

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

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

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

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

Softcore | The Soft Core Point Process Model | |

scanpp | Read Point Pattern From Data File | |

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

quantile.im | Sample Quantiles of Pixel Image | |

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

ants | Harkness-Isham ants' nests data | |

rescue.rectangle | Convert Window Back To Rectangle | |

bdist.pixels | Distance to Boundary of Window | |

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

rotate.ppp | Rotate a Point Pattern | |

fasp.object | Function Arrays for Spatial Patterns | |

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

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

ord.family | Ord Interaction Process Family | |

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

psp.object | Class of Line Segment Patterns | |

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

No Results! |

## Last month downloads

## Details

Date | 5 June 2006 |

License | GPL version 2 or newer |

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

Packaged | Mon Jun 5 11:53:50 2006; adrian |

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

suggests | sm |

Contributors | Rolf Turner, Adrian Baddeley |

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