# spatstat v1.13-0

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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.
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 | |

Kmeasure | Reduced Second Moment Measure | |

Geyer | Geyer's Saturation Point Process Model | |

BadGey | Hybrid Geyer Point Process Model | |

fv.object | Data Frames of Function Values | |

as.owin | Convert Data To Class owin | |

DiggleGratton | Diggle-Gratton model | |

pairdist.default | Pairwise distances | |

amacrine | Hughes' Amacrine Cell Data | |

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

Strauss | The Strauss Point Process Model | |

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

inforder.family | Infinite Order Interaction Family | |

distmap.ppp | Distance Map of Point Pattern | |

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

plot.fv | Plot Function Valuesn | |

anemones | Beadlet Anemones Data | |

Gmulti | Marked Nearest Neighbour Distance Function | |

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

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

eval.im | Evaluate Expression Involving Pixel Images | |

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

humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |

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

Jest | Estimate the J-function | |

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

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

spatstat | The Spatstat Package | |

plot.listof | Plot a List of Things | |

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

Fest | Estimate the empty space function F | |

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

bdist.points | Distance to Boundary of Window | |

Gest | Nearest Neighbour Distance Function G | |

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

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

Poisson | Poisson Point Process Model | |

append.psp | Combine Two Line Segment Patterns | |

nbfires | Point Patterns of New Brunswick Forest Fires | |

Kdot.inhom | Inhomogeneous Multitype K Dot Function | |

MultiStrauss | The Multitype Strauss Point Process Model | |

im.object | Class of Images | |

Pairwise | Generic Pairwise Interaction model | |

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

LennardJones | The Lennard-Jones Potential | |

Kcross.inhom | Inhomogeneous Cross K Function | |

nncross | Nearest Neighbour in Another Point Pattern | |

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

summary.im | Summarizing a Pixel Image | |

Kinhom | Inhomogeneous K-function | |

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

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

expand.owin | Expand Window By Factor | |

multiplicity.ppp | Count Multiplicity of Duplicate Points | |

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

as.im | Convert to Pixel Image | |

crossdist | Pairwise distances | |

plot.hyperframe | Plot Entries in a Hyperframe | |

owin.object | Class owin | |

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

Linhom | L-function | |

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

pairdist.ppp | Pairwise distances | |

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

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

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

erode.owin | Erode a Window | |

centroid.owin | Centroid of a window | |

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

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

complement.owin | Take Complement of a Window | |

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

quadratcount | Quadrat counting for a point pattern | |

rpoispp | Generate Poisson Point Pattern | |

Ord | Generic Ord Interaction model | |

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

pppdist | Distance Between Two Point Patterns | |

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

japanesepines | Japanese Pines Point Pattern | |

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

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

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

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

distmap.owin | Distance Map of Window | |

ants | Harkness-Isham ants' nests data | |

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

rMaternI | Simulate Matern Model I | |

AreaInter | The Area Interaction Point Process Model | |

eval.fv | Evaluate Expression Involving Functions | |

bdist.pixels | Distance to Boundary of Window | |

Kmulti | Marked K-Function | |

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

clickpoly | Interactively Define a Polygon | |

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

gridcentres | Rectangular grid of points | |

betacells | Beta Ganglion Cells in Cat Retina | |

im | Create a Pixel Image Object | |

plot.fasp | Plot a Function Array | |

bramblecanes | Hutchings' Bramble Canes data | |

as.ppp | Convert Data To Class ppp | |

bei | Tropical rain forest trees | |

clarkevans | Clark and Evans Aggregation Index | |

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

endpoints.psp | Endpoints of Line Segment Pattern | |

Jmulti | Marked J Function | |

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

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

pppmatching | Create a Point Matching | |

lengths.psp | Lengths of Line Segments | |

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

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

quad.object | Class of Quadrature Schemes | |

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

eem | Exponential Energy Marks | |

rmpoint | Generate N Random Multitype Points | |

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

quantile.im | Sample Quantiles of Pixel Image | |

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

Lest | L-function | |

finpines | Pine saplings in Finland. | |

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

ponderosa | Ponderosa Pine Tree Point Pattern | |

envelope | Simulation envelopes of summary function | |

contour.im | Contour plot of pixel image | |

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

as.rectangle | Window Frame | |

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

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

diameter | Diameter of a Window | |

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

letterR | Window in Shape of Letter R | |

ppm | Fit Point Process Model to Data | |

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

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

markcorr | Mark Correlation Function | |

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

pairdist.psp | Pairwise distances between line segments | |

rNeymanScott | Simulate Neyman-Scott Process | |

fasp.object | Function Arrays for Spatial Patterns | |

ewcdf | Weighted Empirical Cumulative Distribution Function | |

Saturated | Saturated Pairwise Interaction model | |

lurking | Lurking variable plot | |

lansing | Lansing Woods Point Pattern | |

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

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

Softcore | The Soft Core Point Process Model | |

OrdThresh | Ord's Interaction model | |

Iest | Estimate the I-function | |

convexhull.xy | Convex Hull of Points | |

as.psp | Convert Data To Class psp | |

copper | Berman-Huntington points and lines data | |

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

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

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

vertices | Vertices of a Window | |

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

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

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

corners | Corners of a rectangle | |

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

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

spatstat.options | Internal Options in Spatstat Package | |

plot.quad | plot a Spatial Quadrature Scheme | |

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

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

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

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

is.marked | Test Whether Marks Are Present | |

spatstat-internal | Internal spatstat functions | |

interp.im | Interpolate a Pixel Image | |

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

nndist | Nearest neighbour distances | |

scanpp | Read Point Pattern From Data File | |

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

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

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

mincontrast | Method of Minimum Contrast | |

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

gridweights | Compute Quadrature Weights Based on Grid Counts | |

summary.quad | Summarizing a Quadrature Scheme | |

suffstat | Sufficient Statistic of Point Process Model | |

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

rMatClust | Simulate Matern Cluster Process | |

is.multitype | Test whether Object is Multitype | |

eroded.areas | Areas of Morphological Erosions | |

rcell | Simulate Baddeley-Silverman Cell Process | |

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

pairwise.family | Pairwise Interaction Process Family | |

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

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

rSSI | Simulate Simple Sequential Inhibition | |

demopat | Artificial Data Point Pattern | |

model.images | Compute Images of Constructed Covariates | |

disc | Circular Window | |

affine.owin | Apply Affine Transformation To Window | |

nnwhich | Nearest neighbour | |

pairdist | Pairwise distances | |

dilate.owin | Dilate a Window | |

clickppp | Interactively Add Points | |

matchingdist | Distance for a Point Pattern Matching | |

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

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

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

ord.family | Ord Interaction Process Family | |

progressreport | Print Progress Reports | |

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

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

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

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

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

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

trim.rectangle | Cut margins from rectangle | |

Kest.fft | K-function using FFT | |

cells | Biological Cells Point Pattern | |

simdat | Simulated Point Pattern | |

plot.im | Plot a Pixel Image | |

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

rlabel | Random Re-Labelling of Point Pattern | |

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

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

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

chorley | Chorley-Ribble Cancer Data | |

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

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

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

hamster | Aherne's hamster tumour data | |

print.quad | Print a Quadrature Scheme | |

harmonic | Basis for Harmonic Functions | |

rStrauss | Perfect Simulation of the Strauss Process | |

ppp | Create a Point Pattern | |

longleaf | Longleaf Pines Point Pattern | |

psp.object | Class of Line Segment Patterns | |

rescue.rectangle | Convert Window Back To Rectangle | |

rotate | Rotate | |

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

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

reach | Interaction Distance of a Point Process | |

spatstat-deprecated | Deprecated spatstat functions | |

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

rsyst | Simulate systematic random point pattern | |

midpoints.psp | Midpoints of Line Segment Pattern | |

distmap | Distance Map | |

rpoint | Generate N Random Points | |

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

rstrat | Simulate Stratified Random Point Pattern | |

ppp.object | Class of Point Patterns | |

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

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

pppmatching.object | Class of Point Matchings | |

runifpoint | Generate N Uniform Random Points | |

superimpose | Superimpose Several Point Patterns | |

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

shift.owin | Apply Vector Translation To Window | |

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

hyperframe | Hyper Data Frame | |

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

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

affine | Apply Affine Transformation | |

ripras | Estimate window from points alone | |

localK | Neighbourhood density function | |

rGaussPoisson | Simulate Gauss-Poisson Process | |

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

area.owin | Area of a Window | |

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

rshift.ppp | Randomly Shift a Point Pattern | |

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

areadiff | Difference of Disc Areas | |

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

setcov | Set Covariance of a Window | |

nztrees | New Zealand Trees Point Pattern | |

summary.owin | Summary of a Spatial Window | |

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

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

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

levelset | Level Set of a Pixel Image | |

unmark | Remove Marks from a Marked Point Pattern | |

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

persp.im | Perspective Plot of Pixel Image | |

rpoisline | Generate Poisson Random Line Process | |

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

rmpoispp | Generate Multitype Poisson Point Pattern | |

rshift | Random Shift | |

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

Kest | K-function | |

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

angles.psp | Orientation Angles of Line Segments | |

rotate.ppp | Rotate a Point Pattern | |

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

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

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

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

subset.fasp | Extract Subset of Function Array | |

psp | Create a Line Segment Pattern | |

subset.fv | Extract Subset of Function Values | |

rotate.psp | Rotate a Line Segment Pattern | |

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

subset.im | Extract Subset of Image | |

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

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

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

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

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

profilepl | Profile Maximum Pseudolikelihood | |

spruces | Spruces Point Pattern | |

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

rescale | Convert dataset to another unit of length | |

rThomas | Simulate Thomas Process | |

rotate.owin | Rotate a Window | |

shift | Apply Vector Translation | |

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

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

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

concatxy | Concatenate x,y Coordinate Vectors | |

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

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

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

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

square | Square Window | |

spokes | Spokes pattern of dummy points | |

owin | Create a Window | |

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

swedishpines | Swedish Pines Point Pattern | |

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

unitname | Name for Unit of Length | |

pcf | Pair Correlation Function | |

plot.owin | Plot a Spatial Window | |

plot.ppp | plot a Spatial Point Pattern | |

rMaternII | Simulate Matern Model II | |

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

rthin | Random Thinning | |

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

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

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

No Results! |

## Last month downloads

## Details

Date | 11 April 2008 |

License | GPL (>= 2) |

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

Packaged | Sat Apr 12 01:09:17 2008; adrian |

depends | base (>= 2.6.0) , graphics , mgcv , R (>= 2.6.0) , stats |

suggests | deldir , sm |

Contributors | Rolf Turner, Adrian Baddeley |

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