spatstat v1.25-1
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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. Also supports three-dimensional point patterns, and space-time point patterns in any number of dimensions.
Contains over 1000 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, pixel images and tessellations.
Exploratory methods include K-functions, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics etc.
Point process models can be fitted to point pattern data using functions ppm, kppm, slrm similar to glm. Models may include dependence on covariates, interpoint interaction, cluster formation 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 | |
G3est | Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern | |
Kmodel | K function of a model | |
Extract.fasp | Extract Subset of Function Array | |
as.rectangle | Window Frame | |
Kest | K-function | |
Kest.fft | K-function using FFT | |
PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
Kmulti | Marked K-Function | |
cells | Biological Cells Point Pattern | |
clarkevans.test | Clark and Evans Test | |
density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
fv | Create a Function Value Table | |
km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
Lcross.inhom | Inhomogeneous Cross Type L Function | |
kppm | Fit Cluster or Cox Point Process Model | |
OrdThresh | Ord's Interaction model | |
is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
allstats | Calculate four standard summary functions of a point pattern. | |
marks.psp | Marks of a Line Segment Pattern | |
chorley | Chorley-Ribble Cancer Data | |
convexhull.xy | Convex Hull of Points | |
methods.pp3 | Methods for three-dimensional point patterns | |
methods.distfun | Methods for Distance Functions | |
anova.slrm | Analysis of Deviance for Spatial Logistic Regression Models | |
as.hyperframe.ppx | Extract coordinates and marks of multidimensional point pattern | |
multiplicity.ppp | Count Multiplicity of Duplicate Points | |
bdist.points | Distance to Boundary of Window | |
crossdist.ppx | Pairwise Distances Between Two Different Multi-Dimensional Point Patterns | |
dilated.areas | Areas of Morphological Dilations | |
clarkevans | Clark and Evans Aggregation Index | |
ord.family | Ord Interaction Process Family | |
colourmap | Colour Lookup Tables | |
pixelquad | Quadrature Scheme Based on Pixel Grid | |
pcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Type-i-To-Any-Type) | |
is.marked.ppm | Test Whether A Point Process Model is Marked | |
pool.rat | Pool Data from Several Ratio Objects | |
disc | Circular Window | |
localKinhom | Inhomogeneous Neighbourhood Density Function | |
ppp | Create a Point Pattern | |
density.psp | Kernel Smoothing of Line Segment Pattern | |
crossdist.default | Pairwise distances between two different sets of points | |
spatstat-deprecated | Deprecated spatstat functions | |
ponderosa | Ponderosa Pine Tree Point Pattern | |
DiggleGatesStibbard | Diggle-Gates-Stibbard Point Process Model | |
rknn | Theoretical Distribution of Nearest Neighbour Distance | |
methods.kppm | Methods for Cluster Point Process Models | |
matclust.estpcf | Fit the Matern Cluster Point Process by Minimum Contrast Using Pair Correlation | |
Geyer | Geyer's Saturation Point Process Model | |
rgbim | Create Colour-Valued Pixel Image | |
Softcore | The Soft Core Point Process Model | |
harmonise.im | Make Pixel Images Compatible | |
Tstat | Third order summary statistic | |
inside.owin | Test Whether Points Are Inside A Window | |
as.function.fv | Convert Function Value Table to Function | |
Extract.psp | Extract Subset of Line Segment Pattern | |
pppdist | Distance Between Two Point Patterns | |
Gres | Residual G Function | |
quad.object | Class of Quadrature Schemes | |
rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |
affine.ppp | Apply Affine Transformation To Point Pattern | |
shift.psp | Apply Vector Translation To Line Segment Pattern | |
quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
BadGey | Hybrid Geyer Point Process Model | |
Jmulti | Marked J Function | |
ants | Harkness-Isham ants' nests data | |
as.data.frame.im | Convert Pixel Image to Data Frame | |
linearK | Linear K Function | |
Gcom | Model Compensator of Nearest Neighbour Function | |
Fest | Estimate the empty space function F | |
summary.splitppp | Summary of a Split Point Pattern | |
Poisson | Poisson Point Process Model | |
smooth.msr | Smooth a Signed or Vector-Valued Measure | |
alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern | |
colourtools | Convert and Compare Colours in Different Formats | |
Iest | Estimate the I-function | |
matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
mean.im | Maximum, Minimum, Mean, Median, Range or Sum of Pixel Values in an Image | |
affine.psp | Apply Affine Transformation To Line Segment Pattern | |
anova.lppm | ANOVA for Fitted Point Process Models on Linear Network | |
copper | Berman-Huntington points and lines data | |
Kinhom | Inhomogeneous K-function | |
as.mask.psp | Convert Line Segment Pattern to Binary Pixel Mask | |
bdist.tiles | Distance to Boundary of Window | |
rNeymanScott | Simulate Neyman-Scott Process | |
boxx | Multi-Dimensional Box | |
DiggleGratton | Diggle-Gratton model | |
bounding.box | Bounding Box of a Window or Point Pattern | |
discretise | Safely Convert Point Pattern Window to Binary Mask | |
Hardcore | The Hard Core Point Process Model | |
rSSI | Simulate Simple Sequential Inhibition | |
Extract.splitppp | Extract or Replace Sub-Patterns | |
affine | Apply Affine Transformation | |
Jcross | Multitype J Function (i-to-j) | |
nnwhich.ppx | Nearest Neighbours in Any Dimensions | |
pairs.im | Scatterplot Matrix for Pixel Images | |
default.expand | Compute Expansion Window for Simulation | |
as.hyperframe | Convert Data to Hyperframe | |
coords | Extract or Change Coordinates of a Spatial or Spatiotemporal Point Pattern | |
flu | Influenza Virus Proteins | |
border | Border Region of a Window | |
rpoislpp | Poisson Point Process on a Linear Network | |
applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
runifpoint | Generate N Uniform Random Points | |
amacrine | Hughes' Amacrine Cell Data | |
cut.ppp | Classify Points in a Point Pattern | |
hist.im | Histogram of Pixel Values in an Image | |
coef.slrm | Coefficients of Fitted Spatial Logistic Regression Model | |
selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
bermantest | Berman's Tests for Point Process Model | |
plot.colourmap | Plot a Colour Map | |
distmap.owin | Distance Map of Window | |
envelope.lpp | Envelope for Point Patterns on Linear Network | |
default.rmhcontrol | Set Default Control Parameters for Metropolis-Hastings Algorithm. | |
convexhull | Convex Hull | |
as.interact | Extract Interaction Structure | |
as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |
is.subset.owin | Determine Whether One Window is Contained In Another | |
pppmatching.object | Class of Point Matchings | |
as.ppp | Convert Data To Class ppp | |
is.owin | Test Whether An Object Is A Window | |
bw.diggle | Cross Validated Bandwidth Selection for Kernel Density | |
as.data.frame.hyperframe | Coerce Hyperframe to Data Frame | |
rhohat | Smoothing Estimate of Covariate Transformation | |
envelope.pp3 | Simulation Envelopes of Summary Function for 3D Point Pattern | |
japanesepines | Japanese Pines Point Pattern | |
dirichlet | Dirichlet Tessellation of Point Pattern | |
Jdot | Multitype J Function (i-to-any) | |
ippm | Optimise Irregular Trend Parameters in Point Process Model | |
plot.layered | Layered Plot | |
pairdist | Pairwise distances | |
is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
summary.ppm | Summarizing a Fitted Point Process Model | |
distmap.ppp | Distance Map of Point Pattern | |
bw.scott | Scott's Rule for Bandwidth Selection for Kernel Density | |
thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
rotate.ppp | Rotate a Point Pattern | |
murchison | Murchison gold deposits | |
clip.infline | Intersect Infinite Straight Lines with a Window | |
bounding.box.xy | Convex Hull of Points | |
plot.fasp | Plot a Function Array | |
finpines | Pine saplings in Finland. | |
nncorr | Nearest-Neighbour Correlation Indices of Marked Point Pattern | |
dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
runifpointOnLines | Generate N Uniform Random Points On Line Segments | |
contour.im | Contour plot of pixel image | |
plot.slrm | Plot a Fitted Spatial Logistic Regression | |
is.marked.ppp | Test Whether A Point Pattern is Marked | |
cut.im | Convert Pixel Image from Numeric to Factor | |
tess | Create a Tessellation | |
layered | Create List of Plotting Layers | |
edges2triangles | List Triangles in a Graph | |
blur | Apply Gaussian Blur to a Pixel Image | |
matchingdist | Distance for a Point Pattern Matching | |
fasp.object | Function Arrays for Spatial Patterns | |
clickppp | Interactively Add Points | |
centroid.owin | Centroid of a window | |
fitted.slrm | Fitted Probabilities for Spatial Logistic Regression | |
nztrees | New Zealand Trees Point Pattern | |
crossing.psp | Crossing Points of Two Line Segment Patterns | |
valid.ppm | Check Whether Point Process Model is Valid | |
sharpen | Data Sharpening of Point Pattern | |
sumouter | Compute Quadratic Forms | |
istat | Point and Click Interface for Exploratory Analysis of Point Pattern | |
midpoints.psp | Midpoints of Line Segment Pattern | |
is.im | Test Whether An Object Is A Pixel Image | |
pcf.fv | Pair Correlation Function obtained from K Function | |
pool.fasp | Pool Data from Several Function Arrays | |
plot.tess | Plot a tessellation | |
gridcentres | Rectangular grid of points | |
summary.owin | Summary of a Spatial Window | |
AreaInter | The Area Interaction Point Process Model | |
linearpcf | Linear Pair Correlation Function | |
nnwhich.pp3 | Nearest neighbours in three dimensions | |
ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
miplot | Morishita Index Plot | |
setcov | Set Covariance of a Window | |
K3est | K-function of a Three-Dimensional Point Pattern | |
rthin | Random Thinning | |
integral.im | Integral of a Pixel Image | |
ppm.object | Class of Fitted Point Process Models | |
Hest | Spherical Contact Distribution Function | |
quantile.im | Sample Quantiles of Pixel Image | |
methods.linnet | Methods for Linear Networks | |
pppmatching | Create a Point Matching | |
pairsat.family | Saturated Pairwise Interaction Point Process Family | |
rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
is.convex | Test Whether a Window is Convex | |
lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
lppm | Fit Point Process Model to Point Pattern on Linear Network | |
diameter.owin | Diameter of a Window | |
summary.quad | Summarizing a Quadrature Scheme | |
methods.rhohat | Methods for Intensity Functions of Spatial Covariate | |
simulate.kppm | Simulate a Fitted Cluster Point Process Model | |
scaletointerval | Rescale Data to Lie Between Specified Limits | |
rsyst | Simulate systematic random point pattern | |
rmpoispp | Generate Multitype Poisson Point Pattern | |
kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
quadrat.test.splitppp | Chi-Squared Test of CSR for Split Point Pattern | |
pairdist.lpp | Pairwise shortest-path distances between points on a linear network | |
im.object | Class of Images | |
summary.ppp | Summary of a Point Pattern Dataset | |
pixellate.owin | Convert Window to Pixel Image | |
rStrauss | Perfect Simulation of the Strauss Process | |
reach | Interaction Distance of a Point Process | |
gridweights | Compute Quadrature Weights Based on Grid Counts | |
Kmeasure | Reduced Second Moment Measure | |
rcell | Simulate Baddeley-Silverman Cell Process | |
methods.boxx | Methods for Multi-Dimensional Box | |
distmap.psp | Distance Map of Line Segment Pattern | |
model.matrix.ppm | Extract Design Matrix from Point Process Model | |
methods.lpp | Methods for Point Patterns on a Linear Network | |
incircle | Find Largest Circle Inside Window | |
infline | Infinite Straight Lines | |
nearest.raster.point | Find Pixel Nearest to a Given Point | |
is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
nndist | Nearest neighbour distances | |
plot.msr | Plot a Signed or Vector-Valued Measure | |
plot.kstest | Plot a Spatial Kolmogorov-Smirnov Test | |
suffstat | Sufficient Statistic of Point Process Model | |
Emark | Diagnostics for random marking | |
ppm | Fit Point Process Model to Data | |
plot.linim | Plot Pixel Image on Linear Network | |
Lest | L-function | |
quadratcount | Quadrat counting for a point pattern | |
rVarGamma | Simulate Neyman-Scott Point Process with Variance Gamma cluster kernel | |
Extract.fv | Extract Subset of Function Values | |
stieltjes | Compute Integral of Function Against Cumulative Distribution | |
quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
predict.ppm | Prediction from a Fitted Point Process Model | |
superimpose | Superimpose Several Geometric Patterns | |
MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
MultiHard | The Multitype Hard Core Point Process Model | |
Extract.quad | Subset of Quadrature Scheme | |
Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
project2segment | Move Point To Nearest Line | |
pp3 | Three Dimensional Point Pattern | |
latest.news | Print News About Latest Version of Package | |
rpoislinetess | Poisson Line Tessellation | |
Gest | Nearest Neighbour Distance Function G | |
rDGS | Perfect Simulation of the Diggle-Gates-Stibbard Process | |
shapley | Galaxies in the Shapley Supercluster | |
summary.psp | Summary of a Line Segment Pattern Dataset | |
with.fv | Evaluate an Expression in a Function Table | |
nearestsegment | Find Line Segment Nearest to Each Point | |
rshift | Random Shift | |
nbfires | Point Patterns of New Brunswick Forest Fires | |
rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
which.max.im | Identify Pixelwise Maximum of Several Pixel Images | |
pairdist.psp | Pairwise distances between line segments | |
Replace.im | Reset Values in Subset of Image | |
zapsmall.im | Rounding of Pixel Values | |
letterR | Window in Shape of Letter R | |
vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
localK | Neighbourhood density function | |
model.frame.ppm | Extract the Environment of a Point Process Model | |
unmark | Remove Marks | |
model.depends | Identify Covariates Involved in each Model Term | |
StraussHard | The Strauss / Hard Core Point Process Model | |
quadratresample | Resample a Point Pattern by Resampling Quadrats | |
Gfox | Foxall's Distance Functions | |
rotate.owin | Rotate a Window | |
affine.owin | Apply Affine Transformation To Window | |
pcf3est | Pair Correlation Function of a Three-Dimensional Point Pattern | |
ppx | Multidimensional Space-Time Point Pattern | |
rshift.splitppp | Randomly Shift a List of Point Patterns | |
shift.owin | Apply Vector Translation To Window | |
shift.im | Apply Vector Translation To Pixel Image | |
urkiola | Urkiola Woods Point Pattern | |
smooth.ppp | Spatial smoothing of observations at irregular points | |
clickjoin | Interactively join vertices on a plot | |
tile.areas | Compute Areas of Tiles in a Tessellation | |
whist | Weighted Histogram | |
simplenet | Simple Example of Linear Network | |
rDiggleGratton | Perfect Simulation of the Diggle-Gratton Process | |
as.im | Convert to Pixel Image | |
scanpp | Read Point Pattern From Data File | |
Extract.listof | Extract or Replace Subset of a List of Things | |
lut | Lookup Tables | |
Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
angles.psp | Orientation Angles of Line Segments | |
LennardJones | The Lennard-Jones Potential | |
Extract.ppp | Extract or Replace Subset of Point Pattern | |
perimeter | Perimeter Length of Window | |
is.multitype | Test whether Object is Multitype | |
circumradius | Circumradius and Diameter of a Linear Network | |
spokes | Spokes pattern of dummy points | |
anova.ppm | ANOVA for Fitted Point Process Models | |
vertices | Vertices of a Window | |
vargamma.estpcf | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |
clickpoly | Interactively Define a Polygon | |
raster.x | Cartesian Coordinates for a Pixel Raster | |
with.hyperframe | Evaluate an Expression in Each Row of a Hyperframe | |
heather | Diggle's Heather Data | |
as.data.frame.psp | Coerce Line Segment Pattern to a Data Frame | |
Extract.msr | Extract Subset of Signed or Vector Measure | |
Gmulti | Marked Nearest Neighbour Distance Function | |
Kdot | Multitype K Function (i-to-any) | |
plot.owin | Plot a Spatial Window | |
npoints | Number of Points in a Point Pattern | |
plot.psp | plot a Spatial Line Segment Pattern | |
plot.kppm | Plot a fitted cluster point process | |
rPoissonCluster | Simulate Poisson Cluster Process | |
pcfdot | Multitype pair correlation function (i-to-any) | |
compatible.fasp | Test Whether Function Arrays Are Compatible | |
progressreport | Print Progress Reports | |
reduced.sample | Reduced Sample Estimator using Histogram Data | |
connected | Connected components of an image or window | |
methods.lppm | Methods for Fitted Point Process Models on a Linear Network | |
anemones | Beadlet Anemones Data | |
rescale.owin | Convert Window to Another Unit of Length | |
areaLoss | Difference of Disc Areas | |
as.tess | Convert Data To Tessellation | |
pairdist.ppx | Pairwise Distances in Any Dimensions | |
bei | Tropical rain forest trees | |
lansing | Lansing Woods Point Pattern | |
diameter | Diameter of an Object | |
swedishpines | Swedish Pines Point Pattern | |
scan.test | Spatial Scan Test | |
by.im | Apply Function to Image Broken Down by Factor | |
nndist.ppx | Nearest Neighbour Distances in Any Dimensions | |
smooth.fv | Apply Smoothing to Function Values | |
pcf.ppp | Pair Correlation Function of Point Pattern | |
envelope | Simulation Envelopes of Summary Function | |
plot.bermantest | Plot Result of Berman Test | |
area.owin | Area of a Window | |
betacells | Beta Ganglion Cells in Cat Retina | |
kstest.ppm | Kolmogorov-Smirnov Test for Point Process Model | |
varblock | Estimate Variance of Summary Statistic by Subdivision | |
cauchy.estpcf | Fit the Neyman-Scott cluster process with Cauchy kernel | |
data.ppm | Extract Original Data from a Fitted Point Process Model | |
ewcdf | Weighted Empirical Cumulative Distribution Function | |
chicago | Chicago Street Crime Data | |
iplot | Point and Click Interface for Displaying a Point Pattern | |
hyperframe | Hyper Data Frame | |
shift.ppp | Apply Vector Translation To Point Pattern | |
linnet | Create a Linear Network | |
pool.envelope | Pool Data from Several Envelopes | |
as.owin | Convert Data To Class owin | |
print.ppp | Print Brief Details of a Point Pattern Dataset | |
linearKinhom | Inhomogeneous Linear K Function | |
bdist.pixels | Distance to Boundary of Window | |
nncross | Nearest Neighbours Between Two Patterns | |
quadrat.test | Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
distmap | Distance Map | |
Extract.tess | Extract or Replace Subset of Tessellation | |
lpp | Create Point Pattern on Linear Network | |
as.psp | Convert Data To Class psp | |
Linhom | L-function | |
effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model | |
formula.ppm | Model Formulae for Gibbs Point Process Models | |
Kscaled | Locally Scaled K-function | |
is.empty | Test Whether An Object Is Empty | |
rMaternII | Simulate Matern Model II | |
compatible | Test Whether Objects Are Compatible | |
bronzefilter | Bronze gradient filter data | |
linim | Create Pixel Image on Linear Network | |
solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
idw | Inverse-distance weighted smoothing of observations at irregular points | |
is.marked | Test Whether Marks Are Present | |
longleaf | Longleaf Pines Point Pattern | |
lurking | Lurking variable plot | |
square | Square Window | |
nndist.psp | Nearest neighbour distances between line segments | |
plot.im | Plot a Pixel Image | |
markconnect | Mark Connection Function | |
triplet.family | Triplet Interaction Family | |
plot.fv | Plot Function Values | |
pairdist.ppp | Pairwise distances | |
crossdist.ppp | Pairwise distances between two different point patterns | |
plot.pp3 | Plot a three-dimensional point pattern | |
pcfcross | Multitype pair correlation function (cross-type) | |
dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
diameter.boxx | Geometrical Calculations for Multi-Dimensional Box | |
bind.fv | Combine Function Value Tables | |
qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
periodify | Make Periodic Copies of a Spatial Pattern | |
plot.hyperframe | Plot Entries in a Hyperframe | |
print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
eval.fv | Evaluate Expression Involving Functions | |
cauchy.estK | Fit the Neyman-Scott cluster process with Cauchy kernel | |
identify.psp | Identify Segments in a Line Segment Pattern | |
delaunay | Delaunay Triangulation of Point Pattern | |
demopat | Artificial Data Point Pattern | |
pcfinhom | Inhomogeneous Pair Correlation Function | |
plot.influence.ppm | Plot Influence Measure | |
psp | Create a Line Segment Pattern | |
rMosaicField | Mosaic Random Field | |
plot.listof | Plot a List of Things | |
relrisk | Nonparametric Estimate of Spatially-Varying Relative Risk | |
lgcp.estpcf | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
rescale | Convert dataset to another unit of length | |
ripras | Estimate window from points alone | |
markcorrint | Mark Correlation Integral | |
plot.ppp | plot a Spatial Point Pattern | |
project.ppm | Force Point Process Model to be Valid | |
rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
fryplot | Fry Plot of Point Pattern | |
marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern | |
redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
rescue.rectangle | Convert Window Back To Rectangle | |
rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |
rstrat | Simulate Stratified Random Point Pattern | |
methods.units | Methods for Units | |
rescale.ppp | Convert Point Pattern to Another Unit of Length | |
fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
unnormdensity | Weighted kernel smoother | |
pairdist.default | Pairwise distances | |
lineardisc | Compute Disc of Given Radius in Linear Network | |
inforder.family | Infinite Order Interaction Family | |
nnclean | Nearest Neighbour Clutter Removal | |
rMaternI | Simulate Matern Model I | |
pairwise.family | Pairwise Interaction Process Family | |
linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |
rMosaicSet | Mosaic Random Set | |
rLGCP | Simulate Log-Gaussian Cox Process | |
rmpoint | Generate N Random Multitype Points | |
rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
runifpoint3 | Generate N Uniform Random Points in Three Dimensions | |
rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |
F3est | Empty Space Function of a Three-Dimensional Point Pattern | |
rshift.ppp | Randomly Shift a Point Pattern | |
Extract.im | Extract Subset of Image | |
markcorr | Mark Correlation Function | |
Ord | Generic Ord Interaction model | |
print.ppm | Print a Fitted Point Process Model | |
plot.leverage.ppm | Plot Leverage Function | |
nnwhich | Nearest neighbour | |
pixellate.psp | Convert Line Segment Pattern to Pixel Image | |
psst | Pseudoscore Diagnostic For Fitted Model against General Alternative | |
pcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-Type) | |
profilepl | Profile Maximum Pseudolikelihood | |
rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |
spatstat-package | The Spatstat Package | |
as.mask | Pixel Image Approximation of a Window | |
summary.im | Summarizing a Pixel Image | |
predict.lppm | Predict Point Process Model on Linear Network | |
box3 | Three-Dimensional Box | |
bw.relrisk | Cross Validated Bandwidth Selection for Relative Risk Estimation | |
vargamma.estK | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |
expand.owin | Expand Window By Factor | |
split.ppp | Divide Point Pattern into Sub-patterns | |
default.dummy | Generate a Default Pattern of Dummy Points | |
split.im | Divide Image Into Sub-images | |
dilation | Morphological Dilation | |
rlabel | Random Re-Labelling of Point Pattern | |
deltametric | Delta Metric | |
update.kppm | Update a Fitted Cluster Point Process Model | |
simdat | Simulated Point Pattern | |
fv.object | Function Value Table | |
slrm | Spatial Logistic Regression | |
spatstat.options | Internal Options in Spatstat Package | |
imcov | Spatial Covariance of a Pixel Image | |
update.ppm | Update a Fitted Point Process Model | |
nndist.pp3 | Nearest neighbour distances in three dimensions | |
is.ppp | Test Whether An Object Is A Point Pattern | |
pixellate | Convert Spatial Object to Pixel Image | |
unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
predict.slrm | Predicted or Fitted Values from Spatial Logistic Regression | |
rMatClust | Simulate Matern Cluster Process | |
rescale.im | Convert Pixel Image to Another Unit of Length | |
residuals.ppm | Residuals for Fitted Point Process Model | |
runiflpp | Uniform Random Points on a Linear Network | |
Kcross.inhom | Inhomogeneous Cross K Function | |
tiles | Extract List of Tiles in a Tessellation | |
Ldot | Multitype L-function (i-to-any) | |
intersect.owin | Intersection, Union or Set Subtraction of Two Windows | |
SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model | |
Triplets | The Triplet Point Process Model | |
as.matrix.im | Convert Pixel Image to Matrix or Array | |
bramblecanes | Hutchings' Bramble Canes data | |
crossdist.pp3 | Pairwise distances between two different three-dimensional point patterns | |
chop.tess | Subdivide a Window or Tessellation using a Set of Lines | |
Jest | Estimate the J-function | |
flipxy | Exchange X and Y Coordinates | |
harmonic | Basis for Harmonic Functions | |
distfun | Distance Map as a Function | |
is.stationary | Recognise Stationary and Poisson Point Process Models | |
MultiStrauss | The Multitype Strauss Point Process Model | |
as.box3 | Convert Data to Three-Dimensional Box | |
as.polygonal | Convert a Window to a Polygonal Window | |
compatible.fv | Test Whether Function Objects Are Compatible | |
bw.smoothppp | Cross Validated Bandwidth Selection for Spatial Smoothing | |
leverage.ppm | Leverage Measure for Spatial Point Process Model | |
osteo | Osteocyte Lacunae Data: Replicated Three-Dimensional Point Patterns | |
compatible.im | Test Whether Pixel Images Are Compatible | |
localpcf | Local pair correlation function | |
owin | Create a Window | |
eem | Exponential Energy Marks | |
contour.listof | Plot a List of Things | |
discpartarea | Area of Part of Disc | |
predict.kppm | Prediction from a Fitted Cluster Point Process Model | |
influence.ppm | Influence Measure for Spatial Point Process Model | |
print.owin | Print Brief Details of a Spatial Window | |
gpc2owin | Convert Polygonal Region into Different Format | |
interp.im | Interpolate a Pixel Image | |
rHardcore | Perfect Simulation of the Hardcore Process | |
rlinegrid | Generate grid of parallel lines with random displacement | |
print.quad | Print a Quadrature Scheme | |
rThomas | Simulate Thomas Process | |
nsegments | Number of Line Segments in a Line Segment Pattern | |
persp.im | Perspective Plot of Pixel Image | |
rpoint | Generate N Random Points | |
plot.linnet | Plot a linear network | |
plot.quad | plot a Spatial Quadrature Scheme | |
runifpointx | Generate N Uniform Random Points in Any Dimensions | |
psstG | Pseudoscore Diagnostic For Fitted Model against Saturation Alternative | |
simplify.owin | Approximate a Polygon by a Simpler Polygon | |
rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |
rat | Ratio object | |
rGaussPoisson | Simulate Gauss-Poisson Process | |
rjitter | Random Perturbation of a Point Pattern | |
vcov.kppm | Variance-Covariance Matrix for a Fitted Cluster Point Process Model | |
spatstat-internal | Internal spatstat functions | |
rpoispp | Generate Poisson Point Pattern | |
rshift.psp | Randomly Shift a Line Segment Pattern | |
rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |
simulate.ppm | Simulate a Fitted Gibbs Point Process Model | |
thomas.estpcf | Fit the Thomas Point Process by Minimum Contrast | |
volume | Volume of an Object | |
Kcom | Model Compensator of K Function | |
Ldot.inhom | Inhomogeneous Multitype L Dot Function | |
append.psp | Combine Two Line Segment Patterns | |
cbind.hyperframe | Combine Hyperframes by Rows or by Columns | |
compareFit | Residual Diagnostics for Multiple Fitted Models | |
dfbetas.ppm | Parameter influence measure | |
coef.ppm | Coefficients of Fitted Point Process Model | |
diameter.box3 | Geometrical Calculations for Three-Dimensional Box | |
envelope.envelope | Recompute Envelopes | |
eroded.areas | Areas of Morphological Erosions | |
endpoints.psp | Endpoints of Line Segment Pattern | |
fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |
eval.fasp | Evaluate Expression Involving Function Arrays | |
lengths.psp | Lengths of Line Segments | |
hamster | Aherne's hamster tumour data | |
msr | Signed or Vector-Valued Measure | |
mincontrast | Method of Minimum Contrast | |
pcf | Pair Correlation Function | |
pairdist.pp3 | Pairwise distances in Three Dimensions | |
pixellate.ppp | Convert Point Pattern to Pixel Image | |
psp.object | Class of Line Segment Patterns | |
residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |
summary.listof | Summary of a List of Things | |
Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
Fiksel | The Fiksel Interaction | |
Kcross | Multitype K Function (Cross-type) | |
corners | Corners of a rectangle | |
concatxy | Concatenate x,y Coordinate Vectors | |
closing | Morphological Closing | |
logLik.ppm | Log Likelihood and AIC for Point Process Model | |
marks | Marks of a Point Pattern | |
adaptive.density | Intensity Estimate of Point Pattern Using Tessellation | |
areaGain | Difference of Disc Areas | |
Strauss | The Strauss Point Process Model | |
by.ppp | Apply a Function to a Point Pattern Broken Down by Factor | |
Kres | Residual K Function | |
npfun | Dummy Function Returns Number of Points | |
density.ppp | Kernel Smoothed Intensity of Point Pattern | |
Pairwise | Generic Pairwise Interaction model | |
runifdisc | Generate N Uniform Random Points in a Disc | |
diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
shift | Apply Vector Translation | |
trim.rectangle | Cut margins from rectangle | |
pointsOnLines | Place Points Evenly Along Specified Lines | |
dummify | Convert Data to Numeric Values by Constructing Dummy Variables | |
eval.im | Evaluate Expression Involving Pixel Images | |
bw.stoyan | Stoyan's Rule of Thumb for Bandwidth Selection | |
Saturated | Saturated Pairwise Interaction model | |
pcf.fasp | Pair Correlation Function obtained from array of K functions | |
methods.box3 | Methods for Three-Dimensional Box | |
spruces | Spruces Point Pattern | |
plot.envelope | Plot a Simulation Envelope | |
markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
unitname | Name for Unit of Length | |
redwood | California Redwoods Point Pattern (Ripley's Subset) | |
psstA | Pseudoscore Diagnostic For Fitted Model against Area-Interaction Alternative | |
identify.ppp | Identify Points in a Point Pattern | |
opening | Morphological Opening | |
collapse.fv | Collapse Several Function Tables into One | |
crossdist.psp | Pairwise distances between two different line segment patterns | |
gorillas | Gorilla Nesting Sites | |
rpoisline | Generate Poisson Random Line Process | |
crossdist | Pairwise distances | |
logLik.slrm | Loglikelihood of Spatial Logistic Regression | |
rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
methods.ppx | Methods for Multidimensional Space-Time Point Patterns | |
Lcross | Multitype L-function (cross-type) | |
intersect.tess | Intersection of Two Tessellations | |
quadrats | Divide Region into Quadrats | |
model.images | Compute Images of Constructed Covariates | |
owin.object | Class owin | |
ppp.object | Class of Point Patterns | |
print.im | Print Brief Details of an Image | |
plot.splitppp | Plot a List of Point Patterns | |
rmh.ppm | Simulate from a Fitted Point Process Model | |
duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
rotate | Rotate | |
markvario | Mark Variogram | |
erosion | Morphological Erosion | |
complement.owin | Take Complement of a Window | |
im | Create a Pixel Image Object | |
levelset | Level Set of a Pixel Image | |
pool | Pool Data | |
plot.ppm | plot a Fitted Point Process Model | |
rCauchy | Simulate Neyman-Scott Point Process with Cauchy cluster kernel | |
union.quad | Union of Data and Dummy Points | |
rotate.psp | Rotate a Line Segment Pattern | |
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Details
Date | 2011-12-21 |
License | GPL (>= 2) |
URL | http://www.spatstat.org |
LazyData | true |
LazyLoad | true |
ByteCompile | true |
Packaged | 2011-12-21 04:34:58 UTC; adrian |
Repository | CRAN |
Date/Publication | 2011-12-21 08:53:46 |
depends | base (>= 2.14.0) , deldir (>= 0.0-10) , graphics , mgcv , R (>= 2.14.0) , stats , utils |
suggests | gpclib , maptools , RandomFields (>= 2.0) , rpanel , scatterplot3d , sm , spatial , tkrplot |
Contributors | Rolf Turner, Adrian Baddeley |
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