spatstat v1.25-5
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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 | |
localK | Neighbourhood density function | |
pool | Pool Data | |
logLik.ppm | Log Likelihood and AIC for Point Process Model | |
methods.rhohat | Methods for Intensity Functions of Spatial Covariate | |
pairwise.family | Pairwise Interaction Process Family | |
quadrats | Divide Region into Quadrats | |
rescale.ppp | Convert Point Pattern to Another Unit of Length | |
linearpcf | Linear Pair Correlation Function | |
msr | Signed or Vector-Valued Measure | |
simulate.slrm | Simulate a Fitted Spatial Logistic Regression Model | |
localpcf | Local pair correlation function | |
pixellate | Convert Spatial Object to Pixel Image | |
spokes | Spokes pattern of dummy points | |
plot.splitppp | Plot a List of Point Patterns | |
nnwhich | Nearest neighbour | |
linearKinhom | Inhomogeneous Linear K Function | |
methods.pp3 | Methods for three-dimensional point patterns | |
summary.im | Summarizing a Pixel Image | |
raster.x | Cartesian Coordinates for a Pixel Raster | |
pairdist | Pairwise distances | |
pcf.ppp | Pair Correlation Function of Point Pattern | |
residuals.ppm | Residuals for Fitted Point Process Model | |
nndist.ppx | Nearest Neighbour Distances in Any Dimensions | |
simdat | Simulated Point Pattern | |
localKinhom | Inhomogeneous Neighbourhood Density Function | |
psstA | Pseudoscore Diagnostic For Fitted Model against Area-Interaction Alternative | |
plot.ppp | plot a Spatial Point Pattern | |
quantile.im | Sample Quantiles of Pixel Image | |
rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |
persp.im | Perspective Plot of Pixel Image | |
plot.slrm | Plot a Fitted Spatial Logistic Regression | |
swedishpines | Swedish Pines Point Pattern | |
pp3 | Three Dimensional Point Pattern | |
tess | Create a Tessellation | |
rescale | Convert dataset to another unit of length | |
progressreport | Print Progress Reports | |
quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
markcorr | Mark Correlation Function | |
redwood | California Redwoods Point Pattern (Ripley's Subset) | |
print.ppm | Print a Fitted Point Process Model | |
rMaternII | Simulate Matern Model II | |
unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
rCauchy | Simulate Neyman-Scott Point Process with Cauchy cluster kernel | |
unmark | Remove Marks | |
marks.psp | Marks of a Line Segment Pattern | |
rmpoispp | Generate Multitype Poisson Point Pattern | |
plot.linim | Plot Pixel Image on Linear Network | |
methods.ppx | Methods for Multidimensional Space-Time Point Patterns | |
plot.colourmap | Plot a Colour Map | |
logLik.slrm | Loglikelihood of Spatial Logistic Regression | |
nbfires | Point Patterns of New Brunswick Forest Fires | |
residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
reduced.sample | Reduced Sample Estimator using Histogram Data | |
reach | Interaction Distance of a Point Process | |
rstrat | Simulate Stratified Random Point Pattern | |
scan.test | Spatial Scan Test | |
mincontrast | Method of Minimum Contrast | |
methods.boxx | Methods for Multi-Dimensional Box | |
rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
npfun | Dummy Function Returns Number of Points | |
plot.kstest | Plot a Spatial Kolmogorov-Smirnov Test | |
rpoislpp | Poisson Point Process on a Linear Network | |
pcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-Type) | |
selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
matchingdist | Distance for a Point Pattern Matching | |
rthin | Random Thinning | |
split.ppp | Divide Point Pattern into Sub-patterns | |
shift.psp | Apply Vector Translation To Line Segment Pattern | |
methods.lppm | Methods for Fitted Point Process Models on a Linear Network | |
mean.im | Maximum, Minimum, Mean, Median, Range or Sum of Pixel Values in an Image | |
shift | Apply Vector Translation | |
plot.owin | Plot a Spatial Window | |
unnormdensity | Weighted kernel smoother | |
methods.lpp | Methods for Point Patterns on a Linear Network | |
predict.slrm | Predicted or Fitted Values from Spatial Logistic Regression | |
multiplicity.ppp | Count Multiplicity of Duplicate Points | |
shift.im | Apply Vector Translation To Pixel Image | |
pointsOnLines | Place Points Evenly Along Specified Lines | |
periodify | Make Periodic Copies of a Spatial Pattern | |
lpp | Create Point Pattern on Linear Network | |
pairdist.psp | Pairwise distances between line segments | |
rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |
plot.pp3 | Plot a three-dimensional point pattern | |
rescale.im | Convert Pixel Image to Another Unit of Length | |
Lcross.inhom | Inhomogeneous Cross Type L Function | |
simplenet | Simple Example of Linear Network | |
print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
setcov | Set Covariance of a Window | |
markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
vertices | Vertices of a Window | |
psp | Create a Line Segment Pattern | |
plot.msr | Plot a Signed or Vector-Valued Measure | |
which.max.im | Identify Pixelwise Maximum of Several Pixel Images | |
Jmulti | Marked J Function | |
pool.rat | Pool Data from Several Ratio Objects | |
lurking | Lurking variable plot | |
runifpointOnLines | Generate N Uniform Random Points On Line Segments | |
ppm | Fit Point Process Model to Data | |
print.owin | Print Brief Details of a Spatial Window | |
project2segment | Move Point To Nearest Line | |
quadrat.test | Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
profilepl | Profile Maximum Pseudolikelihood | |
methods.linnet | Methods for Linear Networks | |
rotate.owin | Rotate a Window | |
as.psp | Convert Data To Class psp | |
Kinhom | Inhomogeneous K-function | |
pairdist.lpp | Pairwise shortest-path distances between points on a linear network | |
print.ppp | Print Brief Details of a Point Pattern Dataset | |
quadratcount | Quadrat counting for a point pattern | |
applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
Lest | L-function | |
quad.object | Class of Quadrature Schemes | |
marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern | |
rHardcore | Perfect Simulation of the Hardcore Process | |
nncorr | Nearest-Neighbour Correlation Indices of Marked Point Pattern | |
print.im | Print Brief Details of an Image | |
rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |
slrm | Spatial Logistic Regression | |
plot.kppm | Plot a fitted cluster point process | |
simplify.owin | Approximate a Polygon by a Simpler Polygon | |
spatstat-internal | Internal spatstat functions | |
print.quad | Print a Quadrature Scheme | |
Kest.fft | K-function using FFT | |
square | Square Window | |
ppm.object | Class of Fitted Point Process Models | |
quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
rMaternI | Simulate Matern Model I | |
suffstat | Sufficient Statistic of Point Process Model | |
area.owin | Area of a Window | |
summary.ppm | Summarizing a Fitted Point Process Model | |
rStraussHard | Perfect Simulation of the Strauss-Hardcore Process | |
tile.areas | Compute Areas of Tiles in a Tessellation | |
spruces | Spruces Point Pattern | |
areaLoss | Difference of Disc Areas | |
rescale.owin | Convert Window to Another Unit of Length | |
pairs.im | Scatterplot Matrix for Pixel Images | |
pairdist.ppx | Pairwise Distances in Any Dimensions | |
matclust.estpcf | Fit the Matern Cluster Point Process by Minimum Contrast Using Pair Correlation | |
nnwhich.pp3 | Nearest neighbours in three dimensions | |
rhohat | Smoothing Estimate of Covariate Transformation | |
pcfcross | Multitype pair correlation function (cross-type) | |
ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
plot.fasp | Plot a Function Array | |
rNeymanScott | Simulate Neyman-Scott Process | |
rGaussPoisson | Simulate Gauss-Poisson Process | |
summary.ppp | Summary of a Point Pattern Dataset | |
rknn | Theoretical Distribution of Nearest Neighbour Distance | |
identify.ppp | Identify Points in a Point Pattern | |
plot.fv | Plot Function Values | |
Replace.im | Reset Values in Subset of Image | |
rThomas | Simulate Thomas Process | |
im | Create a Pixel Image Object | |
rPoissonCluster | Simulate Poisson Cluster Process | |
plot.tess | Plot a tessellation | |
pixellate.psp | Convert Line Segment Pattern to Pixel Image | |
coef.ppm | Coefficients of Fitted Point Process Model | |
rgbim | Create Colour-Valued Pixel Image | |
rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
as.interact | Extract Interaction Structure | |
smooth.fv | Apply Smoothing to Function Values | |
matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
rotate.ppp | Rotate a Point Pattern | |
plot.influence.ppm | Plot Influence Measure | |
markcorrint | Mark Correlation Integral | |
cells | Biological Cells Point Pattern | |
lppm | Fit Point Process Model to Point Pattern on Linear Network | |
rshift.ppp | Randomly Shift a Point Pattern | |
clickjoin | Interactively join vertices on a plot | |
rsyst | Simulate systematic random point pattern | |
murchison | Murchison gold deposits | |
fv.object | Function Value Table | |
runiflpp | Uniform Random Points on a Linear Network | |
predict.kppm | Prediction from a Fitted Cluster Point Process Model | |
ppp | Create a Point Pattern | |
smooth.ppp | Spatial smoothing of observations at irregular points | |
nndist.psp | Nearest neighbour distances between line segments | |
shapley | Galaxies in the Shapley Supercluster | |
whist | Weighted Histogram | |
vargamma.estpcf | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |
summary.listof | Summary of a List of Things | |
rStrauss | Perfect Simulation of the Strauss Process | |
vcov.kppm | Variance-Covariance Matrix for a Fitted Cluster Point Process Model | |
superimpose | Superimpose Several Geometric Patterns | |
hamster | Aherne's hamster tumour data | |
is.owin | Test Whether An Object Is A Window | |
concatxy | Concatenate x,y Coordinate Vectors | |
rpoint | Generate N Random Points | |
zapsmall.im | Rounding of Pixel Values | |
lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
shift.ppp | Apply Vector Translation To Point Pattern | |
erosion | Morphological Erosion | |
chop.tess | Subdivide a Window or Tessellation using a Set of Lines | |
eval.im | Evaluate Expression Involving Pixel Images | |
simulate.kppm | Simulate a Fitted Cluster Point Process Model | |
hyperframe | Hyper Data Frame | |
envelope | Simulation Envelopes of Summary Function | |
Tstat | Third order summary statistic | |
areaGain | Difference of Disc Areas | |
by.ppp | Apply a Function to a Point Pattern Broken Down by Factor | |
nztrees | New Zealand Trees Point Pattern | |
opening | Morphological Opening | |
pairsat.family | Saturated Pairwise Interaction Point Process Family | |
anemones | Beadlet Anemones Data | |
plot.envelope | Plot a Simulation Envelope | |
pixelquad | Quadrature Scheme Based on Pixel Grid | |
Kcross.inhom | Inhomogeneous Cross K Function | |
anova.lppm | ANOVA for Fitted Point Process Models on Linear Network | |
default.dummy | Generate a Default Pattern of Dummy Points | |
commonGrid | Determine A Common Spatial Domain And Pixel Resolution | |
fv | Create a Function Value Table | |
linim | Create Pixel Image on Linear Network | |
crossdist.ppp | Pairwise distances between two different point patterns | |
urkiola | Urkiola Woods Point Pattern | |
Jcross | Multitype J Function (i-to-j) | |
Kcom | Model Compensator of K Function | |
chorley | Chorley-Ribble Cancer Data | |
model.frame.ppm | Extract the Environment of a Point Process Model | |
miplot | Morishita Index Plot | |
density.ppp | Kernel Smoothed Intensity of Point Pattern | |
crossing.psp | Crossing Points of Two Line Segment Patterns | |
Gest | Nearest Neighbour Distance Function G | |
model.matrix.ppm | Extract Design Matrix from Point Process Model | |
Kdot | Multitype K Function (i-to-any) | |
circumradius | Circumradius and Diameter of a Linear Network | |
disc | Circular Window | |
kppm | Fit Cluster or Cox Point Process Model | |
plot.ppm | plot a Fitted Point Process Model | |
Hardcore | The Hard Core Point Process Model | |
as.owin | Convert Data To Class owin | |
project.ppm | Force Point Process Model to be Valid | |
diameter | Diameter of an Object | |
K3est | K-function of a Three-Dimensional Point Pattern | |
interp.im | Interpolate a Pixel Image | |
qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
delaunay | Delaunay Triangulation of Point Pattern | |
predict.ppm | Prediction from a Fitted Point Process Model | |
compareFit | Residual Diagnostics for Multiple Fitted Models | |
rat | Ratio object | |
methods.kppm | Methods for Cluster Point Process Models | |
dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
owin.object | Class owin | |
cut.im | Convert Pixel Image from Numeric to Factor | |
rmpoint | Generate N Random Multitype Points | |
gpc2owin | Convert Polygonal Region into Different Format | |
cauchy.estpcf | Fit the Neyman-Scott cluster process with Cauchy kernel | |
Lcross | Multitype L-function (cross-type) | |
fryplot | Fry Plot of Point Pattern | |
Linhom | L-function | |
imcov | Spatial Covariance of a Pixel Image | |
dummify | Convert Data to Numeric Values by Constructing Dummy Variables | |
distfun | Distance Map as a Function | |
centroid.owin | Centroid of a window | |
finpines | Pine saplings in Finland. | |
pairdist.default | Pairwise distances | |
identify.psp | Identify Segments in a Line Segment Pattern | |
dilation | Morphological Dilation | |
Kscaled | Locally Scaled K-function | |
perimeter | Perimeter Length of Window | |
anova.slrm | Analysis of Deviance for Spatial Logistic Regression Models | |
pcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Type-i-To-Any-Type) | |
as.box3 | Convert Data to Three-Dimensional Box | |
rjitter | Random Perturbation of a Point Pattern | |
cbind.hyperframe | Combine Hyperframes by Rows or by Columns | |
expand.owin | Expand Window By Factor | |
eval.fv | Evaluate Expression Involving Functions | |
anova.ppm | ANOVA for Fitted Point Process Models | |
lgcp.estpcf | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
MultiStrauss | The Multitype Strauss Point Process Model | |
diameter.owin | Diameter of a Window | |
as.tess | Convert Data To Tessellation | |
eem | Exponential Energy Marks | |
runifpoint3 | Generate N Uniform Random Points in Three Dimensions | |
Poisson | Poisson Point Process Model | |
data.ppm | Extract Original Data from a Fitted Point Process Model | |
methods.slrm | Methods for Spatial Logistic Regression Models | |
letterR | Window in Shape of Letter R | |
bw.diggle | Cross Validated Bandwidth Selection for Kernel Density | |
Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
is.im | Test Whether An Object Is A Pixel Image | |
compatible.fasp | Test Whether Function Arrays Are Compatible | |
valid.ppm | Check Whether Point Process Model is Valid | |
as.mask | Pixel Image Approximation of a Window | |
Kmulti | Marked K-Function | |
plot.bermantest | Plot Result of Berman Test | |
Jest | Estimate the J-function | |
as.hyperframe.ppx | Extract coordinates and marks of multidimensional point pattern | |
bdist.points | Distance to Boundary of Window | |
idw | Inverse-distance weighted smoothing of observations at irregular points | |
clip.infline | Intersect Infinite Straight Lines with a Window | |
Saturated | Saturated Pairwise Interaction model | |
effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model | |
as.data.frame.hyperframe | Coerce Hyperframe to Data Frame | |
coef.slrm | Coefficients of Fitted Spatial Logistic Regression Model | |
nearest.raster.point | Find Pixel Nearest to a Given Point | |
Kcross | Multitype K Function (Cross-type) | |
compatible.im | Test Whether Pixel Images Are Compatible | |
pppmatching | Create a Point Matching | |
discretise | Safely Convert Point Pattern Window to Binary Mask | |
Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
methods.units | Methods for Units | |
midpoints.psp | Midpoints of Line Segment Pattern | |
istat | Point and Click Interface for Exploratory Analysis of Point Pattern | |
MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
pixellate.owin | Convert Window to Pixel Image | |
psstG | Pseudoscore Diagnostic For Fitted Model against Saturation Alternative | |
angles.psp | Orientation Angles of Line Segments | |
is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
Gres | Residual G Function | |
plot.psp | plot a Spatial Line Segment Pattern | |
quadrat.test.splitppp | Chi-Squared Test of CSR for Split Point Pattern | |
adaptive.density | Intensity Estimate of Point Pattern Using Tessellation | |
rshift | Random Shift | |
predict.lppm | Predict Point Process Model on Linear Network | |
rLGCP | Simulate Log-Gaussian Cox Process | |
bermantest | Berman's Tests for Point Process Model | |
rMosaicSet | Mosaic Random Set | |
linearK | Linear K Function | |
Triplets | The Triplet Point Process Model | |
affine.owin | Apply Affine Transformation To Window | |
crossdist.psp | Pairwise distances between two different line segment patterns | |
rDiggleGratton | Perfect Simulation of the Diggle-Gratton Process | |
as.function.fv | Convert Function Value Table to Function | |
G3est | Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern | |
pairdist.pp3 | Pairwise distances in Three Dimensions | |
as.data.frame.im | Convert Pixel Image to Data Frame | |
as.polygonal | Convert a Window to a Polygonal Window | |
rescue.rectangle | Convert Window Back To Rectangle | |
diameter.box3 | Geometrical Calculations for Three-Dimensional Box | |
is.convex | Test Whether a Window is Convex | |
fasp.object | Function Arrays for Spatial Patterns | |
amacrine | Hughes' Amacrine Cell Data | |
Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
pcf.fv | Pair Correlation Function obtained from K Function | |
pixellate.ppp | Convert Point Pattern to Pixel Image | |
box3 | Three-Dimensional Box | |
clarkevans | Clark and Evans Aggregation Index | |
bdist.tiles | Distance to Boundary of Window | |
Ord | Generic Ord Interaction model | |
is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
japanesepines | Japanese Pines Point Pattern | |
default.expand | Compute Expansion Window for Simulation | |
lansing | Lansing Woods Point Pattern | |
rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
clickppp | Interactively Add Points | |
rmh.ppm | Simulate from a Fitted Point Process Model | |
methods.box3 | Methods for Three-Dimensional Box | |
linnet | Create a Linear Network | |
rotate | Rotate | |
deltametric | Delta Metric | |
crossdist.ppx | Pairwise Distances Between Two Different Multi-Dimensional Point Patterns | |
closing | Morphological Closing | |
collapse.fv | Collapse Several Function Tables into One | |
rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |
update.kppm | Update a Fitted Cluster Point Process Model | |
affine.ppp | Apply Affine Transformation To Point Pattern | |
as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |
infline | Infinite Straight Lines | |
crossdist | Pairwise distances | |
dirichlet | Dirichlet Tessellation of Point Pattern | |
connected | Connected components of an image or window | |
colourmap | Colour Lookup Tables | |
envelope.envelope | Recompute Envelopes | |
split.im | Divide Image Into Sub-images | |
plot.hyperframe | Plot Entries in a Hyperframe | |
diameter.boxx | Geometrical Calculations for Multi-Dimensional Box | |
density.psp | Kernel Smoothing of Line Segment Pattern | |
influence.ppm | Influence Measure for Spatial Point Process Model | |
dilated.areas | Areas of Morphological Dilations | |
Extract.splitppp | Extract or Replace Sub-Patterns | |
rpoisline | Generate Poisson Random Line Process | |
spatstat-deprecated | Deprecated spatstat functions | |
marks | Marks of a Point Pattern | |
blur | Apply Gaussian Blur to a Pixel Image | |
intersect.owin | Intersection, Union or Set Subtraction of Two Windows | |
rotate.psp | Rotate a Line Segment Pattern | |
bdist.pixels | Distance to Boundary of Window | |
clarkevans.test | Clark and Evans Test | |
update.ppm | Update a Fitted Point Process Model | |
is.multitype | Test whether Object is Multitype | |
Extract.fasp | Extract Subset of Function Array | |
is.ppp | Test Whether An Object Is A Point Pattern | |
Gfox | Foxall's Distance Functions | |
volume | Volume of an Object | |
Hest | Spherical Contact Distribution Function | |
distmap.ppp | Distance Map of Point Pattern | |
Fest | Estimate the empty space function F | |
compatible | Test Whether Objects Are Compatible | |
Extract.msr | Extract Subset of Signed or Vector Measure | |
rshift.splitppp | Randomly Shift a List of Point Patterns | |
default.rmhcontrol | Set Default Control Parameters for Metropolis-Hastings Algorithm. | |
owin | Create a Window | |
duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
convexhull.xy | Convex Hull of Points | |
bw.relrisk | Cross Validated Bandwidth Selection for Relative Risk Estimation | |
contour.im | Contour plot of pixel image | |
levelset | Level Set of a Pixel Image | |
Emark | Diagnostics for random marking | |
runifpoint | Generate N Uniform Random Points | |
sharpen | Data Sharpening of Point Pattern | |
as.mask.psp | Convert Line Segment Pattern to Binary Pixel Mask | |
demopat | Artificial Data Point Pattern | |
relrisk | Nonparametric Estimate of Spatially-Varying Relative Risk | |
dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
simulate.ppm | Simulate a Fitted Gibbs Point Process Model | |
Extract.im | Extract Subset of Image | |
summary.quad | Summarizing a Quadrature Scheme | |
chicago | Chicago Street Crime Data | |
runifdisc | Generate N Uniform Random Points in a Disc | |
heather | Diggle's Heather Data | |
markvario | Mark Variogram | |
dfbetas.ppm | Parameter influence measure | |
kstest.ppm | Kolmogorov-Smirnov Test for Point Process Model | |
summary.splitppp | Summary of a Split Point Pattern | |
osteo | Osteocyte Lacunae Data: Replicated Three-Dimensional Point Patterns | |
rpoislinetess | Poisson Line Tessellation | |
km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
lut | Lookup Tables | |
methods.rho2hat | Methods for Intensity Functions of Two Spatial Covariates | |
rMatClust | Simulate Matern Cluster Process | |
plot.linnet | Plot a linear network | |
thomas.estpcf | Fit the Thomas Point Process by Minimum Contrast | |
Extract.psp | Extract Subset of Line Segment Pattern | |
is.marked | Test Whether Marks Are Present | |
Extract.ppp | Extract or Replace Subset of Point Pattern | |
plot.leverage.ppm | Plot Leverage Function | |
Geyer | Geyer's Saturation Point Process Model | |
bei | Tropical rain forest trees | |
pool.fasp | Pool Data from Several Function Arrays | |
ppp.object | Class of Point Patterns | |
Ldot | Multitype L-function (i-to-any) | |
is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
as.matrix.owin | Convert Pixel Image to Matrix | |
pcfdot | Multitype pair correlation function (i-to-any) | |
Softcore | The Soft Core Point Process Model | |
diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
psp.object | Class of Line Segment Patterns | |
rSSI | Simulate Simple Sequential Inhibition | |
rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
AreaInter | The Area Interaction Point Process Model | |
F3est | Empty Space Function of a Three-Dimensional Point Pattern | |
with.fv | Evaluate an Expression in a Function Table | |
colourtools | Convert and Compare Colours in Different Formats | |
crossdist.default | Pairwise distances between two different sets of points | |
is.marked.ppm | Test Whether A Point Process Model is Marked | |
alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern | |
Kest | K-function | |
boxx | Multi-Dimensional Box | |
convexhull | Convex Hull | |
contour.listof | Plot a List of Things | |
formula.ppm | Model Formulae for Gibbs Point Process Models | |
cut.ppp | Classify Points in a Point Pattern | |
integral.im | Integral of a Pixel Image | |
envelope.lpp | Envelope for Point Patterns on Linear Network | |
gorillas | Gorilla Nesting Sites | |
gridcentres | Rectangular grid of points | |
ewcdf | Weighted Empirical Cumulative Distribution Function | |
affine.psp | Apply Affine Transformation To Line Segment Pattern | |
as.data.frame.psp | Coerce Line Segment Pattern to a Data Frame | |
LennardJones | The Lennard-Jones Potential | |
incircle | Find Largest Circle Inside Window | |
ants | Harkness-Isham ants' nests data | |
StraussHard | The Strauss / Hard Core Point Process Model | |
rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |
PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
bounding.box.xy | Convex Hull of Points | |
redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
Kmodel | K function of a model | |
clickpoly | Interactively Define a Polygon | |
varblock | Estimate Variance of Summary Statistic by Subdivision | |
bind.fv | Combine Function Value Tables | |
linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |
eval.fasp | Evaluate Expression Involving Function Arrays | |
npoints | Number of Points in a Point Pattern | |
fitted.slrm | Fitted Probabilities for Spatial Logistic Regression | |
eroded.areas | Areas of Morphological Erosions | |
is.marked.ppp | Test Whether A Point Pattern is Marked | |
plot.quad | plot a Spatial Quadrature Scheme | |
rMosaicField | Mosaic Random Field | |
bramblecanes | Hutchings' Bramble Canes data | |
humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
bounding.box | Bounding Box of a Window or Point Pattern | |
border | Border Region of a Window | |
bronzefilter | Bronze gradient filter data | |
complement.owin | Take Complement of a Window | |
kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
rlinegrid | Generate grid of parallel lines with random displacement | |
ippm | Optimise Irregular Trend Parameters in Point Process Model | |
rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |
hist.im | Histogram of Pixel Values in an Image | |
runifpointx | Generate N Uniform Random Points in Any Dimensions | |
leverage.ppm | Leverage Measure for Spatial Point Process Model | |
thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
unitname | Name for Unit of Length | |
latest.news | Print News About Latest Version of Package | |
Strauss | The Strauss Point Process Model | |
methods.distfun | Methods for Distance Functions | |
Gmulti | Marked Nearest Neighbour Distance Function | |
nnclean | Nearest Neighbour Clutter Removal | |
Extract.quad | Subset of Quadrature Scheme | |
plot.layered | Layered Plot | |
BadGey | Hybrid Geyer Point Process Model | |
DiggleGatesStibbard | Diggle-Gates-Stibbard Point Process Model | |
as.hyperframe | Convert Data to Hyperframe | |
Iest | Estimate the I-function | |
corners | Corners of a rectangle | |
Kres | Residual K Function | |
psst | Pseudoscore Diagnostic For Fitted Model against General Alternative | |
harmonise.im | Make Pixel Images Compatible | |
intersect.tess | Intersection of Two Tessellations | |
is.stationary | Recognise Stationary and Poisson Point Process Models | |
inside.owin | Test Whether Points Are Inside A Window | |
im.object | Class of Images | |
layered | Create List of Plotting Layers | |
OrdThresh | Ord's Interaction model | |
longleaf | Longleaf Pines Point Pattern | |
plot.listof | Plot a List of Things | |
nndist | Nearest neighbour distances | |
ord.family | Ord Interaction Process Family | |
ppx | Multidimensional Space-Time Point Pattern | |
rho2hat | Smoothed Relative Density of Pairs of Covariate Values | |
ripras | Estimate window from points alone | |
rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |
rshift.psp | Randomly Shift a Line Segment Pattern | |
spatstat-package | The Spatstat Package | |
pcf | Pair Correlation Function | |
tiles | Extract List of Tiles in a Tessellation | |
sumouter | Compute Quadratic Forms | |
stieltjes | Compute Integral of Function Against Cumulative Distribution | |
with.hyperframe | Evaluate an Expression in Each Row of a Hyperframe | |
Extract.fv | Extract Subset of Function Values | |
DiggleGratton | Diggle-Gratton model | |
allstats | Calculate four standard summary functions of a point pattern. | |
MultiHard | The Multitype Hard Core Point Process Model | |
coords | Extract or Change Coordinates of a Spatial or Spatiotemporal Point Pattern | |
envelope.pp3 | Simulation Envelopes of Summary Function for 3D Point Pattern | |
flipxy | Exchange X and Y Coordinates | |
copper | Berman-Huntington points and lines data | |
gridweights | Compute Quadrature Weights Based on Grid Counts | |
cauchy.estK | Fit the Neyman-Scott cluster process with Cauchy kernel | |
betacells | Beta Ganglion Cells in Cat Retina | |
crossdist.pp3 | Pairwise distances between two different three-dimensional point patterns | |
is.empty | Test Whether An Object Is Empty | |
flu | Influenza Virus Proteins | |
pcf.fasp | Pair Correlation Function obtained from array of K functions | |
pcfinhom | Inhomogeneous Pair Correlation Function | |
bw.scott | Scott's Rule for Bandwidth Selection for Kernel Density | |
lineardisc | Compute Disc of Given Radius in Linear Network | |
nndist.pp3 | Nearest neighbour distances in three dimensions | |
model.depends | Identify Covariates Involved in each Model Term | |
plot.im | Plot a Pixel Image | |
ponderosa | Ponderosa Pine Tree Point Pattern | |
rcell | Simulate Baddeley-Silverman Cell Process | |
rpoispp | Generate Poisson Point Pattern | |
scaletointerval | Rescale Data to Lie Between Specified Limits | |
vargamma.estK | Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel | |
summary.psp | Summary of a Line Segment Pattern Dataset | |
as.im | Convert to Pixel Image | |
distmap | Distance Map | |
discpartarea | Area of Part of Disc | |
bw.stoyan | Stoyan's Rule of Thumb for Bandwidth Selection | |
lengths.psp | Lengths of Line Segments | |
inforder.family | Infinite Order Interaction Family | |
density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
as.rectangle | Window Frame | |
distmap.psp | Distance Map of Line Segment Pattern | |
Fiksel | The Fiksel Interaction | |
bw.smoothppp | Cross Validated Bandwidth Selection for Spatial Smoothing | |
compatible.fv | Test Whether Function Objects Are Compatible | |
Gcom | Model Compensator of Nearest Neighbour Function | |
rVarGamma | Simulate Neyman-Scott Point Process with Variance Gamma cluster kernel | |
Extract.tess | Extract or Replace Subset of Tessellation | |
triplet.family | Triplet Interaction Family | |
Kmeasure | Reduced Second Moment Measure | |
Ldot.inhom | Inhomogeneous Multitype L Dot Function | |
nsegments | Number of Line Segments in a Line Segment Pattern | |
edges2triangles | List Triangles in a Graph | |
as.ppp | Convert Data To Class ppp | |
Extract.listof | Extract or Replace Subset of a List of Things | |
Jdot | Multitype J Function (i-to-any) | |
distmap.owin | Distance Map of Window | |
rDGS | Perfect Simulation of the Diggle-Gates-Stibbard Process | |
model.images | Compute Images of Constructed Covariates | |
affine | Apply Affine Transformation | |
nearestsegment | Find Line Segment Nearest to Each Point | |
shift.owin | Apply Vector Translation To Window | |
smooth.msr | Smooth a Signed or Vector-Valued Measure | |
union.quad | Union of Data and Dummy Points | |
spatstat.options | Internal Options in Spatstat Package | |
markconnect | Mark Connection Function | |
Pairwise | Generic Pairwise Interaction model | |
pppmatching.object | Class of Point Matchings | |
vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model | |
append.psp | Combine Two Line Segment Patterns | |
as.matrix.im | Convert Pixel Image to Matrix or Array | |
by.im | Apply Function to Image Broken Down by Factor | |
endpoints.psp | Endpoints of Line Segment Pattern | |
fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |
fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
harmonic | Basis for Harmonic Functions | |
iplot | Point and Click Interface for Displaying a Point Pattern | |
is.subset.owin | Determine Whether One Window is Contained In Another | |
nncross | Nearest Neighbours Between Two Patterns | |
pairdist.ppp | Pairwise distances | |
pcf3est | Pair Correlation Function of a Three-Dimensional Point Pattern | |
plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
pool.envelope | Pool Data from Several Envelopes | |
pppdist | Distance Between Two Point Patterns | |
quadratresample | Resample a Point Pattern by Resampling Quadrats | |
rlabel | Random Re-Labelling of Point Pattern | |
scanpp | Read Point Pattern From Data File | |
solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
trim.rectangle | Cut margins from rectangle | |
summary.owin | Summary of a Spatial Window | |
nnwhich.ppx | Nearest Neighbours in Any Dimensions | |
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Details
Date | 2012-03-14 |
License | GPL (>= 2) |
URL | http://www.spatstat.org |
LazyData | true |
LazyLoad | true |
ByteCompile | true |
Packaged | 2012-03-14 05:31:42 UTC; adrian |
Repository | CRAN |
Date/Publication | 2012-03-14 07:09:51 |
depends | base (>= 2.14.0) , deldir (>= 0.0-10) , graphics , mgcv , R (>= 2.14.0) , stats , utils |
suggests | gpclib , locfit , maptools , RandomFields (>= 2.0) , rpanel , scatterplot3d , sm , spatial , tkrplot |
Contributors | Rolf Turner, Adrian Baddeley |
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