spatstat v1.23-3
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. 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 | |
Extract.splitppp | Extract or Replace Sub-Patterns | |
Kmodel | K function of a model | |
Pairwise | Generic Pairwise Interaction model | |
Lest | L-function | |
allstats | Calculate four standard summary functions of a point pattern. | |
Emark | Diagnostics for random marking | |
Fiksel | The Fiksel Interaction | |
Lcross | Multitype L-function (cross-type) | |
Kest | K-function | |
as.rectangle | Window Frame | |
as.polygonal | Convert a Window to a Polygonal Window | |
convexhull.xy | Convex Hull of Points | |
centroid.owin | Centroid of a window | |
colourmap | Colour Lookup Tables | |
Kinhom | Inhomogeneous K-function | |
OrdThresh | Ord's Interaction model | |
is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
Linhom | L-function | |
anova.slrm | Analysis of Deviance for Spatial Logistic Regression Models | |
crossdist.pp3 | Pairwise distances between two different three-dimensional point patterns | |
methods.distfun | Methods for Distance Functions | |
Extract.im | Extract Subset of Image | |
fv.object | Function Value Table | |
bounding.box | Bounding Box of a Window or Point Pattern | |
Kcross | Multitype K Function (Cross-type) | |
SatPiece | Piecewise Constant Saturated Pairwise Interaction Point Process Model | |
as.function.fv | Convert Function Value Table to Function | |
identify.psp | Identify Segments in a Line Segment Pattern | |
cut.im | Convert Pixel Image from Numeric to Factor | |
clarkevans | Clark and Evans Aggregation Index | |
demopat | Artificial Data Point Pattern | |
methods.boxx | Methods for Multi-Dimensional Box | |
anova.ppm | ANOVA for Fitted Point Process Models | |
convexhull | Convex Hull | |
as.mask.psp | Convert Line Segment Pattern to Binary Pixel Mask | |
Extract.psp | Extract Subset of Line Segment Pattern | |
Iest | Estimate the I-function | |
methods.lppm | Methods for Fitted Point Process Models on a Linear Network | |
cut.ppp | Classify Points in a Point Pattern | |
Fest | Estimate the empty space function F | |
Kcom | Model Compensator of K Function | |
as.data.frame.psp | Coerce Line Segment Pattern to a Data Frame | |
discretise | Safely Convert Point Pattern Window to Binary Mask | |
distmap.psp | Distance Map of Line Segment Pattern | |
Lcross.inhom | Inhomogeneous Cross Type L Function | |
Kdot | Multitype K Function (i-to-any) | |
nnwhich.pp3 | Nearest neighbours in three dimensions | |
owin.object | Class owin | |
duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
flu | Influenza Virus Proteins | |
nncross | Nearest Neighbours Between Two Patterns | |
midpoints.psp | Midpoints of Line Segment Pattern | |
harmonic | Basis for Harmonic Functions | |
multiplicity.ppp | Count Multiplicity of Duplicate Points | |
bind.fv | Combine Function Value Tables | |
Kscaled | Locally Scaled K-function | |
Kmeasure | Reduced Second Moment Measure | |
crossdist.ppp | Pairwise distances between two different point patterns | |
bei | Tropical rain forest trees | |
pairs.im | Scatterplot Matrix for Pixel Images | |
Extract.fasp | Extract Subset of Function Array | |
gridcentres | Rectangular grid of points | |
envelope | Simulation Envelopes of Summary Function | |
Replace.im | Reset Values in Subset of Image | |
chicago | Chicago Street Crime Data | |
clip.infline | Intersect Infinite Straight Lines with a Window | |
by.im | Apply Function to Image Broken Down by Factor | |
Gcom | Model Compensator of Nearest Neighbour Function | |
LennardJones | The Lennard-Jones Potential | |
MultiStrauss | The Multitype Strauss Point Process Model | |
envelope.lpp | Envelope for Point Patterns on Linear Network | |
plot.linnet | Plot a linear network | |
chorley | Chorley-Ribble Cancer Data | |
is.marked.ppp | Test Whether A Point Pattern is Marked | |
crossing.psp | Crossing Points of Two Line Segment Patterns | |
Gfox | Foxall's Distance Functions | |
BadGey | Hybrid Geyer Point Process Model | |
Ldot.inhom | Inhomogeneous Multitype L Dot Function | |
AreaInter | The Area Interaction Point Process Model | |
anemones | Beadlet Anemones Data | |
ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
linim | Create Pixel Image on Linear Network | |
heather | Diggle's Heather Data | |
Jdot | Multitype J Function (i-to-any) | |
anova.lppm | ANOVA for Fitted Point Process Models on Linear Network | |
colourtools | Convert and Compare Colours in Different Formats | |
Kres | Residual K Function | |
plot.psp | plot a Spatial Line Segment Pattern | |
Kest.fft | K-function using FFT | |
kstest.ppm | Kolmogorov-Smirnov Test for Point Process Model | |
area.owin | Area of a Window | |
markconnect | Mark Connection Function | |
Gest | Nearest Neighbour Distance Function G | |
angles.psp | Orientation Angles of Line Segments | |
bdist.tiles | Distance to Boundary of Window | |
dilated.areas | Areas of Morphological Dilations | |
is.subset.owin | Determine Whether One Window is Contained In Another | |
ponderosa | Ponderosa Pine Tree Point Pattern | |
as.box3 | Convert Data to Three-Dimensional Box | |
Jest | Estimate the J-function | |
dirichlet | Dirichlet Tessellation of Point Pattern | |
Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
spatstat-deprecated | Deprecated spatstat functions | |
logLik.slrm | Loglikelihood of Spatial Logistic Regression | |
pcf | Pair Correlation Function | |
affine.ppp | Apply Affine Transformation To Point Pattern | |
Gmulti | Marked Nearest Neighbour Distance Function | |
gpc2owin | Convert Polygonal Region into Different Format | |
plot.msr | Plot a Signed or Vector-Valued Measure | |
linnet | Create a Linear Network | |
adaptive.density | Intensity Estimate of Point Pattern Using Tessellation | |
idw | Inverse-distance weighted smoothing of observations at irregular points | |
areaGain | Difference of Disc Areas | |
Poisson | Poisson Point Process Model | |
pcfinhom | Inhomogeneous Pair Correlation Function | |
Saturated | Saturated Pairwise Interaction model | |
progressreport | Print Progress Reports | |
as.hyperframe.ppx | Extract coordinates and marks of multidimensional point pattern | |
psp | Create a Line Segment Pattern | |
fitted.slrm | Fitted Probabilities for Spatial Logistic Regression | |
methods.rhohat | Methods for Intensity Functions of Spatial Covariate | |
plot.tess | Plot a tessellation | |
rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
nndist | Nearest neighbour distances | |
rpoisline | Generate Poisson Random Line Process | |
pppdist | Distance Between Two Point Patterns | |
logLik.ppm | Log Likelihood and AIC for Point Process Model | |
as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |
diameter | Diameter of an Object | |
is.ppp | Test Whether An Object Is A Point Pattern | |
as.data.frame.im | Convert Pixel Image to Data Frame | |
plot.bermantest | Plot Result of Berman Test | |
im.object | Class of Images | |
incircle | Find Largest Circle Inside Window | |
nndist.psp | Nearest neighbour distances between line segments | |
km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
ants | Harkness-Isham ants' nests data | |
rThomas | Simulate Thomas Process | |
bw.stoyan | Stoyan's Rule of Thumb for Bandwidth Selection | |
clarkevans.test | Clark and Evans Test | |
pairdist.pp3 | Pairwise distances in Three Dimensions | |
DiggleGratton | Diggle-Gratton model | |
as.interact | Extract Interaction Structure | |
bdist.pixels | Distance to Boundary of Window | |
nsegments | Number of Line Segments in a Line Segment Pattern | |
box3 | Three-Dimensional Box | |
Jmulti | Marked J Function | |
kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
chop.tess | Subdivide a Window or Tessellation using a Set of Lines | |
pcf3est | Pair Correlation Function of a Three-Dimensional Point Pattern | |
as.tess | Convert Data To Tessellation | |
pairdist.lpp | Pairwise shortest-path distances between points on a linear network | |
finpines | Pine saplings in Finland. | |
predict.lppm | Predict Point Process Model on Linear Network | |
cells | Biological Cells Point Pattern | |
border | Border Region of a Window | |
Strauss | The Strauss Point Process Model | |
bdist.points | Distance to Boundary of Window | |
amacrine | Hughes' Amacrine Cell Data | |
residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
bermantest | Berman's Tests for Point Process Model | |
crossdist.psp | Pairwise distances between two different line segment patterns | |
lineardisc | Compute Disc of Given Radius in Linear Network | |
DiggleGatesStibbard | Diggle-Gates-Stibbard Point Process Model | |
by.ppp | Apply a Function to a Point Pattern Broken Down by Factor | |
qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
pcfcross.inhom | Inhomogeneous Multitype Pair Correlation Function (Cross-Type) | |
reach | Interaction Distance of a Point Process | |
Kcross.inhom | Inhomogeneous Cross K Function | |
as.hyperframe | Convert Data to Hyperframe | |
infline | Infinite Straight Lines | |
ppp.object | Class of Point Patterns | |
distfun | Distance Map as a Function | |
pairdist.ppp | Pairwise distances | |
runifpointOnLines | Generate N Uniform Random Points On Line Segments | |
rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |
crossdist | Pairwise distances | |
setcov | Set Covariance of a Window | |
pixelquad | Quadrature Scheme Based on Pixel Grid | |
rotate.owin | Rotate a Window | |
clickjoin | Interactively join vertices on a plot | |
default.expand | Compute Expansion Window for Simulation | |
G3est | Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern | |
Extract.tess | Extract or Replace Subset of Tessellation | |
fryplot | Fry Plot of Point Pattern | |
rescale.im | Convert Pixel Image to Another Unit of Length | |
crossdist.ppx | Pairwise Distances Between Two Different Multi-Dimensional Point Patterns | |
coef.ppm | Coefficients of Fitted Point Process Model | |
rpoislinetess | Poisson Line Tessellation | |
dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
fv | Create a Function Value Table | |
psp.object | Class of Line Segment Patterns | |
redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
contour.im | Contour plot of pixel image | |
ripras | Estimate window from points alone | |
plot.colourmap | Plot a Colour Map | |
plot.kppm | Plot a fitted cluster point process | |
pcfdot.inhom | Inhomogeneous Multitype Pair Correlation Function (Type-i-To-Any-Type) | |
periodify | Make Periodic Copies of a Spatial Pattern | |
residuals.ppm | Residuals for Fitted Point Process Model | |
mincontrast | Method of Minimum Contrast | |
localK | Neighbourhood density function | |
print.ppm | Print a Fitted Point Process Model | |
rlabel | Random Re-Labelling of Point Pattern | |
runifdisc | Generate N Uniform Random Points in a Disc | |
compareFit | Residual Diagnostics for Multiple Fitted Models | |
eval.fasp | Evaluate Expression Involving Function Arrays | |
is.marked | Test Whether Marks Are Present | |
matchingdist | Distance for a Point Pattern Matching | |
Ldot | Multitype L-function (i-to-any) | |
quadrat.test | Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
print.quad | Print a Quadrature Scheme | |
quadrat.test.splitppp | Chi-Squared Test of CSR for Split Point Pattern | |
concatxy | Concatenate x,y Coordinate Vectors | |
profilepl | Profile Maximum Pseudolikelihood | |
rmh.ppm | Simulate from a Fitted Point Process Model | |
lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
intersect.tess | Intersection of Two Tessellations | |
as.data.frame.hyperframe | Coerce Hyperframe to Data Frame | |
linearpcf | Linear Pair Correlation Function | |
append.psp | Combine Two Line Segment Patterns | |
shift.owin | Apply Vector Translation To Window | |
Ord | Generic Ord Interaction model | |
stieltjes | Compute Integral of Function Against Cumulative Distribution | |
nnclean | Nearest Neighbour Clutter Removal | |
is.owin | Test Whether An Object Is A Window | |
affine.owin | Apply Affine Transformation To Window | |
discpartarea | Area of Part of Disc | |
rMosaicSet | Mosaic Random Set | |
K3est | K-function of a Three-Dimensional Point Pattern | |
distmap.owin | Distance Map of Window | |
mean.im | Maximum, Minimum, Mean, Median, Range or Sum of Pixel Values in an Image | |
nztrees | New Zealand Trees Point Pattern | |
pixellate.ppp | Convert Point Pattern to Pixel Image | |
summary.im | Summarizing a Pixel Image | |
density.psp | Kernel Smoothing of Line Segment Pattern | |
spatstat-internal | Internal spatstat functions | |
longleaf | Longleaf Pines Point Pattern | |
StraussHard | The Strauss / Hard Core Point Process Model | |
spruces | Spruces Point Pattern | |
fasp.object | Function Arrays for Spatial Patterns | |
eem | Exponential Energy Marks | |
expand.owin | Expand Window By Factor | |
as.mask | Pixel Image Approximation of a Window | |
summary.splitppp | Summary of a Split Point Pattern | |
plot.fasp | Plot a Function Array | |
flipxy | Exchange X and Y Coordinates | |
scanpp | Read Point Pattern From Data File | |
psstA | Pseudoscore Diagnostic For Fitted Model against Area-Interaction Alternative | |
rpoisppx | Generate Poisson Point Pattern in Any Dimensions | |
perimeter | Perimeter Length of Window | |
fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |
markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
Extract.msr | Extract Subset of Signed or Vector Measure | |
union.quad | Union of Data and Dummy Points | |
im | Create a Pixel Image Object | |
pointsOnLines | Place Points Evenly Along Specified Lines | |
predict.kppm | Prediction from a Fitted Cluster Point Process Model | |
rescale.owin | Convert Window to Another Unit of Length | |
tile.areas | Compute Areas of Tiles in a Tessellation | |
quadratresample | Resample a Point Pattern by Resampling Quadrats | |
miplot | Morishita Index Plot | |
iplot | Point and Click Interface for Displaying a Point Pattern | |
lengths.psp | Lengths of Line Segments | |
Kmulti | Marked K-Function | |
rLGCP | Simulate Log-Gaussian Cox Process | |
Extract.quad | Subset of Quadrature Scheme | |
swedishpines | Swedish Pines Point Pattern | |
Gres | Residual G Function | |
summary.ppm | Summarizing a Fitted Point Process Model | |
hist.im | Histogram of Pixel Values in an Image | |
rmpoint | Generate N Random Multitype Points | |
model.frame.ppm | Extract the Environment of a Point Process Model | |
square | Square Window | |
rGaussPoisson | Simulate Gauss-Poisson Process | |
rpoislpp | Poisson Point Process on a Linear Network | |
lurking | Lurking variable plot | |
plot.ppp | plot a Spatial Point Pattern | |
affine.psp | Apply Affine Transformation To Line Segment Pattern | |
plot.im | Plot a Pixel Image | |
nnwhich | Nearest neighbour | |
alltypes | Calculate Summary Statistic for All Types in a Multitype Point Pattern | |
rcell | Simulate Baddeley-Silverman Cell Process | |
rMatClust | Simulate Matern Cluster Process | |
nnwhich.ppx | Nearest Neighbours in Any Dimensions | |
spatstat.options | Internal Options in Spatstat Package | |
as.matrix.im | Convert Pixel Image to Matrix or Array | |
nbfires | Point Patterns of New Brunswick Forest Fires | |
which.max.im | Identify Pixelwise Maximum of Several Pixel Images | |
summary.psp | Summary of a Line Segment Pattern Dataset | |
rknn | Theoretical Distribution of Nearest Neighbour Distance | |
plot.fv | Plot Function Values | |
pixellate | Convert Spatial Object to Pixel Image | |
plot.pp3 | Plot a three-dimensional point pattern | |
simdat | Simulated Point Pattern | |
boxx | Multi-Dimensional Box | |
print.ppp | Print Brief Details of a Point Pattern Dataset | |
tiles | Extract List of Tiles in a Tessellation | |
bw.relrisk | Cross Validated Bandwidth Selection for Relative Risk Estimation | |
circumradius | Circumradius and Diameter of a Linear Network | |
closing | Morphological Closing | |
unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
marktable | Tabulate Marks in Neighbourhood of Every Point in a Point Pattern | |
applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
split.im | Divide Image Into Sub-images | |
betacells | Beta Ganglion Cells in Cat Retina | |
plot.splitppp | Plot a List of Point Patterns | |
rStrauss | Perfect Simulation of the Strauss Process | |
rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |
matclust.estpcf | Fit the Matern Cluster Point Process by Minimum Contrast Using Pair Correlation | |
split.ppp | Divide Point Pattern into Sub-patterns | |
collapse.fv | Collapse Several Function Tables into One | |
plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
coef.slrm | Coefficients of Fitted Spatial Logistic Regression Model | |
inside.owin | Test Whether Points Are Inside A Window | |
delaunay | Delaunay Triangulation of Point Pattern | |
rlinegrid | Generate grid of parallel lines with random displacement | |
deltametric | Delta Metric | |
Extract.ppp | Extract or Replace Subset of Point Pattern | |
is.stationary | Recognise Stationary and Poisson Point Process Models | |
methods.pp3 | Methods for three-dimensional point patterns | |
npoints | Number of Points in a Point Pattern | |
as.im | Convert to Pixel Image | |
varblock | Estimate Variance of Summary Statistic by Subdivision | |
coords | Extract or Change Coordinates of a Spatial or Spatiotemporal Point Pattern | |
methods.box3 | Methods for Three-Dimensional Box | |
as.psp | Convert Data To Class psp | |
methods.lpp | Methods for Point Patterns on a Linear Network | |
shift.psp | Apply Vector Translation To Line Segment Pattern | |
nndist.ppx | Nearest Neighbour Distances in Any Dimensions | |
pp3 | Three Dimensional Point Pattern | |
smooth.fv | Apply Smoothing to Function Values | |
rescale | Convert dataset to another unit of length | |
intersect.owin | Intersection, Union or Set Subtraction of Two Windows | |
msr | Signed or Vector-Valued Measure | |
as.ppp | Convert Data To Class ppp | |
rshift.ppp | Randomly Shift a Point Pattern | |
Extract.fv | Extract Subset of Function Values | |
rotate | Rotate | |
suffstat | Sufficient Statistic of Point Process Model | |
is.im | Test Whether An Object Is A Pixel Image | |
print.im | Print Brief Details of an Image | |
rstrat | Simulate Stratified Random Point Pattern | |
lpp | Create Point Pattern on Linear Network | |
effectfun | Compute Fitted Effect of a Spatial Covariate in a Point Process Model | |
pcfcross | Multitype pair correlation function (cross-type) | |
rshift.splitppp | Randomly Shift a List of Point Patterns | |
Softcore | The Soft Core Point Process Model | |
pppmatching.object | Class of Point Matchings | |
urkiola | Urkiola Woods Point Pattern | |
simulate.kppm | Simulate a Fitted Cluster Point Process Model | |
scaletointerval | Rescale Data to Lie Between Specified Limits | |
quad.object | Class of Quadrature Schemes | |
sharpen | Data Sharpening of Point Pattern | |
with.hyperframe | Evaluate an Expression in Each Row of a Hyperframe | |
areaLoss | Difference of Disc Areas | |
nearest.raster.point | Find Pixel Nearest to a Given Point | |
disc | Circular Window | |
superimpose | Superimpose Several Geometric Patterns | |
erosion | Morphological Erosion | |
hamster | Aherne's hamster tumour data | |
connected | Connected components of an image or window | |
spatstat-package | The Spatstat Package | |
rSSI | Simulate Simple Sequential Inhibition | |
distmap.ppp | Distance Map of Point Pattern | |
opening | Morphological Opening | |
complement.owin | Take Complement of a Window | |
nearestsegment | Find Line Segment Nearest to Each Point | |
inforder.family | Infinite Order Interaction Family | |
pixellate.psp | Convert Line Segment Pattern to Pixel Image | |
diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
default.dummy | Generate a Default Pattern of Dummy Points | |
diameter.box3 | Geometrical Calculations for Three-Dimensional Box | |
plot.linim | Plot Pixel Image on Linear Network | |
rotate.ppp | Rotate a Point Pattern | |
with.fv | Evaluate an Expression in a Function Table | |
simulate.ppm | Simulate a Fitted Gibbs Point Process Model | |
crossdist.default | Pairwise distances between two different sets of points | |
humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
distmap | Distance Map | |
plot.listof | Plot a List of Things | |
plot.hyperframe | Plot Entries in a Hyperframe | |
murchison | Murchison gold deposits | |
unmark | Remove Marks | |
smooth.msr | Smooth a Signed or Vector-Valued Measure | |
integral.im | Integral of a Pixel Image | |
linearKinhom | Inhomogeneous Linear K Function | |
pcf.ppp | Pair Correlation Function of Point Pattern | |
persp.im | Perspective Plot of Pixel Image | |
envelope.pp3 | Simulation Envelopes of Summary Function for 3D Point Pattern | |
ewcdf | Weighted Empirical Cumulative Distribution Function | |
istat | Point and Click Interface for Exploratory Analysis of Point Pattern | |
quadratcount | Quadrat counting for a point pattern | |
eval.im | Evaluate Expression Involving Pixel Images | |
plot.kstest | Plot a Spatial Kolmogorov-Smirnov Test | |
as.owin | Convert Data To Class owin | |
matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
runifpoint | Generate N Uniform Random Points | |
formula.ppm | Model Formulae for Gibbs Point Process Models | |
rjitter | Random Perturbation of a Point Pattern | |
pairsat.family | Saturated Pairwise Interaction Point Process Family | |
is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
plot.ppm | plot a Fitted Point Process Model | |
print.owin | Print Brief Details of a Spatial Window | |
rMosaicField | Mosaic Random Field | |
pcf.fv | Pair Correlation Function obtained from K Function | |
hyperframe | Hyper Data Frame | |
quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |
selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
rpoispp | Generate Poisson Point Pattern | |
markcorr | Mark Correlation Function | |
is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
npfun | Dummy Function Returns Number of Points | |
markvario | Mark Variogram | |
pppmatching | Create a Point Matching | |
lgcp.estpcf | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
project2segment | Move Point To Nearest Line | |
rpoisppOnLines | Generate Poisson Point Pattern on Line Segments | |
rthin | Random Thinning | |
linearK | Linear K Function | |
rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |
lut | Lookup Tables | |
quadrats | Divide Region into Quadrats | |
pairdist.default | Pairwise distances | |
runiflpp | Uniform Random Points on a Linear Network | |
shift.ppp | Apply Vector Translation To Point Pattern | |
methods.linnet | Methods for Linear Networks | |
solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
ppx | Multidimensional Space-Time Point Pattern | |
owin | Create a Window | |
rshift.psp | Randomly Shift a Line Segment Pattern | |
thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
methods.kppm | Methods for Cluster Point Process Models | |
sumouter | Compute Quadratic Forms | |
slrm | Spatial Logistic Regression | |
reduced.sample | Reduced Sample Estimator using Histogram Data | |
summary.ppp | Summary of a Point Pattern Dataset | |
nndist.pp3 | Nearest neighbour distances in three dimensions | |
quantile.im | Sample Quantiles of Pixel Image | |
rmpoispp | Generate Multitype Poisson Point Pattern | |
spokes | Spokes pattern of dummy points | |
rescue.rectangle | Convert Window Back To Rectangle | |
thomas.estpcf | Fit the Thomas Point Process by Minimum Contrast | |
endpoints.psp | Endpoints of Line Segment Pattern | |
summary.owin | Summary of a Spatial Window | |
update.ppm | Update a Fitted Point Process Model | |
summary.listof | Summary of a List of Things | |
predict.ppm | Prediction from a Fitted Point Process Model | |
osteo | Osteocyte Lacunae Data: Replicated Three-Dimensional Point Patterns | |
pairdist.ppx | Pairwise Distances in Any Dimensions | |
pairwise.family | Pairwise Interaction Process Family | |
rhohat | Smoothing Estimate of Covariate Transformation | |
zapsmall.im | Rounding of Pixel Values | |
update.kppm | Update a Fitted Cluster Point Process Model | |
vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
plot.slrm | Plot a Fitted Spatial Logistic Regression | |
print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
psst | Pseudoscore Diagnostic For Fitted Model against General Alternative | |
quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
rNeymanScott | Simulate Neyman-Scott Process | |
rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
runifpointx | Generate N Uniform Random Points in Any Dimensions | |
dilation | Morphological Dilation | |
unitname | Name for Unit of Length | |
rpoint | Generate N Random Points | |
Jcross | Multitype J Function (i-to-j) | |
Hest | Spherical Contact Distribution Function | |
simplify.owin | Approximate a Polygon by a Simpler Polygon | |
runifpoint3 | Generate N Uniform Random Points in Three Dimensions | |
Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
affine | Apply Affine Transformation | |
raster.x | Cartesian Coordinates for a Pixel Raster | |
blur | Apply Gaussian Blur to a Pixel Image | |
bramblecanes | Hutchings' Bramble Canes data | |
bronzefilter | Bronze gradient filter data | |
psstG | Pseudoscore Diagnostic For Fitted Model against Saturation Alternative | |
kppm | Fit Cluster or Cox Point Process Model | |
clickpoly | Interactively Define a Polygon | |
compatible.fv | Test Whether Two Function Objects Are Compatible | |
copper | Berman-Huntington points and lines data | |
diameter.owin | Diameter of a Window | |
identify.ppp | Identify Points in a Point Pattern | |
compatible.im | Test Whether Two Pixel Images Are Compatible | |
rMaternI | Simulate Matern Model I | |
plot.envelope | Plot a Simulation Envelope | |
redwood | California Redwoods Point Pattern (Ripley's Subset) | |
methods.ppx | Methods for Multidimensional Space-Time Point Patterns | |
is.marked.ppm | Test Whether A Point Process Model is Marked | |
japanesepines | Japanese Pines Point Pattern | |
Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
lansing | Lansing Woods Point Pattern | |
Hardcore | The Hard Core Point Process Model | |
linearpcfinhom | Inhomogeneous Linear Pair Correlation Function | |
levelset | Level Set of a Pixel Image | |
marks | Marks of a Point Pattern | |
pcf.fasp | Pair Correlation Function obtained from array of K functions | |
pixellate.owin | Convert Window to Pixel Image | |
cbind.hyperframe | Combine Hyperframes by Rows or by Columns | |
rescale.ppp | Convert Point Pattern to Another Unit of Length | |
ppm.object | Class of Fitted Point Process Models | |
clickppp | Interactively Add Points | |
corners | Corners of a rectangle | |
eroded.areas | Areas of Morphological Erosions | |
tess | Create a Tessellation | |
rshift | Random Shift | |
is.multitype | Test whether Object is Multitype | |
latest.news | Print News About Latest Version of Package | |
nncorr | Nearest-Neighbour Correlation Indices of Marked Point Pattern | |
ord.family | Ord Interaction Process Family | |
pcfdot | Multitype pair correlation function (i-to-any) | |
predict.slrm | Predicted or Fitted Values from Spatial Logistic Regression | |
rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
rsyst | Simulate systematic random point pattern | |
shift.im | Apply Vector Translation To Pixel Image | |
shift | Apply Vector Translation | |
whist | Weighted Histogram | |
vertices | Vertices of a Window | |
localKinhom | Inhomogeneous Neighbourhood Density Function | |
model.images | Compute Images of Constructed Covariates | |
F3est | Empty Space Function of a Three-Dimensional Point Pattern | |
Geyer | Geyer's Saturation Point Process Model | |
PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
compatible.fasp | Test Whether Two Function Arrays Are Compatible | |
default.rmhcontrol | Set Default Control Parameters for Metropolis-Hastings Algorithm. | |
is.empty | Test Whether An Object Is Empty | |
is.convex | Test Whether a Window is Convex | |
interp.im | Interpolate a Pixel Image | |
lppm | Fit Point Process Model to Point Pattern on Linear Network | |
pairdist | Pairwise distances | |
ppp | Create a Point Pattern | |
rotate.psp | Rotate a Line Segment Pattern | |
shapley | Galaxies in the Shapley Supercluster | |
simplenet | Simple Example of Linear Network | |
smooth.ppp | Spatial smoothing of observations at irregular points | |
summary.quad | Summarizing a Quadrature Scheme | |
Extract.listof | Extract or Replace Subset of a List of Things | |
MultiHard | The Multitype Hard Core Point Process Model | |
data.ppm | Extract Original Data from a Fitted Point Process Model | |
bounding.box.xy | Convex Hull of Points | |
density.ppp | Kernel Smoothed Intensity of Point Pattern | |
diameter.boxx | Geometrical Calculations for Multi-Dimensional Box | |
gridweights | Compute Quadrature Weights Based on Grid Counts | |
eval.fv | Evaluate Expression Involving Functions | |
letterR | Window in Shape of Letter R | |
localpcf | Local pair correlation function | |
markcorrint | Mark Correlation Integral | |
marks.psp | Marks of a Line Segment Pattern | |
model.matrix.ppm | Extract Design Matrix from Point Process Model | |
pairdist.psp | Pairwise distances between line segments | |
plot.owin | Plot a Spatial Window | |
plot.quad | plot a Spatial Quadrature Scheme | |
rMaternII | Simulate Matern Model II | |
relrisk | Nonparametric Estimate of Spatially-Varying Relative Risk | |
rgbim | Create Colour-Valued Pixel Image | |
trim.rectangle | Cut margins from rectangle | |
vcov.kppm | Variance-Covariance Matrix for a Fitted Cluster Point Process Model | |
volume | Volume of an Object | |
ppm | Fit Point Process Model to Data | |
rpoispp3 | Generate Poisson Point Pattern in Three Dimensions | |
No Results! |
Last month downloads
Details
Date | 2011-08-12 |
License | GPL (>= 2) |
URL | http://www.spatstat.org |
Packaged | 2011-08-12 11:25:44 UTC; adrian |
Repository | CRAN |
Date/Publication | 2011-08-12 14:30:54 |
depends | base (>= 2.13.0) , deldir (>= 0.0-10) , graphics , mgcv , R (>= 2.13.0) , stats , utils |
suggests | gpclib , maptools , RandomFields (>= 2.0) , rpanel , scatterplot3d , sm , spatial , tkrplot |
Contributors | Rolf Turner, Adrian Baddeley |
Include our badge in your README
[](http://www.rdocumentation.org/packages/spatstat)