spatstat v1.11-8
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Spatial Point Pattern analysis, model-fitting, simulation, tests
A package for analysing spatial data,
mainly Spatial Point Patterns,
including multitype/marked points and spatial covariates,
in any two-dimensional spatial region.
Contains functions for exploratory data analysis,
model-fitting, simulation, spatial sampling, model diagnostics,
and formal inference. Data types include point patterns,
line segment patterns, spatial windows, and
pixel images. Point process models can be
fitted to point pattern data. Cluster type models are fitted
by the method of minimum contrast. Very general Gibbs point
process models can be fitted to point pattern data
using a function ppm similar to lm or glm. Models may
include dependence on covariates, interpoint interaction
and dependence on marks. Fitted models can be simulated automatically.
Also provides facilities for formal inference (such as chi-squared
tests) and model diagnostics (including simulation
envelopes, residuals, residual plots and Q-Q plots).
Functions in spatstat
Name | Description | |
affine.psp | Apply Affine Transformation To Line Segment Pattern | |
anemones | Beadlet Anemones Data | |
chorley | Chorley-Ribble Cancer Data | |
bramblecanes | Hutchings' Bramble Canes data | |
default.dummy | Generate a Default Pattern of Dummy Points | |
Saturated | Saturated Pairwise Interaction model | |
area.owin | Area of a Window | |
as.mask | Pixel Image Approximation of a Window | |
DiggleGratton | Diggle-Gratton model | |
Kmeasure | Reduced Second Moment Measure | |
bounding.box.xy | Convex Hull of Points | |
affine | Apply Affine Transformation | |
cut.ppp | Convert Point Pattern Marks from Numeric to Factor | |
fv.object | Data Frames of Function Values | |
is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
Kmulti | Marked K-Function | |
Softcore | The Soft Core Point Process Model | |
Kest | K-function | |
nncorr | Nearest-Neighbour Correlation of Marked Point Pattern | |
complement.owin | Take Complement of a Window | |
Kest.fft | K-function using FFT | |
im | Create a Pixel Image Object | |
as.owin | Convert Data To Class owin | |
Poisson | Poisson Point Process Model | |
density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
StraussHard | The Strauss / Hard Core Point Process Model | |
Kcross | Multitype K Function (Cross-type) | |
diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
crossdist.default | Pairwise distances between two different sets of points | |
harmonic | Basis for Harmonic Functions | |
spatstat-internal | Internal spatstat functions | |
bounding.box | Bounding Box of a Window or Point Pattern | |
Kdot | Multitype K Function (i-to-any) | |
data.ppm | Extract Original Data from a Fitted Point Process Model | |
disc | Circular Window | |
finpines | Pine saplings in Finland. | |
Kcross.inhom | Inhomogeneous Cross K Function | |
dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
append.psp | Combine Two Line Segment Patterns | |
anova.ppm | ANOVA for Fitted Point Process Models | |
allstats | Calculate four standard summary functions of a point pattern. | |
crossdist | Pairwise distances | |
pcf | Pair Correlation Function | |
is.im | Test Whether An Object Is A Pixel Image | |
angles.psp | Orientation Angles of Line Segments | |
ants | Harkness-Isham ants' nests data | |
pairdist.psp | Pairwise distances between line segments | |
japanesepines | Japanese Pines Point Pattern | |
km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
pcf.fv | Pair Correlation Function obtained from K Function | |
plot.listof | Plot a List of Things | |
spatstat-deprecated | Deprecated spatstat functions | |
is.ppp | Test Whether An Object Is A Point Pattern | |
clarkevans | Clark and Evans Aggregation Index | |
logLik.ppm | Log Likelihood for Poisson Point Process Model | |
rlabel | Random Re-Labelling of Point Pattern | |
print.im | Print Brief Details of an Image | |
demopat | Artificial Data Point Pattern | |
distmap.owin | Distance Map of Window | |
ks.test.ppm | Kolmogorov-Smirnov Test for Point Process Model | |
midpoints.psp | Midpoints of Line Segment Pattern | |
im.object | Class of Images | |
rStrauss | Perfect Simulation of the Strauss Process | |
ewcdf | Weighted Empirical Cumulative Distribution Function | |
fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
clickpoly | Interactively Define a Polygon | |
compatible.im | Test Whether Two Pixel Images Are Compatible | |
subset.fv | Extract Subset of Function Values | |
lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
nztrees | New Zealand Trees Point Pattern | |
Fest | Estimate the empty space function F | |
is.multitype | Test whether Object is Multitype | |
interp.im | Interpolate a Pixel Image | |
rMatClust | Simulate Matern Cluster Process | |
cut.im | Convert Pixel Image from Numeric to Factor | |
plot.quad | plot a Spatial Quadrature Scheme | |
density.ppp | Kernel Smoothed Intensity of Point Pattern | |
nndist | Nearest neighbour distances | |
rmpoint | Generate N Random Multitype Points | |
rSSI | Simulate Simple Sequential Inhibition | |
multiplicity.ppp | Count Multiplicity of Duplicate Points | |
is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
shift | Apply Vector Translation | |
letterR | Window in Shape of Letter R | |
quadrat.test | Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
levelset | Level Set of a Pixel Image | |
pairwise.family | Pairwise Interaction Process Family | |
ppm.object | Class of Fitted Point Process Models | |
fitin.ppm | Extract the Interaction from a Fitted Point Process Model | |
crossdist.psp | Pairwise distances between two different line segment patterns | |
print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
lansing | Lansing Woods Point Pattern | |
Jdot | Multitype J Function (i-to-any) | |
is.owin | Test Whether An Object Is A Window | |
raster.x | Cartesian Coordinates for a Pixel Raster | |
owin.object | Class owin | |
hist.im | Histogram of Pixel Values in an Image | |
discretise | Safely Convert Point Pattern Window to Binary Mask | |
pairdist.default | Pairwise distances | |
Jest | Estimate the J-function | |
unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
quadratcount | Quadrat counting for a point pattern | |
plot.ppm | plot a Fitted Point Process Model | |
markcorr | Mark Correlation Function | |
pairdist.ppp | Pairwise distances | |
pairdist | Pairwise distances | |
Jcross | Multitype J Function (i-to-j) | |
rpoint | Generate N Random Points | |
eval.fv | Evaluate Expression Involving Functions | |
subset.im | Extract Subset of Image | |
print.ppp | Print Brief Details of a Point Pattern Dataset | |
lengths.psp | Lengths of Line Segments | |
Ord | Generic Ord Interaction model | |
affine.owin | Apply Affine Transformation To Window | |
pairsat.family | Saturated Pairwise Interaction Point Process Family | |
plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
print.quad | Print a Quadrature Scheme | |
density.psp | Kernel Smoothing of Line Segment Pattern | |
Iest | Estimate the I-function | |
Geyer | Geyer's Saturation Point Process Model | |
persp.im | Perspective Plot of Pixel Image | |
profilepl | Profile Maximum Pseudolikelihood | |
quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
ord.family | Ord Interaction Process Family | |
quad.object | Class of Quadrature Schemes | |
amacrine | Hughes' Amacrine Cell Data | |
rescale | Convert dataset to another unit of length | |
rmh.ppm | Simulate from a Fitted Point Process Model | |
summary.listof | Summary of a List of Things | |
ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
update.ppm | Update a Fitted Point Process Model | |
erode.owin | Erode a Window | |
psp | Create a Line Segment Pattern | |
redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
reach | Interaction Distance of a Point Process | |
crossing.psp | Crossing Points of Two Line Segment Patterns | |
simdat | Simulated Point Pattern | |
rThomas | Simulate Thomas Process | |
setmarks | Set or Reset the Marks in a Point Pattern | |
spatstat | The Spatstat Package | |
convexhull.xy | Convex Hull of Points | |
reduced.sample | Reduced Sample Estimator using Histogram Data | |
corners | Corners of a rectangle | |
unmark | Remove Marks from a Marked Point Pattern | |
rshift.ppp | Randomly Shift a Point Pattern | |
Strauss | The Strauss Point Process Model | |
runifpoint | Generate N Uniform Random Points | |
selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
as.matrix.im | Convert Pixel Image to Matrix | |
summary.splitppp | Summary of a Split Point Pattern | |
clickppp | Interactively Add Points | |
predict.ppm | Prediction from a Fitted Point Process Model | |
identify.ppp | Identify Points in a Point Pattern | |
shift.ppp | Apply Vector Translation To Point Pattern | |
envelope | Simulation envelopes of summary function | |
rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
eroded.areas | Areas of Morphological Erosions | |
coef.ppm | Coefficients of Fitted Point Process Model | |
residuals.ppm | Residuals for Fitted Point Process Model | |
rcell | Simulate Baddeley-Silverman Cell Process | |
scanpp | Read Point Pattern From Data File | |
Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
rpoispp | Generate Poisson Point Pattern | |
Gmulti | Marked Nearest Neighbour Distance Function | |
shift.im | Apply Vector Translation To Pixel Image | |
ppm | Fit Point Process Model to Data | |
distmap.ppp | Distance Map of Point Pattern | |
expand.owin | Expand Window By Factor | |
rmhmodel.list | Define Point Process Model for Metropolis-Hastings Simulation. | |
Kinhom | Inhomogeneous K-function | |
longleaf | Longleaf Pines Point Pattern | |
rNeymanScott | Simulate Neyman-Scott Process | |
rescale.owin | Convert Window to Another Unit of Length | |
rshift.psp | Randomly Shift a Line Segment Pattern | |
quantile.im | Sample Quantiles of Pixel Image | |
as.rectangle | Window Frame | |
rthin | Random Thinning | |
is.subset.owin | Determine Whether One Window is Contained In Another | |
rotate.psp | Rotate a Line Segment Pattern | |
OrdThresh | Ord's Interaction model | |
spokes | Spokes pattern of dummy points | |
spruces | Spruces Point Pattern | |
compatible.fv | Test Whether Two Function Objects Are Compatible | |
subset.ppp | Extract or Replace Subset of Point Pattern | |
plot.ppp | plot a Spatial Point Pattern | |
applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
affine.ppp | Apply Affine Transformation To Point Pattern | |
setcov | Set Covariance of a Window | |
is.marked.ppm | Test Whether A Point Process Model is Marked | |
square | Square Window | |
shift.owin | Apply Vector Translation To Window | |
union.quad | Union of Data and Dummy Points | |
lurking | Lurking variable plot | |
gridweights | Compute Quadrature Weights Based on Grid Counts | |
pppdist | Optimal Match Between Two Point Patterns | |
gridcentres | Rectangular grid of points | |
summary.owin | Summary of a Spatial Window | |
shift.psp | Apply Vector Translation To Line Segment Pattern | |
rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
inside.owin | Test Whether Points Are Inside A Window | |
summary.ppm | Summarizing a Fitted Point Process Model | |
as.ppp | Convert Data To Class ppp | |
plot.fasp | Plot a Function Array | |
plot.owin | Plot a Spatial Window | |
betacells | Beta Ganglion Cells in Cat Retina | |
is.marked | Test Whether Marks Are Present | |
ppp | Create a Point Pattern | |
is.marked.ppp | Test Whether A Point Pattern is Marked | |
nbfires | Point Patterns of New Brunswick Forest Fires | |
plot.splitppp | Plot a List of Point Patterns | |
rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
pcf.ppp | Pair Correlation Function of Point Pattern | |
summary.im | Summarizing a Pixel Image | |
copper | Berman-Huntington points and lines data | |
hamster | Aherne's hamster tumour data | |
progressreport | Print Progress Reports | |
rmhmodel.default | Build Point Process Model for Metropolis-Hastings Simulation. | |
Gest | Nearest Neighbour Distance Function G | |
redwood | California Redwoods Point Pattern (Ripley's Subset) | |
residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
crossdist.ppp | Pairwise distances between two different point patterns | |
distmap | Distance Map | |
MultiStrauss | The Multitype Strauss Point Process Model | |
rotate | Rotate | |
rshift.splitppp | Randomly Shift a List of Point Patterns | |
Jmulti | Marked J Function | |
distmap.psp | Distance Map of Line Segment Pattern | |
as.psp | Convert Data To Class psp | |
rlinegrid | Generate grid of parallel lines with random displacement | |
plot.psp | plot a Spatial Line Segment Pattern | |
nncross | Nearest Neighbour in Another Point Pattern | |
rescale.psp | Convert Line Segment Pattern to Another Unit of Length | |
plot.fv | Plot Function Valuesn | |
centroid.owin | Centroid of a window | |
rescue.rectangle | Convert Window Back To Rectangle | |
rotate.ppp | Rotate a Point Pattern | |
subset.psp | Extract Subset of Line Segment Pattern | |
eval.im | Evaluate Expression Involving Pixel Images | |
rescale.ppp | Convert Point Pattern to Another Unit of Length | |
mincontrast | Method of Minimum Contrast | |
rstrat | Simulate Stratified Random Point Pattern | |
rmhmodel.ppm | Interpret Fitted Model for Metropolis-Hastings Simulation. | |
alltypes | Calculate Statistic for All Types in a Multitype Point Pattern | |
is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
concatxy | Concatenate x,y Coordinate Vectors | |
mean.im | Mean Pixel Value in an Image | |
intersect.owin | Intersection or Union of Two Windows | |
endpoints.psp | Endpoints of Line Segment Pattern | |
plot.im | Plot a Pixel Image | |
nndist.psp | Nearest neighbour distances between line segments | |
subset.splitppp | Extract or Replace Sub-Patterns | |
qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
split.ppp | Divide Point Pattern into Sub-patterns | |
nnwhich | Nearest neighbour | |
Pairwise | Generic Pairwise Interaction model | |
summary.ppp | Summary of a Point Pattern Dataset | |
nearest.raster.point | Find Pixel Nearest to a Given Point | |
runifdisc | Generate N Uniform Random Points in a Disc | |
vertices | Vertices of a Window | |
trim.rectangle | Cut margins from rectangle | |
rMaternII | Simulate Matern Model II | |
as.data.frame.ppp | Coerce Point Pattern to a Data Frame | |
ripras | Estimate window from points alone | |
units | Name for Unit of Length | |
rshift | Random Shift | |
as.im | Convert to Pixel Image | |
thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
superimpose | Superimpose Several Point Patterns | |
vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
fasp.object | Function Arrays for Spatial Patterns | |
cells | Biological Cells Point Pattern | |
quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
subset.fasp | Extract Subset of Function Array | |
rotate.owin | Rotate a Window | |
rsyst | Simulate systematic random point pattern | |
summary.quad | Summarizing a Quadrature Scheme | |
spatstat.options | Internal Options in Spatstat Package | |
rmpoispp | Generate Multitype Poisson Point Pattern | |
subset.listof | Extract or Replace Subset of a List of Things | |
swedishpines | Swedish Pines Point Pattern | |
solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
summary.psp | Summary of a Line Segment Pattern Dataset | |
kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
subsetget.im | Reset Values in Subset of Image | |
bdist.points | Distance to Boundary of Window | |
LennardJones | The Lennard-Jones Potential | |
bei | Tropical rain forest trees | |
MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
print.owin | Print Brief Details of a Spatial Window | |
psp.object | Class of Line Segment Patterns | |
bdist.pixels | Distance to Boundary of Window | |
print.ppm | Print a Fitted Point Process Model | |
contour.im | Contour plot of pixel image | |
diameter | Diameter of a Window | |
dilate.owin | Dilate a Window | |
rMaternI | Simulate Matern Model I | |
eem | Exponential Energy Marks | |
rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
owin | Create a Window | |
pcf.fasp | Pair Correlation Function obtained from array of K functions | |
humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
ppp.object | Class of Point Patterns | |
rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
rpoisline | Generate Poisson Random Line Process | |
suffstat | Sufficient Statistic of Point Process Model | |
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Details
Date | 26 July 2007 |
License | GPL version 2 or newer |
URL | http://www.spatstat.org |
Packaged | Fri Jul 27 02:26:55 2007; adrian |
depends | base (>= 2.4.0) , graphics , mgcv , R (>= 2.4.0) , stats |
suggests | deldir , sm |
Contributors | Rolf Turner, Adrian Baddeley |
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