spatstat v1.10-2
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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 | |
compatible.fv | Test Whether Two Function Objects Are Compatible | |
data.ppm | Extract Original Data from a Fitted Point Process Model | |
density.psp | Kernel Smoothing of Line Segment Pattern | |
chorley | Chorley-Ribble Cancer Data | |
distmap.psp | Distance Map of Line Segment Pattern | |
is.multitype.ppm | Test Whether A Point Process Model is Multitype | |
lansing | Lansing Woods Point Pattern | |
nncorr | Nearest-Neighbour Correlation of Marked Point Pattern | |
plot.splitppp | Plot a List of Point Patterns | |
quadratcount | Quadrat counting for a point pattern | |
redwood | California Redwoods Point Pattern (Ripley's Subset) | |
rotate | Rotate | |
subset.im | Extract Subset of Image | |
spatstat | The Spatstat Package | |
spokes | Spokes pattern of dummy points | |
unique.ppp | Extract Unique Points from a Spatial Point Pattern | |
MultiStrauss | The Multitype Strauss Point Process Model | |
alltypes | Calculate Statistic for All Types in a Multitype Point Pattern | |
area.owin | Area of a Window | |
crossing.psp | Crossing Points of Two Line Segment Patterns | |
envelope | Simulation envelopes of summary function | |
cut.ppp | Convert Point Pattern Marks from Numeric to Factor | |
is.im | Test Whether An Object Is A Pixel Image | |
pairdist.default | Pairwise distances | |
rMaternII | Simulate Matern Model II | |
plot.owin | Plot a Spatial Window | |
selfcrossing.psp | Crossing Points in a Line Segment Pattern | |
harmonic | Basis for Harmonic Functions | |
km.rs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
rcell | Simulate Baddeley-Silverman Cell Process | |
affine.owin | Apply Affine Transformation To Window | |
rpoint | Generate N Random Points | |
summary.ppp | Summary of a Point Pattern Dataset | |
as.im | Convert to Pixel Image | |
quantile.im | Sample Quantiles of Pixel Image | |
pcf.fasp | Pair Correlation Function obtained from array of K functions | |
superimpose | Superimpose Several Point Patterns | |
Kmulti | Marked K-Function | |
StraussHard | The Strauss / Hard Core Point Process Model | |
diagnose.ppm | Diagnostic Plots for Fitted Point Process Model | |
profilepl | Profile Maximum Pseudolikelihood | |
psp.object | Class of Line Segment Patterns | |
quad.object | Class of Quadrature Schemes | |
rshift.splitppp | Randomly Shift a List of Point Patterns | |
runifpoint | Generate N Uniform Random Points | |
pairdist.ppp | Pairwise distances | |
rshift.ppp | Randomly Shift a Point Pattern | |
ppp.object | Class of Point Patterns | |
summary.quad | Summarizing a Quadrature Scheme | |
thomas.estK | Fit the Thomas Point Process by Minimum Contrast | |
as.ppp | Convert Data To Class ppp | |
coef.ppm | Coefficients of Fitted Point Process Model | |
density.splitppp | Kernel Smoothed Intensity of Split Point Pattern | |
distmap.owin | Distance Map of Window | |
Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
affine.ppp | Apply Affine Transformation To Point Pattern | |
is.marked | Test Whether Marks Are Present | |
Kest | K-function | |
betacells | Beta Ganglion Cells in Cat Retina | |
complement.owin | Take Complement of a Window | |
nnwhich | Nearest neighbour | |
eem | Exponential Energy Marks | |
spatstat-internal | Internal spatstat functions | |
lengths.psp | Lengths of Line Segments | |
crossdist.psp | Pairwise distances between two different line segment patterns | |
levelset | Level Set of a Pixel Image | |
density.ppp | Kernel Smoothed Intensity of Point Pattern | |
Jdot | Multitype J Function (i-to-any) | |
print.ppp | Print Brief Details of a Point Pattern Dataset | |
lgcp.estK | Fit a Log-Gaussian Cox Point Process by Minimum Contrast | |
quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
Kmeasure | Reduced Second Moment Measure | |
residualspaper | Data and Code From JRSS Discussion Paper on Residuals | |
letterR | Window in Shape of Letter R | |
runifdisc | Generate N Uniform Random Points in a Disc | |
crossdist.ppp | Pairwise distances between two different point patterns | |
shift.im | Apply Vector Translation To Pixel Image | |
anova.ppm | ANOVA for Fitted Point Process Models | |
japanesepines | Japanese Pines Point Pattern | |
demopat | Artificial Data Point Pattern | |
lurking | Lurking variable plot | |
subset.fasp | Extract Subset of Function Array | |
pairdist.psp | Pairwise distances between line segments | |
Saturated | Saturated Pairwise Interaction model | |
rMaternI | Simulate Matern Model I | |
rpoispp | Generate Poisson Point Pattern | |
append.psp | Combine Two Line Segment Patterns | |
swedishpines | Swedish Pines Point Pattern | |
as.matrix.im | Convert Pixel Image to Matrix | |
subset.ppp | Extract or Replace Subset of Point Pattern | |
bei | Tropical rain forest trees | |
rThomas | Simulate Thomas Process | |
suffstat | Sufficient Statistic of Point Process Model | |
rstrat | Simulate Stratified Random Point Pattern | |
spatstat-deprecated | Deprecated spatstat functions | |
expand.owin | Expand Window By Factor | |
Iest | Estimate the I-function | |
dilate.owin | Dilate a Window | |
Softcore | The Soft Core Point Process Model | |
Kest.fft | K-function using FFT | |
identify.ppp | Identify Points in a Point Pattern | |
duplicated.ppp | Determine Duplicated Points in a Spatial Point Pattern | |
midpoints.psp | Midpoints of Line Segment Pattern | |
Strauss | The Strauss Point Process Model | |
summary.psp | Summary of a Line Segment Pattern Dataset | |
Jcross | Multitype J Function (i-to-j) | |
print.ppm | Print a Fitted Point Process Model | |
square | Square Window | |
shift | Apply Vector Translation | |
trim.rectangle | Cut margins from rectangle | |
rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
pcf.fv | Pair Correlation Function obtained from K Function | |
crossdist.default | Pairwise distances between two different sets of points | |
fv.object | Data Frames of Function Values | |
unmark | Remove Marks from a Marked Point Pattern | |
plot.fasp | Plot a Function Array | |
ord.family | Ord Interaction Process Family | |
qqplot.ppm | Q-Q Plot of Residuals from Fitted Point Process Model | |
rmhstart | Determine Initial State for Metropolis-Hastings Simulation. | |
print.psp | Print Brief Details of a Line Segment Pattern Dataset | |
raster.x | Cartesian Coordinates for a Pixel Raster | |
shift.psp | Apply Vector Translation To Line Segment Pattern | |
PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
pppdist | Optimal Match Between Two Point Patterns | |
shift.ppp | Apply Vector Translation To Point Pattern | |
rotate.psp | Rotate a Line Segment Pattern | |
clickppp | Interactively Add Points | |
summary.owin | Summary of a Spatial Window | |
summary.ppm | Summarizing a Fitted Point Process Model | |
copper | Berman-Huntington points and lines data | |
subset.fv | Extract Subset of Function Values | |
distmap | Distance Map | |
rNeymanScott | Simulate Neyman-Scott Process | |
diameter | Diameter of a Window Frame | |
eval.fv | Evaluate Expression Involving Functions | |
intersect.owin | Intersection or Union of Two Windows | |
Kdot.inhom | Inhomogeneous Multitype K Dot Function | |
matclust.estK | Fit the Matern Cluster Point Process by Minimum Contrast | |
plot.ppp | plot a Spatial Point Pattern | |
print.owin | Print Brief Details of a Spatial Window | |
dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
Kcross | Multitype K Function (Cross-type) | |
as.mask | Pixel Image Approximation of a Window | |
LennardJones | The Lennard-Jones Potential | |
crossdist | Pairwise distances | |
default.dummy | Generate a Default Pattern of Dummy Points | |
gridcentres | Rectangular grid of points | |
fasp.object | Function Arrays for Spatial Patterns | |
is.ppp | Test Whether An Object Is A Point Pattern | |
Jest | Estimate the J-function | |
Poisson | Poisson Point Process Model | |
nearest.raster.point | Find Pixel Nearest to a Given Point | |
bramblecanes | Hutchings' Bramble Canes data | |
nztrees | New Zealand Trees Point Pattern | |
dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
rsyst | Simulate systematic random point pattern | |
is.marked.ppp | Test Whether A Point Pattern is Marked | |
is.ppm | Test Whether An Object Is A Fitted Point Process Model | |
is.multitype.ppp | Test Whether A Point Pattern is Multitype | |
mean.im | Mean Pixel Value in an Image | |
markstat | Summarise Marks in Every Neighbourhood in a Point Pattern | |
ppp | Create a Point Pattern | |
scanpp | Read Point Pattern From Data File | |
ripras | Estimate window from points alone | |
shift.owin | Apply Vector Translation To Window | |
solutionset | Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True | |
summary.im | Summarizing a Pixel Image | |
setcov | Set Covariance of a Window | |
Ord | Generic Ord Interaction model | |
as.psp | Convert Data To Class psp | |
corners | Corners of a rectangle | |
allstats | Calculate four standard summary functions of a point pattern. | |
as.owin | Convert Data To Class owin | |
contour.im | Contour plot of pixel image | |
concatxy | Concatenate x,y Coordinate Vectors | |
bdist.points | Distance to Boundary of Window | |
bdist.pixels | Distance to Boundary of Window | |
eroded.areas | Areas of Morphological Erosions | |
ganglia | Beta Ganglion Cells in Cat Retina, Old Version | |
print.im | Print Brief Details of an Image | |
gridweights | Compute Quadrature Weights Based on Grid Counts | |
plot.quad | plot a Spatial Quadrature Scheme | |
pcf | Pair Correlation Function | |
ppm | Fit Point Process Model to Data | |
setmarks | Set or Reset the Marks in a Point Pattern | |
quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
reduced.sample | Reduced Sample Estimator using Histogram Data | |
rotate.owin | Rotate a Window | |
Gest | Nearest Neighbour Distance Function G | |
Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
ants | Harkness-Isham ants' nests data | |
hamster | Aherne's hamster tumour data | |
plot.im | Plot a Pixel Image | |
plot.listof | Plot a List of Things | |
rlabel | Random Re-Labelling of Point Pattern | |
pairwise.family | Pairwise Interaction Process Family | |
rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
rotate.ppp | Rotate a Point Pattern | |
rmpoispp | Generate Multitype Poisson Point Pattern | |
split.ppp | Divide Point Pattern into Sub-patterns | |
update.ppm | Update a Fitted Point Process Model | |
Jmulti | Marked J Function | |
Pairwise | Generic Pairwise Interaction model | |
bounding.box | Bounding Box of a Window | |
cells | Biological Cells Point Pattern | |
is.subset.owin | Determine Whether One Window is Contained In Another | |
as.rectangle | Window Frame | |
owin.object | Class owin | |
predict.ppm | Prediction from a Fitted Point Process Model | |
Fest | Estimate the empty space function F | |
OrdThresh | Ord's Interaction model | |
angles.psp | Orientation Angles of Line Segments | |
cut.im | Convert Pixel Image from Numeric to Factor | |
endpoints.psp | Endpoints of Line Segment Pattern | |
eval.im | Evaluate Expression Involving Pixel Images | |
owin | Create a Window | |
plot.psp | plot a Spatial Line Segment Pattern | |
plot.ppm | plot a Fitted Point Process Model | |
print.quad | Print a Quadrature Scheme | |
spruces | Spruces Point Pattern | |
Gmulti | Marked Nearest Neighbour Distance Function | |
amacrine | Hughes' Amacrine Cell Data | |
disc | Circular Window | |
humberside | Humberside Data on Childhood Leukaemia and Lymphoma | |
inside.owin | Test Whether Points Are Inside A Window | |
is.multitype | Test whether Object is Multitype | |
markcorr | Mark Correlation Function | |
nndist | Nearest neighbour distances | |
mincontrast | Method of Minimum Contrast | |
pairsat.family | Saturated Pairwise Interaction Point Process Family | |
quadrat.test | Chi-Squared Dispersion Test for Spatial Point Pattern Based on Quadrat Counts | |
ppm.object | Class of Fitted Point Process Models | |
redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
residuals.ppm | Residuals for Fitted Point Process Model | |
rmhcontrol | Set Control Parameters for Metropolis-Hastings Algorithm. | |
DiggleGratton | Diggle-Gratton model | |
affine | Apply Affine Transformation | |
finpines | Pine saplings in Finland. | |
hist.im | Histogram of Pixel Values in an Image | |
is.owin | Test Whether An Object Is A Window | |
rStrauss | Perfect Simulation of the Strauss Process | |
pairdist | Pairwise distances | |
rescue.rectangle | Convert Window Back To Rectangle | |
rshift.psp | Randomly Shift a Line Segment Pattern | |
rshift | Random Shift | |
Kdot | Multitype K Function (i-to-any) | |
distmap.ppp | Distance Map of Point Pattern | |
Kinhom | Inhomogeneous K-function | |
im | Create a Pixel Image Object | |
is.marked.ppm | Test Whether A Point Process Model is Marked | |
rMatClust | Simulate Matern Cluster Process | |
reach | Interaction Distance of a Point Process | |
rmh.ppm | Simulate from a Fitted Point Process Model | |
rmpoint | Generate N Random Multitype Points | |
rthin | Random Thinning | |
units | Name for Unit of Length | |
Geyer | Geyer's Saturation Point Process Model | |
Kcross.inhom | Inhomogeneous Cross K Function | |
MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
compatible.im | Test Whether Two Pixel Images Are Compatible | |
erode.owin | Erode a Window | |
fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
multiplicity.ppp | Count Multiplicity of Duplicate Points | |
longleaf | Longleaf Pines Point Pattern | |
plot.fv | Plot Function Valuesn | |
psp | Create a Line Segment Pattern | |
im.object | Class of Images | |
rSSI | Simulate Simple Sequential Inhibition | |
rpoisline | Generate Poisson Random Line Process | |
spatstat.options | Internal Options in Spatstat Package | |
vcov.ppm | Variance-Covariance Matrix for a Fitted Point Process Model | |
union.quad | Union of Data and Dummy Points | |
simdat | Simulated Point Pattern | |
subset.psp | Extract Subset of Line Segment Pattern | |
affine.psp | Apply Affine Transformation To Line Segment Pattern | |
centroid.owin | Centroid of a window | |
kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
nncross | Nearest Neighbour in Another Point Pattern | |
persp.im | Perspective Plot of Pixel Image | |
rmhmodel | Define Point Process Model for Metropolis-Hastings Simulation. | |
plot.plotppm | Plot a plotppm Object Created by plot.ppm | |
pcf.ppp | Pair Correlation Function of Point Pattern | |
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Details
Date | 06 November 2006 |
License | GPL version 2 or newer |
URL | http://www.spatstat.org |
Packaged | Mon Nov 6 16:58:39 2006; adrian |
depends | base (>= 2.2.0) , mgcv , R (>= 2.2.0) |
suggests | deldir , sm |
Contributors | Rolf Turner, Adrian Baddeley |
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