spatstat v1.3-2
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Analysis of spatial point patterns
Spatial Point Pattern data analysis, modelling and simulation
including multitype/marked points and spatial covariates
Functions in spatstat
Name | Description | |
DiggleGratton | Diggle-Gratton model | |
cut.ppp | Convert Point Pattern Marks from Numeric to Factor | |
Jcross | Multitype J Function (i-to-j) | |
eroded.areas | Areas of Morphological Erosions | |
Poisson | Poisson Point Process Model | |
pairdist | Pairwise distances | |
bounding.box | Bounding Box of a Window | |
dummy.ppm | Extract Dummy Points Used to Fit a Point Process Model | |
plot.ppm | plot a Fitted Point Process Model | |
redwoodfull | California Redwoods Point Pattern (Entire Dataset) | |
shift.owin | Apply Vector Translation To Window | |
im.object | Class of Images | |
is.marked.ppm | Test Whether A Point Process Model is Marked | |
nearest.raster.point | Find Pixel Nearest to a Given Point | |
ppm.object | Class of Fitted Point Process Models | |
Pairwise | Generic Pairwise Interaction model | |
OrdThresh | Ord's Interaction model | |
MultiStraussHard | The Multitype/Hard Core Strauss Point Process Model | |
complement.owin | Take Complement of a Window | |
StraussHard | The Strauss / Hard Core Point Process Model | |
as.mask | Pixel Image Approximation of a Window | |
longleaf | Longleaf Pines Point Pattern | |
pairwise.family | Pairwise Interaction Process Family | |
stratrand | Stratified random point pattern | |
cells | Biological Cells Point Pattern | |
rmh.ppm | Simulate from a Fitted Point Process Model | |
data.ppm | Extract Original Data from a Fitted Point Process Model | |
Kmeasure | Reduced Second Moment Measure | |
letterR | Window in Shape of Letter R | |
default.dummy | Generate a Default Pattern of Dummy Points | |
bdist.pixels | Distance to Boundary of Window | |
Gmulti | Marked Nearest Neighbour Distance Function | |
LennardJones | The Lennard-Jones Potential | |
ppp.object | Class of Point Patterns | |
as.ppp | Convert Data To Class ppp | |
kmrs | Kaplan-Meier and Reduced Sample Estimator using Histograms | |
fasp.object | Function Arrays for Spatial Patterns | |
is.marked.ppp | Test Whether A Point Pattern is Marked | |
redwood | California Redwoods Point Pattern (Ripley's Subset) | |
rThomas | Simulate Thomas Process | |
rotate | Rotate | |
rpoispp | Generate Poisson Point Pattern | |
Gest | Nearest Neighbour Distance Function G | |
PairPiece | The Piecewise Constant Pairwise Interaction Point Process Model | |
Saturated | Saturated Pairwise Interaction model | |
Fest | Estimate the empty space function F | |
unmark | Remove Marks from a Marked Point Pattern | |
im | Create a Pixel Image Object | |
print.ppp | Print Brief Details of a Point Pattern Dataset | |
print.ppm | Print a Fitted Point Process Model | |
shift.im | Apply Vector Translation To Pixel Image | |
swedishpines | Swedish Pines Point Pattern | |
Gcross | Multitype Nearest Neighbour Distance Function (i-to-j) | |
Geyer | Geyer's Saturation Point Process Model | |
Kest.fft | K-function using FFT | |
affine.ppp | Apply Affine Transformation To Point Pattern | |
affine.owin | Apply Affine Transformation To Window | |
bdist.points | Distance to Boundary of Window | |
inside.owin | Test Whether Points Are Inside A Window | |
pairsat.family | Saturated Pairwise Interaction Point Process Family | |
Gdot | Multitype Nearest Neighbour Distance Function (i-to-any) | |
Softcore | The Soft Core Point Process Model | |
Strauss | The Strauss Point Process Model | |
fitted.ppm | Fitted Conditional Intensity for Point Process Model | |
ganglia | Cat Retinal Ganglia Data | |
mpl | Fit Point Process Model by Maximum Pseudolikelihood | |
centroid.owin | Centroid of a window | |
rMatClust | Simulate Matern Cluster Process | |
gridweights | Compute Quadrature Weights Based on Grid Counts | |
rmh | Simulate point patterns using the Metropolis-Hastings algorithm. | |
simdat | Simulated Point Pattern | |
MultiStrauss | The Multitype Strauss Point Process Model | |
owin.object | Class owin | |
quadscheme | Generate a Quadrature Scheme from a Point Pattern | |
rNeymanScott | Simulate Neyman-Scott Process | |
rMaternII | Simulate Matern Model II | |
quad.object | Class of Quadrature Schemes | |
subset.im | Extract Subset of Image | |
shift.ppp | Apply Vector Translation To Point Pattern | |
harmonic | Basis for Harmonic Functions | |
shift | Apply Vector Translation | |
allstats | Calculate four standard summary functions of a point pattern. | |
identify.ppp | Identify Points in a Point Pattern | |
plot.ppp | plot a Spatial Point Pattern | |
union.quad | Union of Data and Dummy Points | |
ppp | Create a Point Pattern | |
rMaternI | Simulate Matern Model I | |
Ord | Generic Ord Interaction model | |
spatstat.options | Internal Options in Spatstat Package | |
kaplan.meier | Kaplan-Meier Estimator using Histogram Data | |
rmh.default | Simulate Point Process Models using the Metropolis-Hastings Algorithm. | |
markcorr | Mark Correlation Function | |
hamster | Aherne's hamster tumour data | |
summary.ppp | Summary of a Point Pattern Dataset | |
Jest | Estimate the J-function | |
Kdot | Multitype K Function (i-to-any) | |
amacrine | Hughes' Amacrine Cell Data | |
as.rectangle | Window Frame | |
diameter | Diameter of a Window Frame | |
spatstat-internal | Internal spatstat functions | |
plot.fasp | Plot a Function Array | |
Kcross | Multitype K Function (Cross-type) | |
applynbd | Apply Function to Every Neighbourhood in a Point Pattern | |
bramblecanes | Hutchings' Bramble Canes data | |
alltypes | Calculate Statistic for All Types in a Multitype Point Pattern | |
nndist | Nearest neighbour distances | |
rSSI | Simple Sequential Inhibition | |
reduced.sample | Reduced Sample Estimator using Histogram Data | |
ksmooth.ppp | Kernel Smoothed Intensity of Point Pattern | |
is.marked | Test Whether Marks Are Present | |
square | Square Window | |
Jdot | Multitype J Function (i-to-any) | |
Jmulti | Marked J Function | |
Kest | K-function | |
corners | Corners of a rectangle | |
concatxy | Concatenate x,y Coordinate Vectors | |
dirichlet.weights | Compute Quadrature Weights Based on Dirichlet Tessellation | |
ord.family | Ord Interaction Process Family | |
plot.owin | Plot a Spatial Window | |
predict.ppm | Prediction from a Fitted Point Process Model | |
print.owin | Print Brief Details of a Spatial Window | |
subset.ppp | Extract Subset of Point Pattern | |
erode.owin | Erode a Window | |
gridcentres | Rectangular grid of points | |
coef.ppm | Coefficients of Fitted Point Process Model | |
as.owin | Convert Data To Class owin | |
Kmulti | Marked K-Function | |
lansing | Lansing Woods Point Pattern | |
raster.x | Cartesian Coordinates for a Pixel Raster | |
nztrees | New Zealand Trees Point Pattern | |
conspire | Plot Together According to a Formula | |
rotate.owin | Rotate a Window | |
runifpoint | Generate N Uniform Random Points | |
summary.owin | Summary of a Spatial Window | |
owin | Create a Window | |
affine | Apply Affine Transformation | |
plot.quad | plot a Spatial Quadrature Scheme | |
area.owin | Area of a Window | |
quad.ppm | Extract Quadrature Scheme Used to Fit a Point Process Model | |
spokes | Spokes pattern of dummy points | |
superimpose | Superimpose Several Point Patterns | |
ripras | Estimate window from points alone | |
subset.fasp | Extract Subset of Function Array | |
Kinhom | Inhomogeneous K-function | |
demopat | Artificial Data Point Pattern | |
pcf | Pair Correlation Function | |
rotate.ppp | Rotate a Point Pattern | |
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Details
Date | 5 May 2003 |
License | GPL version 2 or newer |
URL | http://www.maths.uwa.edu.au/~adrian/spatstat.html |
depends | base (>= 1.3.0) , mgcv , modreg , R (>= 1.3.0) , sm |
Contributors | Rolf Turner, Adrian Baddeley |
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