spatstat: Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
空間解析
- CRAN: http://cran.r-project.org/web/packages/spatstat/index.html
- GitHub: https://github.com/spatstat/spatstat
- URL: http://www.spatstat.org
> library(spatstat)
Loading required package: nlme
Attaching package: 'nlme'
The following object is masked from 'package:raster':
getData
The following object is masked from 'package:dplyr':
collapse
spatstat 1.43-0 (nickname: 'Mixed Effects')
For an introduction to spatstat, type 'beginner'
Attaching package: 'spatstat'
The following objects are masked from 'package:raster':
area, rotate, shift
バージョン: 1.43.0
関数名 | 概略 |
---|---|
AreaInter |
The Area Interaction Point Process Model |
BadGey |
Hybrid Geyer Point Process Model |
CDF |
Cumulative Distribution Function From Kernel Density Estimate |
Concom |
The Connected Component Process Model |
DiggleGatesStibbard |
Diggle-Gates-Stibbard Point Process Model |
DiggleGratton |
Diggle-Gratton model |
Emark |
Diagnostics for random marking |
F3est |
Empty Space Function of a Three-Dimensional Point Pattern |
Fest |
Estimate the Empty Space Function or its Hazard Rate |
Fiksel |
The Fiksel Interaction |
Finhom |
Inhomogeneous Empty Space Function |
Frame |
Extract or Change the Containing Rectangle of a Spatial Object |
G3est |
Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern |
Gcom |
Model Compensator of Nearest Neighbour Function |
Gcross |
Multitype Nearest Neighbour Distance Function (i-to-j) |
Gdot |
Multitype Nearest Neighbour Distance Function (i-to-any) |
Gest |
Nearest Neighbour Distance Function G |
Geyer |
Geyer's Saturation Point Process Model |
Gfox |
Foxall's Distance Functions |
Ginhom |
Inhomogeneous Nearest Neighbour Function |
Gmulti |
Marked Nearest Neighbour Distance Function |
Gres |
Residual G Function |
Hardcore |
The Hard Core Point Process Model |
Hest |
Spherical Contact Distribution Function |
HierHard |
The Hierarchical Hard Core Point Process Model |
HierStrauss |
The Hierarchical Strauss Point Process Model |
HierStraussHard |
The Hierarchical Strauss Hard Core Point Process Model |
Hybrid |
Hybrid Interaction Point Process Model |
Iest |
Estimate the I-function |
Jcross |
Multitype J Function (i-to-j) |
Jdot |
Multitype J Function (i-to-any) |
Jest |
Estimate the J-function |
Jinhom |
Inhomogeneous J-function |
Jmulti |
Marked J Function |
K3est |
K-function of a Three-Dimensional Point Pattern |
Kcom |
Model Compensator of K Function |
Kcross |
Multitype K Function (Cross-type) |
Kcross.inhom |
Inhomogeneous Cross K Function |
Kdot |
Multitype K Function (i-to-any) |
Kdot.inhom |
Inhomogeneous Multitype K Dot Function |
Kest |
K-function |
Kest.fft |
K-function using FFT |
Kinhom |
Inhomogeneous K-function |
Kmark |
Mark-Weighted K Function |
Kmeasure |
Reduced Second Moment Measure |
Kmodel |
K Function or Pair Correlation Function of a Point Process Model |
Kmodel.dppm |
K-function or Pair Correlation Function of a Determinantal Point Process Model |
Kmodel.kppm |
K Function or Pair Correlation Function of Cluster Model or Cox model |
Kmodel.ppm |
K Function or Pair Correlation Function of Gibbs Point Process model |
Kmulti |
Marked K-Function |
Kmulti.inhom |
Inhomogeneous Marked K-Function |
Kovesi |
Colour Sequences with Uniform Perceptual Contrast |
Kres |
Residual K Function |
Kscaled |
Locally Scaled K-function |
Ksector |
Sector K-function |
LambertW |
Lambert's W Function |
Lcross |
Multitype L-function (cross-type) |
Lcross.inhom |
Inhomogeneous Cross Type L Function |
Ldot Multitype |
L-function (i-to-any) |
Ldot.inhom |
Inhomogeneous Multitype L Dot Function |
LennardJones |
The Lennard-Jones Potential |
Lest |
L-function |
Linhom |
L-function |
Math.im |
S3 Group Generic methods for images |
Math.linim |
S3 Group Generic Methods for Images on a Linear Network |
MultiHard |
The Multitype Hard Core Point Process Model |
MultiStrauss |
The Multitype Strauss Point Process Model |
MultiStraussHard |
The Multitype/Hard Core Strauss Point Process Model |
Ord |
Generic Ord Interaction model |
OrdThresh |
Ord's Interaction model |
PPversion |
Transform a Function into its P-P or Q-Q Version |
PairPiece |
The Piecewise Constant Pairwise Interaction Point Process Model |
Pairwise |
Generic Pairwise Interaction model |
Penttinen |
Penttinen Interaction |
Poisson |
Poisson Point Process Model |
SatPiece |
Piecewise Constant Saturated Pairwise Interaction Point Process Model |
Saturated |
Saturated Pairwise Interaction model |
Smooth |
Spatial smoothing of data |
Smooth.fv |
Apply Smoothing to Function Values |
Smooth.msr |
Smooth a Signed or Vector-Valued Measure |
Smooth.ppp |
Spatial smoothing of observations at irregular points |
Smoothfun.ppp |
Smooth Interpolation of Marks as a Spatial Function |
Softcore |
The Soft Core Point Process Model |
Strauss |
The Strauss Point Process Model |
StraussHard |
The Strauss / Hard Core Point Process Model |
Triplets |
The Triplet Point Process Model |
Tstat |
Third order summary statistic |
Window |
Extract or Change the Window of a Spatial Object |
Window.ppm |
Extract Window of Spatial Object |
[.anylist |
Extract or Replace Subset of a List of Things |
[.fasp |
Extract Subset of Function Array |
[.fv |
Extract or Replace Subset of Function Values |
[.hyperframe |
Extract or Replace Subset of Hyperframe |
[.im |
Extract Subset of Image |
[.influence.ppm |
Extract Subset of Influence Object |
[.layered |
Extract or Replace Subset of a Layered Object |
[.leverage.ppm |
Extract Subset of Leverage Object |
[.linnet |
Extract Subset of Linear Network |
[.lpp |
Extract Subset of Point Pattern on Linear Network |
[.msr |
Extract Subset of Signed or Vector Measure |
[.owin |
Extract Subset of Window |
[.ppp |
Extract or Replace Subset of Point Pattern |
[.ppx |
Extract Subset of Multidimensional Point Pattern |
[.psp |
Extract Subset of Line Segment Pattern |
[.quad |
Subset of Quadrature Scheme |
[.solist |
Extract or Replace Subset of a List of Spatial Objest |
[.splitppp |
Extract or Replace Sub-Patterns |
[.tess |
Extract or Replace Subset of Tessellation |
[<-.im |
Reset Values in Subset of Image |
[<-.listof |
Extract or Replace Subset of a List of Things |
adaptive.density |
Intensity Estimate of Point Pattern Using Tessellation |
add.texture |
Fill Plot With Texture |
addvar |
Added Variable Plot for Point Process Model |
affine |
Apply Affine Transformation |
affine.im |
Apply Affine Transformation To Pixel Image |
affine.linnet |
Apply Geometrical Transformations to a Linear Network |
affine.lpp |
Apply Geometrical Transformations to Point Pattern on a Linear Network |
affine.owin |
Apply Affine Transformation To Window |
affine.ppp |
Apply Affine Transformation To Point Pattern |
affine.psp |
Apply Affine Transformation To Line Segment Pattern |
affine.tess |
Apply Geometrical Transformation To Tessellation |
allstats |
Calculate four standard summary functions of a point pattern. |
alltypes |
Calculate Summary Statistic for All Types in a Multitype Point Pattern |
amacrine |
Hughes' Amacrine Cell Data |
anemones |
Beadlet Anemones Data |
angles.psp |
Orientation Angles of Line Segments |
anova.lppm |
ANOVA for Fitted Point Process Models on Linear Network |
anova.mppm |
ANOVA for Fitted Multiple Point Process Models |
anova.ppm |
ANOVA for Fitted Point Process Models |
anova.slrm |
Analysis of Deviance for Spatial Logistic Regression Models |
ants |
Harkness-Isham ants' nests data |
anylist |
List of Objects |
append.psp |
Combine Two Line Segment Patterns |
applynbd |
Apply Function to Every Neighbourhood in a Point Pattern |
area.owin |
Area of a Window |
areaGain |
Difference of Disc Areas |
areaLoss |
Difference of Disc Areas |
as.box3 |
Convert Data to Three-Dimensional Box |
as.boxx |
Convert Data to Multi-Dimensional Box |
as.data.frame.hyperframe |
Coerce Hyperframe to Data Frame |
as.data.frame.im |
Convert Pixel Image to Data Frame |
as.data.frame.owin |
Convert Window to Data Frame |
as.data.frame.ppp |
Coerce Point Pattern to a Data Frame |
as.data.frame.psp |
Coerce Line Segment Pattern to a Data Frame |
as.function.fv |
Convert Function Value Table to Function |
as.function.im |
Convert Pixel Image to Function of Coordinates |
as.fv |
Convert Data To Class fv |
as.hyperframe |
Convert Data to Hyperframe |
as.hyperframe.ppx |
Extract coordinates and marks of multidimensional point pattern |
as.im |
Convert to Pixel Image |
as.interact |
Extract Interaction Structure |
as.layered |
Convert Data To Layered Object |
as.linim |
Convert to Pixel Image on Linear Network |
as.linnet.linim |
Extract Linear Network from Data on a Linear Network |
as.linnet.psp |
Convert Line Segment Pattern to Linear Network |
as.lpp |
Convert Data to a Point Pattern on a Linear Network |
as.mask |
Pixel Image Approximation of a Window |
as.mask.psp |
Convert Line Segment Pattern to Binary Pixel Mask |
as.matrix.im |
Convert Pixel Image to Matrix or Array |
as.matrix.owin |
Convert Pixel Image to Matrix |
as.owin |
Convert Data To Class owin |
as.polygonal |
Convert a Window to a Polygonal Window |
as.ppm |
Extract Fitted Point Process Model |
as.ppp |
Convert Data To Class ppp |
as.psp |
Convert Data To Class psp |
as.rectangle |
Window Frame |
as.solist |
Convert List of Two-Dimensional Spatial Objects |
as.tess |
Convert Data To Tessellation |
auc |
Area Under ROC Curve |
austates |
Australian States and Mainland Territories |
bdist.pixels |
Distance to Boundary of Window |
bdist.points |
Distance to Boundary of Window |
bdist.tiles |
Distance to Boundary of Window |
bdspots |
Breakdown Spots in Microelectronic Materials |
beachcolours |
Create Colour Scheme for a Range of Numbers |
beginner |
Print Introduction For Beginners |
begins |
Check Start of Character String |
bei |
Tropical rain forest trees |
berman.test |
Berman's Tests for Point Process Model |
betacells |
Beta Ganglion Cells in Cat Retina |
bind.fv |
Combine Function Value Tables |
blur |
Apply Gaussian Blur to a Pixel Image |
border |
Border Region of a Window |
bounding.box.xy |
Convex Hull of Points |
boundingbox |
Bounding Box of a Window, Image, or Point Pattern |
box3 |
Three-Dimensional Box |
boxx |
Multi-Dimensional Box |
bramblecanes |
Hutchings' Bramble Canes data |
branchlabelfun |
Tree Branch Membership Labelling Function |
bronzefilter |
Bronze gradient filter data |
bw.diggle |
Cross Validated Bandwidth Selection for Kernel Density |
bw.frac |
Bandwidth Selection Based on Window Geometry |
bw.ppl |
Likelihood Cross Validation Bandwidth Selection for Kernel Density |
bw.relrisk |
Cross Validated Bandwidth Selection for Relative Risk Estimation |
bw.scott |
Scott's Rule for Bandwidth Selection for Kernel Density |
bw.smoothppp |
Cross Validated Bandwidth Selection for Spatial Smoothing |
bw.stoyan |
Stoyan's Rule of Thumb for Bandwidth Selection |
by.im |
Apply Function to Image Broken Down by Factor |
by.ppp |
Apply a Function to a Point Pattern Broken Down by Factor |
cauchy.estK |
Fit the Neyman-Scott cluster process with Cauchy kernel |
cauchy.estpcf |
Fit the Neyman-Scott cluster process with Cauchy kernel |
cbind.hyperframe |
Combine Hyperframes by Rows or by Columns |
cdf.test |
Spatial Distribution Test for Point Pattern or Point Process Model |
cdf.test.mppm |
Spatial Distribution Test for Multiple Point Process Model |
cells |
Biological Cells Point Pattern |
centroid.owin |
Centroid of a window |
chicago |
Chicago Street Crime Data |
chop.tess |
Subdivide a Window or Tessellation using a Set of Lines |
chorley |
Chorley-Ribble Cancer Data |
circdensity |
Density Estimation for Circular Data |
circumradius |
Circumradius of a Window |
clarkevans |
Clark and Evans Aggregation Index |
clarkevans.test |
Clark and Evans Test |
clickbox |
Interactively Define a Rectangle |
clickdist |
Interactively Measure Distance |
clickjoin |
Interactively join vertices on a plot |
clickpoly |
Interactively Define a Polygon |
clickppp |
Interactively Add Points |
clip.infline |
Intersect Infinite Straight Lines with a Window |
clmfires |
Castilla-La Mancha Forest Fires |
closepairs |
Close Pairs of Points |
closepairs.pp3 |
Close Pairs of Points in 3 Dimensions |
closing |
Morphological Closing |
clusterfield |
Field of clusters |
clusterfit |
Fit Cluster or Cox Point Process Model via Minimum Contrast |
clusterkernel |
Extract Cluster Offspring Kernel |
clusterradius |
Compute or Extract Effective Range of Cluster Kernel |
clusterset |
Allard-Fraley Estimator of Cluster Feature |
coef.mppm |
Coefficients of Point Process Model Fitted to Multiple Point Patterns |
coef.ppm |
Coefficients of Fitted Point Process Model |
coef.slrm |
Coefficients of Fitted Spatial Logistic Regression Model |
collapse.fv |
Collapse Several Function Tables into One |
colourmap |
Colour Lookup Tables |
colourtools |
Convert and Compare Colours in Different Formats |
commonGrid |
Determine A Common Spatial Domain And Pixel Resolution |
compareFit |
Residual Diagnostics for Multiple Fitted Models |
compatible |
Test Whether Objects Are Compatible |
compatible.fasp |
Test Whether Function Arrays Are Compatible |
compatible.fv |
Test Whether Function Objects Are Compatible |
compatible.im |
Test Whether Pixel Images Are Compatible |
complement.owin |
Take Complement of a Window |
concatxy |
Concatenate x,y Coordinate Vectors |
connected |
Connected components |
connected.ppp |
Connected components of a point pattern |
contour.im |
Contour plot of pixel image |
contour.imlist |
Array of Contour Plots |
convexhull |
Convex Hull |
convexhull.xy |
Convex Hull of Points |
convolve.im |
Convolution of Pixel Images |
coords |
Extract or Change Coordinates of a Spatial or Spatiotemporal Point Pattern |
copper |
Berman-Huntington points and lines data |
copyExampleFiles |
Copy Data Files for Example |
corners |
Corners of a rectangle |
crossdist |
Pairwise distances |
crossdist.default |
Pairwise distances between two different sets of points |
crossdist.lpp |
Pairwise distances between two point patterns on a linear network |
crossdist.pp3 |
Pairwise distances between two different three-dimensional point patterns |
crossdist.ppp |
Pairwise distances between two different point patterns |
crossdist.ppx |
Pairwise Distances Between Two Different Multi-Dimensional Point Patterns |
crossdist.psp |
Pairwise distances between two different line segment patterns |
crossing.psp |
Crossing Points of Two Line Segment Patterns |
cut.im |
Convert Pixel Image from Numeric to Factor |
cut.ppp |
Classify Points in a Point Pattern |
data.ppm |
Extract Original Data from a Fitted Point Process Model |
dclf.progress |
Progress Plot of Test of Spatial Pattern |
dclf.sigtrace |
Significance Trace of Cressie-Loosmore-Ford or Maximum Absolute Deviation Test |
dclf.test |
Diggle-Cressie-Loosmore-Ford and Maximum Absolute Deviation Tests |
default.dummy |
Generate a Default Pattern of Dummy Points |
default.expand |
Default Expansion Rule for Simulation of Model |
default.rmhcontrol |
Set Default Control Parameters for Metropolis-Hastings Algorithm. |
delaunay |
Delaunay Triangulation of Point Pattern |
delaunayDistance |
Distance on Delaunay Triangulation |
delaunayNetwork |
Linear Network of Delaunay Triangulation or Dirichlet Tessellation |
deletebranch |
Delete or Extract a Branch of a Tree |
deltametric |
Delta Metric |
demohyper |
Demonstration Example of Hyperframe of Spatial Data |
demopat |
Artificial Data Point Pattern |
dendrite |
Dendritic Spines Data |
density.lpp |
Kernel Estimate of Intensity on a Linear Network |
density.ppp |
Kernel Smoothed Intensity of Point Pattern |
density.psp |
Kernel Smoothing of Line Segment Pattern |
density.splitppp |
Kernel Smoothed Intensity of Split Point Pattern |
deriv.fv |
Calculate Derivative of Function Values |
detpointprocfamilyfun |
Construct a New Determinantal Point Process Model Family Function |
dfbetas.ppm |
Parameter influence measure |
dg.envelope |
Global Envelopes for Dao-Genton Test |
dg.progress |
Progress Plot of Dao-Genton Test of Spatial Pattern |
dg.sigtrace |
Significance Trace of Dao-Genton Test |
dg.test |
Dao-Genton Adjusted Goodness-Of-Fit Test |
diagnose.ppm |
Diagnostic Plots for Fitted Point Process Model |
diameter |
Diameter of an Object |
diameter.box3 |
Geometrical Calculations for Three-Dimensional Box |
diameter.boxx |
Geometrical Calculations for Multi-Dimensional Box |
diameter.linnet |
Circumradius and Diameter of a Linear Network |
diameter.owin |
Diameter of a Window |
dilated.areas |
Areas of Morphological Dilations |
dilation |
Morphological Dilation |
dim.detpointprocfamily |
Dimension of Determinantal Point Process Model |
dirichlet |
Dirichlet Tessellation of Point Pattern |
dirichletAreas |
Compute Areas of Tiles in Dirichlet Tessellation |
dirichletVertices |
Vertices and Edges of Dirichlet Tessellation |
dirichletWeights |
Compute Quadrature Weights Based on Dirichlet Tessellation |
disc |
Circular Window |
discpartarea |
Area of Part of Disc |
discretise |
Safely Convert Point Pattern Window to Binary Mask |
discs |
Union of Discs |
distcdf |
Distribution Function of Interpoint Distance |
distfun |
Distance Map as a Function |
distfun.lpp |
Distance Map on Linear Network |
distmap |
Distance Map |
distmap.owin |
Distance Map of Window |
distmap.ppp |
Distance Map of Point Pattern |
distmap.psp |
Distance Map of Line Segment Pattern |
dkernel |
Kernel distributions and random generation |
dmixpois |
Mixed Poisson Distribution |
domain |
Extract the Domain of any Spatial Object |
dppBessel |
Bessel Type Determinantal Point Process Model |
dppCauchy |
Generalized Cauchy Determinantal Point Process Model |
dppGauss |
Gaussian Determinantal Point Process Model |
dppMatern |
Whittle-Matern Determinantal Point Process Model |
dppPowerExp |
Power Exponential Spectral Determinantal Point Process Model |
dppapproxkernel |
Approximate Determinantal Point Process Kernel |
dppapproxpcf |
Approximate Pair Correlation Function of Determinantal Point Process Model |
dppeigen |
Internal function calculating eig and index |
dppkernel |
Extract Kernel from Determinantal Point Process Model Object |
dppm |
Fit Determinantal Point Process Model |
dppparbounds |
Parameter Bound for a Determinantal Point Process Model |
dppspecden |
Extract Spectral Density from Determinantal Point Process Model Object |
dppspecdenrange |
Range of Spectral Density of a Determinantal Point Process Model |
dummify |
Convert Data to Numeric Values by Constructing Dummy Variables |
dummy.ppm |
Extract Dummy Points Used to Fit a Point Process Model |
duplicated.ppp |
Determine Duplicated Points in a Spatial Point Pattern |
edge.Ripley |
Ripley's Isotropic Edge Correction |
edge.Trans |
Translation Edge Correction |
edges |
Extract Boundary Edges of a Window. |
edges2triangles |
List Triangles in a Graph |
edges2vees |
List Dihedral Triples in a Graph |
edit.hyperframe |
Invoke Text Editor on Hyperframe |
edit.ppp |
Invoke Text Editor on Spatial Data |
eem |
Exponential Energy Marks |
effectfun |
Compute Fitted Effect of a Spatial Covariate in a Point Process Model |
ellipse |
Elliptical Window. |
emend |
Force Model to be Valid |
emend.ppm |
Force Point Process Model to be Valid |
endpoints.psp |
Endpoints of Line Segment Pattern |
envelope |
Simulation Envelopes of Summary Function |
envelope.envelope |
Recompute Envelopes |
envelope.lpp |
Envelope for Point Patterns on Linear Network |
envelope.pp3 |
Simulation Envelopes of Summary Function for 3D Point Pattern |
eroded.areas |
Areas of Morphological Erosions |
erosion |
Morphological Erosion |
eval.fasp |
Evaluate Expression Involving Function Arrays |
eval.fv |
Evaluate Expression Involving Functions |
eval.im |
Evaluate Expression Involving Pixel Images |
eval.linim |
Evaluate Expression Involving Pixel Images on Linear Network |
ewcdf |
Weighted Empirical Cumulative Distribution Function |
exactMPLEstrauss |
Exact Maximum Pseudolikelihood Estimate for Stationary Strauss Process |
expand.owin |
Apply Expansion Rule |
fardist |
Farthest Distance to Boundary of Window |
fasp.object |
Function Arrays for Spatial Patterns |
finpines |
Pine saplings in Finland. |
fitin.ppm |
Extract the Interaction from a Fitted Point Process Model |
fitted.lppm |
Fitted Intensity for Point Process on Linear Network |
fitted.mppm |
Fitted Conditional Intensity for Multiple Point Process Model |
fitted.ppm |
Fitted Conditional Intensity for Point Process Model |
fitted.slrm |
Fitted Probabilities for Spatial Logistic Regression |
fixef.mppm |
Extract Fixed Effects from Point Process Model |
flipxy |
Exchange X and Y Coordinates |
flu |
Influenza Virus Proteins |
foo |
Foo is Not a Real Name |
formula.fv |
Extract or Change the Plot Formula for a Function Value Table |
formula.ppm |
Model Formulae for Gibbs Point Process Models |
fourierbasis |
Fourier Basis Functions |
fryplot |
Fry Plot of Point Pattern |
funxy |
Spatial Function Class |
fv |
Create a Function Value Table |
fv.object |
Function Value Table |
fvnames |
Abbreviations for Groups of Columns in Function Value Table |
ganglia |
Beta Ganglion Cells in Cat Retina, Old Version |
gauss.hermite |
Gauss-Hermite Quadrature Approximation to Expectation for Normal Distribution |
gordon |
People in Gordon Square |
gorillas |
Gorilla Nesting Sites |
gridcentres |
Rectangular grid of points |
gridweights |
Compute Quadrature Weights Based on Grid Counts |
grow.rectangle |
Add margins to rectangle |
hamster |
Aherne's hamster tumour data |
harmonic |
Basis for Harmonic Functions |
harmonise |
Make Objects Compatible |
harmonise.fv |
Make Function Tables Compatible |
harmonise.im |
Make Pixel Images Compatible |
harmonise.owin |
Make Windows Compatible |
heather |
Diggle's Heather Data |
hextess |
Hexagonal Grid or Tessellation |
hierpair.family |
Hierarchical Pairwise Interaction Process Family |
hist.im |
Histogram of Pixel Values in an Image |
hopskel |
Hopkins-Skellam Test |
humberside |
Humberside Data on Childhood Leukaemia and Lymphoma |
hybrid.family |
Hybrid Interaction Family |
hyperframe |
Hyper Data Frame |
hyytiala |
Scots pines and other trees at Hyytiala |
identify.ppp |
Identify Points in a Point Pattern |
identify.psp |
Identify Segments in a Line Segment Pattern |
idw |
Inverse-distance weighted smoothing of observations at irregular points |
im |
Create a Pixel Image Object |
im.apply |
Apply Function Pixelwise to List of Images |
im.object |
Class of Images |
imcov |
Spatial Covariance of a Pixel Image |
improve.kppm |
Improve Intensity Estimate of Fitted Cluster Point Process Model |
incircle |
Find Largest Circle Inside Window |
increment.fv |
Increments of a Function |
infline |
Infinite Straight Lines |
influence.ppm |
Influence Measure for Spatial Point Process Model |
inforder.family |
Infinite Order Interaction Family |
inside.owin |
Test Whether Points Are Inside A Window |
integral.im |
Integral of a Pixel Image |
integral.linim |
Integral on a Linear Network |
integral.msr |
Integral of a Measure |
intensity |
Intensity of a Dataset or a Model |
intensity.dppm |
Intensity of Determinantal Point Process Model |
intensity.lpp |
Empirical Intensity of Point Pattern on Linear Network |
intensity.ppm |
Intensity of Fitted Point Process Model |
intensity.ppp |
Empirical Intensity of Point Pattern |
intensity.ppx |
Intensity of a Multidimensional Space-Time Point Pattern |
intensity.quadratcount |
Intensity Estimates Using Quadrat Counts |
interp.colourmap |
Interpolate smoothly between specified colours |
interp.im |
Interpolate a Pixel Image |
intersect.owin |
Intersection, Union or Set Subtraction of Windows |
intersect.tess |
Intersection of Two Tessellations |
invoke.symbolmap |
Plot Data Using Graphics Symbol Map |
iplot |
Point and Click Interface for Displaying Spatial Data |
ippm |
Fit Point Process Model Involving Irregular Trend Parameters |
is.convex |
Test Whether a Window is Convex |
is.dppm |
Recognise Fitted Determinantal Point Process Models |
is.empty |
Test Whether An Object Is Empty |
is.hybrid |
Test Whether Object is a Hybrid |
is.im |
Test Whether An Object Is A Pixel Image |
is.lpp |
Test Whether An Object Is A Point Pattern on a Linear Network |
is.marked |
Test Whether Marks Are Present |
is.marked.ppm |
Test Whether A Point Process Model is Marked |
is.marked.ppp |
Test Whether A Point Pattern is Marked |
is.multitype |
Test whether Object is Multitype |
is.multitype.ppm |
Test Whether A Point Process Model is Multitype |
is.multitype.ppp |
Test Whether A Point Pattern is Multitype |
is.owin |
Test Whether An Object Is A Window |
is.ppm |
Test Whether An Object Is A Fitted Point Process Model |
is.ppp |
Test Whether An Object Is A Point Pattern |
is.rectangle |
Determine Type of Window |
is.stationary |
Recognise Stationary and Poisson Point Process Models |
is.subset.owin |
Determine Whether One Window is Contained In Another |
istat |
Point and Click Interface for Exploratory Analysis of Point Pattern |
japanesepines |
Japanese Pines Point Pattern |
kaplan.meier |
Kaplan-Meier Estimator using Histogram Data |
kernel.factor |
Scale factor for density kernel |
km.rs |
Kaplan-Meier and Reduced Sample Estimator using Histograms |
kppm |
Fit Cluster or Cox Point Process Model |
kstest |
Outdated Functions |
lansing |
Lansing Woods Point Pattern |
latest.news |
Print News About Latest Version of Package |
layered |
Create List of Plotting Layers |
layerplotargs |
Extract or Replace the Plot Arguments of a Layered Object |
layout.boxes |
Generate a Row or Column Arrangement of Rectangles. |
lengths.psp |
Lengths of Line Segments |
letterR |
Window in Shape of Letter R |
levelset |
Level Set of a Pixel Image |
leverage.ppm |
Leverage Measure for Spatial Point Process Model |
lgcp.estK |
Fit a Log-Gaussian Cox Point Process by Minimum Contrast |
lgcp.estpcf |
Fit a Log-Gaussian Cox Point Process by Minimum Contrast |
linearK |
Linear K Function |
linearKcross |
Multitype K Function (Cross-type) for Linear Point Pattern |
linearKcross.inhom |
Inhomogeneous multitype K Function (Cross-type) for Linear Point Pattern |
linearKdot |
Multitype K Function (Dot-type) for Linear Point Pattern |
linearKdot.inhom |
Inhomogeneous multitype K Function (Dot-type) for Linear Point Pattern |
linearKinhom |
Inhomogeneous Linear K Function |
lineardisc |
Compute Disc of Given Radius in Linear Network |
linearmarkconnect |
Mark Connection Function for Multitype Point Pattern on Linear Network |
linearmarkequal |
Mark Connection Function for Multitype Point Pattern on Linear Network |
linearpcf |
Linear Pair Correlation Function |
linearpcfcross |
Multitype Pair Correlation Function (Cross-type) for Linear Point Pattern |
linearpcfcross.inhom |
Inhomogeneous Multitype Pair Correlation Function (Cross-type) for Linear Point Pattern |
linearpcfdot |
Multitype Pair Correlation Function (Dot-type) for Linear Point Pattern |
linearpcfdot.inhom |
Inhomogeneous Multitype Pair Correlation Function (Dot-type) for Linear Point Pattern |
linearpcfinhom |
Inhomogeneous Linear Pair Correlation Function |
linfun |
Function on a Linear Network |
linim |
Create Pixel Image on Linear Network |
linnet |
Create a Linear Network |
localK |
Neighbourhood density function |
localKinhom |
Inhomogeneous Neighbourhood Density Function |
localpcf |
Local pair correlation function |
logLik.dppm |
Log Likelihood and AIC for Fitted Determinantal Point Process Model |
logLik.kppm |
Log Likelihood and AIC for Fitted Cox or Cluster Point Process Model |
logLik.mppm |
Log Likelihood for Poisson Point Process Model |
logLik.ppm |
Log Likelihood and AIC for Point Process Model |
logLik.slrm |
Loglikelihood of Spatial Logistic Regression |
lohboot |
Bootstrap Confidence Bands for Summary Function |
longleaf |
Longleaf Pines Point Pattern |
lpp |
Create Point Pattern on Linear Network |
lppm |
Fit Point Process Model to Point Pattern on Linear Network |
lurking |
Lurking variable plot |
lut |
Lookup Tables |
markconnect |
Mark Connection Function |
markcorr |
Mark Correlation Function |
markcrosscorr |
Mark Cross-Correlation Function |
marks |
Marks of a Point Pattern |
marks.psp |
Marks of a Line Segment Pattern |
marks.tess |
Marks of a Tessellation |
markstat |
Summarise Marks in Every Neighbourhood in a Point Pattern |
marktable |
Tabulate Marks in Neighbourhood of Every Point in a Point Pattern |
markvario |
Mark Variogram |
matchingdist |
Distance for a Point Pattern Matching |
matclust.estK |
Fit the Matern Cluster Point Process by Minimum Contrast |
matclust.estpcf |
Fit the Matern Cluster Point Process by Minimum Contrast Using Pair Correlation |
maxnndist |
Compute Minimum or Maximum Nearest-Neighbour Distance |
mean.im |
Maximum, Minimum, Mean, Median, Range or Sum of Pixel Values in an Image |
mergeLevels |
Merge Levels of a Factor |
methods.box3 |
Methods for Three-Dimensional Box |
methods.boxx |
Methods for Multi-Dimensional Box |
methods.dppm |
Methods for Determinantal Point Process Models |
methods.fii |
Methods for Fitted Interactions |
methods.funxy |
Methods for Spatial Functions |
methods.kppm |
Methods for Cluster Point Process Models |
methods.layered |
Methods for Layered Objects |
methods.linfun |
Methods for Functions on Linear Network |
methods.linim |
Methods for Images on a Linear Network |
methods.linnet |
Methods for Linear Networks |
methods.lpp |
Methods for Point Patterns on a Linear Network |
methods.lppm |
Methods for Fitted Point Process Models on a Linear Network |
methods.objsurf |
Methods for Objective Function Surfaces |
methods.pp3 |
Methods for three-dimensional point patterns |
methods.ppx |
Methods for Multidimensional Space-Time Point Patterns |
methods.rho2hat |
Methods for Intensity Functions of Two Spatial Covariates |
methods.rhohat |
Methods for Intensity Functions of Spatial Covariate |
methods.slrm |
Methods for Spatial Logistic Regression Models |
methods.units |
Methods for Units |
midpoints.psp |
Midpoints of Line Segment Pattern |
mincontrast |
Method of Minimum Contrast |
miplot |
Morisita Index Plot |
model.depends |
Identify Covariates Involved in each Model Term |
model.frame.ppm |
Extract the Variables in a Point Process Model |
model.images |
Compute Images of Constructed Covariates |
model.matrix.ppm |
Extract Design Matrix from Point Process Model |
model.matrix.slrm |
Extract Design Matrix from Spatial Logistic Regression Model |
mppm |
Fit Point Process Model to Several Point Patterns |
msr |
Signed or Vector-Valued Measure |
mucosa |
Cells in Gastric Mucosa |
multiplicity.ppp |
Count Multiplicity of Duplicate Points |
murchison |
Murchison gold deposits |
nbfires |
Point Patterns of New Brunswick Forest Fires |
nearest.raster.point |
Find Pixel Nearest to a Given Point |
nearestsegment |
Find Line Segment Nearest to Each Point |
nestsplit |
Nested Split |
nnclean |
Nearest Neighbour Clutter Removal |
nncorr |
Nearest-Neighbour Correlation Indices of Marked Point Pattern |
nncross |
Nearest Neighbours Between Two Patterns |
nncross.lpp |
Nearest Neighbours on a Linear Network |
nncross.pp3 |
Nearest Neighbours Between Two Patterns in 3D |
nndensity.ppp |
Estimate Intensity of Point Pattern Using Nearest Neighbour Distances |
nndist |
Nearest neighbour distances |
nndist.lpp |
Nearest neighbour distances on a linear network |
nndist.pp3 |
Nearest neighbour distances in three dimensions |
nndist.ppx |
Nearest Neighbour Distances in Any Dimensions |
nndist.psp |
Nearest neighbour distances between line segments |
nnfun |
Nearest Neighbour Index Map as a Function |
nnfun.lpp |
Nearest Neighbour Map on Linear Network |
nnmap |
K-th Nearest Point Map |
nnmark |
Mark of Nearest Neighbour |
nnorient |
Nearest Neighbour Orientation Distribution |
nnwhich |
Nearest neighbour |
nnwhich.lpp |
Identify Nearest Neighbours on a Linear Network |
nnwhich.pp3 |
Nearest neighbours in three dimensions |
nnwhich.ppx |
Nearest Neighbours in Any Dimensions |
npfun |
Dummy Function Returns Number of Points |
npoints |
Number of Points in a Point Pattern |
nsegments |
Number of Line Segments in a Line Segment Pattern |
nztrees |
New Zealand Trees Point Pattern |
objsurf |
Objective Function Surface |
opening |
Morphological Opening |
ord.family |
Ord Interaction Process Family |
osteo |
Osteocyte Lacunae Data: Replicated Three-Dimensional Point Patterns |
overlap.owin |
Compute Area of Overlap |
owin |
Create a Window |
owin.object |
Class owin |
padimage |
Pad the Border of a Pixel Image |
pairdist |
Pairwise distances |
pairdist.default |
Pairwise distances |
pairdist.lpp |
Pairwise shortest-path distances between points on a linear network |
pairdist.pp3 |
Pairwise distances in Three Dimensions |
pairdist.ppp |
Pairwise distances |
pairdist.ppx |
Pairwise Distances in Any Dimensions |
pairdist.psp |
Pairwise distances between line segments |
pairorient |
Point Pair Orientation Distribution |
pairs.im |
Scatterplot Matrix for Pixel Images |
pairsat.family |
Saturated Pairwise Interaction Point Process Family |
pairwise.family |
Pairwise Interaction Process Family |
panel.contour |
Panel Plots using Colour Image or Contour Lines |
paracou |
Kimboto trees at Paracou, French Guiana |
parameters |
Extract Model Parameters in Understandable Form |
parres |
Partial Residuals for Point Process Model |
pcf |
Pair Correlation Function |
pcf.fasp |
Pair Correlation Function obtained from array of K functions |
pcf.fv |
Pair Correlation Function obtained from K Function |
pcf.ppp |
Pair Correlation Function of Point Pattern |
pcf3est |
Pair Correlation Function of a Three-Dimensional Point Pattern |
pcfcross |
Multitype pair correlation function (cross-type) |
pcfcross.inhom |
Inhomogeneous Multitype Pair Correlation Function (Cross-Type) |
pcfdot |
Multitype pair correlation function (i-to-any) |
pcfdot.inhom |
Inhomogeneous Multitype Pair Correlation Function (Type-i-To-Any-Type) |
pcfinhom |
Inhomogeneous Pair Correlation Function |
pcfmulti |
Marked pair correlation function |
perimeter |
Perimeter Length of Window |
periodify |
Make Periodic Copies of a Spatial Pattern |
persp.im |
Perspective Plot of Pixel Image |
perspPoints |
Draw Points or Lines on a Surface Viewed in Perspective |
pixelcentres |
Extract Pixel Centres as Point Pattern |
pixellate |
Convert Spatial Object to Pixel Image |
pixellate.owin |
Convert Window to Pixel Image |
pixellate.ppp |
Convert Point Pattern to Pixel Image |
pixellate.psp |
Convert Line Segment Pattern to Pixel Image |
pixelquad |
Quadrature Scheme Based on Pixel Grid |
plot.anylist |
Plot a List of Things |
plot.bermantest |
Plot Result of Berman Test |
plot.cdftest |
Plot a Spatial Distribution Test |
plot.colourmap |
Plot a Colour Map |
plot.dppm |
Plot a fitted determinantal point process |
plot.envelope |
Plot a Simulation Envelope |
plot.fasp |
Plot a Function Array |
plot.fv |
Plot Function Values |
plot.hyperframe |
Plot Entries in a Hyperframe |
plot.im |
Plot a Pixel Image |
plot.imlist |
Plot a List of Images |
plot.influence.ppm |
Plot Influence Measure |
plot.kppm |
Plot a fitted cluster point process |
plot.layered |
Layered Plot |
plot.leverage.ppm |
Plot Leverage Function |
plot.linim |
Plot Pixel Image on Linear Network |
plot.linnet |
Plot a linear network |
plot.listof |
Plot a List of Things |
plot.lpp |
Plot Point Pattern on Linear Network |
plot.lppm |
Plot a Fitted Point Process Model on a Linear Network |
plot.mppm |
plot a Fitted Multiple Point Process Model |
plot.msr |
Plot a Signed or Vector-Valued Measure |
plot.onearrow |
Plot an Arrow |
plot.owin |
Plot a Spatial Window |
plot.plotppm |
Plot a plotppm Object Created by plot.ppm |
plot.pp3 |
Plot a Three-Dimensional Point Pattern |
plot.ppm |
plot a Fitted Point Process Model |
plot.ppp |
plot a Spatial Point Pattern |
plot.psp |
plot a Spatial Line Segment Pattern |
plot.quad |
Plot a Spatial Quadrature Scheme |
plot.quadratcount |
Plot Quadrat Counts |
plot.quadrattest |
Display the result of a quadrat counting test. |
plot.scan.test |
Plot Result of Scan Test |
plot.slrm |
Plot a Fitted Spatial Logistic Regression |
plot.solist |
Plot a List of Spatial Objects |
plot.splitppp |
Plot a List of Point Patterns |
plot.symbolmap |
Plot a Graphics Symbol Map |
plot.tess |
Plot a tessellation |
plot.textstring |
Plot a Text String |
`plot.texturemap | Plot a Texture Map |
plot.yardstick |
Plot a Yardstick or Scale Bar |
pointsOnLines |
Place Points Evenly Along Specified Lines |
ponderosa |
Ponderosa Pine Tree Point Pattern |
pool |
Pool Data |
pool.anylist |
Pool Data from a List of Objects |
pool.envelope |
Pool Data from Several Envelopes |
pool.fasp |
Pool Data from Several Function Arrays |
pool.fv |
Pool Several Functions |
pool.quadrattest |
Pool Several Quadrat Tests |
pool.rat |
Pool Data from Several Ratio Objects |
pp3 |
Three Dimensional Point Pattern |
ppm |
Fit Point Process Model to Data |
ppm.object |
Class of Fitted Point Process Models |
ppm.ppp |
Fit Point Process Model to Point Pattern Data |
ppp |
Create a Point Pattern |
ppp.object |
Class of Point Patterns |
pppdist |
Distance Between Two Point Patterns |
pppmatching |
Create a Point Matching |
pppmatching.object |
Class of Point Matchings |
ppx Multidimensional |
Space-Time Point Pattern |
predict.dppm |
Prediction from a Fitted Determinantal Point Process Model |
predict.kppm |
Prediction from a Fitted Cluster Point Process Model |
predict.lppm |
Predict Point Process Model on Linear Network |
predict.mppm |
Prediction for Fitted Multiple Point Process Model |
predict.ppm |
Prediction from a Fitted Point Process Model |
predict.slrm |
Predicted or Fitted Values from Spatial Logistic Regression |
print.im |
Print Brief Details of an Image |
print.owin |
Print Brief Details of a Spatial Window |
print.ppm |
Print a Fitted Point Process Model |
print.ppp |
Print Brief Details of a Point Pattern Dataset |
print.psp |
Print Brief Details of a Line Segment Pattern Dataset |
print.quad |
Print a Quadrature Scheme |
profilepl |
Profile Maximum Pseudolikelihood or AIC |
progressreport |
Print Progress Reports |
project2segment |
Move Point To Nearest Line |
project2set |
Find Nearest Point in a Region |
psp |
Create a Line Segment Pattern |
psp.object |
Class of Line Segment Patterns |
psst |
Pseudoscore Diagnostic For Fitted Model against General Alternative |
psstA |
Pseudoscore Diagnostic For Fitted Model against Area-Interaction Alternative |
psstG |
Pseudoscore Diagnostic For Fitted Model against Saturation Alternative |
pyramidal |
Pyramidal Neurons in Cingulate Cortex |
qqplot.ppm |
Q-Q Plot of Residuals from Fitted Point Process Model |
quad.object |
Class of Quadrature Schemes |
quad.ppm |
Extract Quadrature Scheme Used to Fit a Point Process Model |
quadrat.test |
Dispersion Test for Spatial Point Pattern Based on Quadrat Counts |
quadrat.test.mppm |
Chi-Squared Test for Multiple Point Process Model Based on Quadrat Counts |
quadrat.test.splitppp |
Dispersion Test of CSR for Split Point Pattern Based on Quadrat Counts |
quadratcount |
Quadrat counting for a point pattern |
quadratresample |
Resample a Point Pattern by Resampling Quadrats |
quadrats |
Divide Region into Quadrats |
quadscheme |
Generate a Quadrature Scheme from a Point Pattern |
quadscheme.logi |
Generate a Logistic Regression Quadrature Scheme from a Point Pattern |
quantess |
Quantile Tessellation |
quantile.density |
Quantiles of a Density Estimate |
quantile.ewcdf |
Quantiles of Weighted Empirical Cumulative Distribution Function |
quantile.im |
Sample Quantiles of Pixel Image |
quasirandom |
Quasirandom Patterns |
rCauchy |
Simulate Neyman-Scott Point Process with Cauchy cluster kernel |
rDGS |
Perfect Simulation of the Diggle-Gates-Stibbard Process |
rDiggleGratton |
Perfect Simulation of the Diggle-Gratton Process |
rGaussPoisson |
Simulate Gauss-Poisson Process |
rHardcore |
Perfect Simulation of the Hardcore Process |
rLGCP |
Simulate Log-Gaussian Cox Process |
rMatClust |
Simulate Matern Cluster Process |
rMaternI |
Simulate Matern Model I |
rMaternII |
Simulate Matern Model II |
rMosaicField |
Mosaic Random Field |
rMosaicSet |
Mosaic Random Set |
rNeymanScott |
Simulate Neyman-Scott Process |
rPoissonCluster |
Simulate Poisson Cluster Process |
rQuasi |
Generate Quasirandom Point Pattern in Given Window |
rSSI |
Simulate Simple Sequential Inhibition |
rStrauss |
Perfect Simulation of the Strauss Process |
rStraussHard |
Perfect Simulation of the Strauss-Hardcore Process |
rThomas |
Simulate Thomas Process |
rVarGamma |
Simulate Neyman-Scott Point Process with Variance Gamma cluster kernel |
ranef.mppm |
Extract Random Effects from Point Process Model |
range.fv |
Range of Function Values |
raster.x |
Cartesian Coordinates for a Pixel Raster |
rat |
Ratio object |
rcell |
Simulate Baddeley-Silverman Cell Process |
rcellnumber |
Generate Random Numbers of Points for Cell Process |
rdpp |
Simulation of a Determinantal Point Process |
reach |
Interaction Distance of a Point Process |
reach.dppm |
Range of Interaction for a Determinantal Point Process Model |
reduced.sample |
Reduced Sample Estimator using Histogram Data |
redwood |
California Redwoods Point Pattern (Ripley's Subset) |
redwoodfull |
California Redwoods Point Pattern (Entire Dataset) |
reflect |
Reflect In Origin |
relevel.im |
Reorder Levels of a Factor-Valued Image or Pattern |
reload.or.compute |
Compute Unless Previously Saved |
relrisk |
Estimate of Spatially-Varying Relative Risk |
relrisk.ppm |
Parametric Estimate of Spatially-Varying Relative Risk |
relrisk.ppp |
Nonparametric Estimate of Spatially-Varying Relative Risk |
rescale |
Convert dataset to another unit of length |
rescale.im |
Convert Pixel Image to Another Unit of Length |
rescale.owin |
Convert Window to Another Unit of Length |
rescale.ppp |
Convert Point Pattern to Another Unit of Length |
rescale.psp |
Convert Line Segment Pattern to Another Unit of Length |
rescue.rectangle |
Convert Window Back To Rectangle |
residuals.dppm |
Residuals for Fitted Determinantal Point Process Model |
residuals.kppm |
Residuals for Fitted Cox or Cluster Point Process Model |
residuals.mppm |
Residuals for Point Process Model Fitted to Multiple Point Patterns |
residuals.ppm |
Residuals for Fitted Point Process Model |
residualspaper |
Data and Code From JRSS Discussion Paper on Residuals |
rgbim |
Create Colour-Valued Pixel Image |
rho2hat |
Smoothed Relative Density of Pairs of Covariate Values |
rhohat |
Smoothing Estimate of Covariate Transformation |
ripras |
Estimate window from points alone |
rjitter |
Random Perturbation of a Point Pattern |
rknn |
Theoretical Distribution of Nearest Neighbour Distance |
rlabel |
Random Re-Labelling of Point Pattern |
rlinegrid |
Generate grid of parallel lines with random displacement |
rmh |
Simulate point patterns using the Metropolis-Hastings algorithm. |
rmh.default |
Simulate Point Process Models using the Metropolis-Hastings Algorithm. |
rmh.ppm |
Simulate from a Fitted Point Process Model |
rmhcontrol |
Set Control Parameters for Metropolis-Hastings Algorithm. |
rmhexpand |
Specify Simulation Window or Expansion Rule |
rmhmodel |
Define Point Process Model for Metropolis-Hastings Simulation. |
rmhmodel.default |
Build Point Process Model for Metropolis-Hastings Simulation. |
rmhmodel.list |
Define Point Process Model for Metropolis-Hastings Simulation. |
rmhmodel.ppm |
Interpret Fitted Model for Metropolis-Hastings Simulation. |
rmhstart |
Determine Initial State for Metropolis-Hastings Simulation. |
rmpoint |
Generate N Random Multitype Points |
rmpoispp |
Generate Multitype Poisson Point Pattern |
rnoise |
Random Pixel Noise |
roc |
Receiver Operating Characteristic |
rose |
Rose Diagram |
rotate |
Rotate |
rotate.im |
Rotate a Pixel Image |
rotate.owin |
Rotate a Window |
rotate.ppp |
Rotate a Point Pattern |
rotate.psp |
Rotate a Line Segment Pattern |
rotmean |
Rotational Average of a Pixel Image |
round.ppp |
Apply Numerical Rounding to Spatial Coordinates |
rounding |
Detect Numerical Rounding |
rpoint |
Generate N Random Points |
rpoisline |
Generate Poisson Random Line Process |
rpoislinetess |
Poisson Line Tessellation |
rpoislpp |
Poisson Point Process on a Linear Network |
rpoispp |
Generate Poisson Point Pattern |
rpoispp3 |
Generate Poisson Point Pattern in Three Dimensions |
rpoisppOnLines |
Generate Poisson Point Pattern on Line Segments |
rpoisppx |
Generate Poisson Point Pattern in Any Dimensions |
rshift |
Random Shift |
rshift.ppp |
Randomly Shift a Point Pattern |
rshift.psp |
Randomly Shift a Line Segment Pattern |
rshift.splitppp |
Randomly Shift a List of Point Patterns |
rstrat |
Simulate Stratified Random Point Pattern |
rsyst |
Simulate systematic random point pattern |
rtemper |
Simulated Annealing or Simulated Tempering for Gibbs Point Processes |
rthin |
Random Thinning |
run.simplepanel |
Run Point-and-Click Interface |
runifdisc |
Generate N Uniform Random Points in a Disc |
runiflpp |
Uniform Random Points on a Linear Network |
runifpoint |
Generate N Uniform Random Points |
runifpoint3 |
Generate N Uniform Random Points in Three Dimensions |
runifpointOnLines |
Generate N Uniform Random Points On Line Segments |
runifpointx |
Generate N Uniform Random Points in Any Dimensions |
scalardilate |
Apply Scalar Dilation |
scaletointerval |
Rescale Data to Lie Between Specified Limits |
scan.test |
Spatial Scan Test |
scanLRTS |
Likelihood Ratio Test Statistic for Scan Test |
scanpp |
Read Point Pattern From Data File |
segregation.test |
Test of Spatial Segregation of Types |
selfcrossing.psp |
Crossing Points in a Line Segment Pattern |
selfcut.psp |
Cut Line Segments Where They Intersect |
sessionLibs |
Print Names and Version Numbers of Libraries Loaded |
setcov |
Set Covariance of a Window |
shapley |
Galaxies in the Shapley Supercluster |
sharpen |
Data Sharpening of Point Pattern |
shift |
Apply Vector Translation |
shift.im |
Apply Vector Translation To Pixel Image |
shift.owin |
Apply Vector Translation To Window |
shift.ppp |
Apply Vector Translation To Point Pattern |
shift.psp |
Apply Vector Translation To Line Segment Pattern |
sidelengths.owin |
Side Lengths of Enclosing Rectangle of a Window |
simba |
Simulated data from a two-group experiment with replication within each group. |
simdat |
Simulated Point Pattern |
simplenet |
Simple Example of Linear Network |
simplepanel |
Simple Point-and-Click Interface Panels |
simplify.owin |
Approximate a Polygon by a Simpler Polygon |
simulate.dppm |
Simulation of Determinantal Point Process Model |
simulate.kppm |
Simulate a Fitted Cluster Point Process Model |
simulate.lppm |
Simulate a Fitted Point Process Model on a Linear Network |
simulate.ppm |
Simulate a Fitted Gibbs Point Process Model |
simulate.slrm |
Simulate a Fitted Spatial Logistic Regression Model |
slrm |
Spatial Logistic Regression |
solapply |
Apply a Function Over a List and Obtain a List of Objects |
solist |
List of Two-Dimensional Spatial Objects |
solutionset |
Evaluate Logical Expression Involving Pixel Images and Return Region Where Expression is True |
spatdim |
Spatial Dimension of a Dataset |
spatialcdf |
Spatial Cumulative Distribution Function |
spatstat-package |
The Spatstat Package |
spatstat.options |
Internal Options in Spatstat Package |
spiders |
Spider Webs on Mortar Lines of a Brick Wall |
split.hyperframe |
Divide Hyperframe Into Subsets and Reassemble |
split.im |
Divide Image Into Sub-images |
split.ppp |
Divide Point Pattern into Sub-patterns |
split.ppx |
Divide Multidimensional Point Pattern into Sub-patterns |
spokes |
Spokes pattern of dummy points |
sporophores |
Sporophores Data |
spruces |
Spruces Point Pattern |
square |
Square Window |
stieltjes |
Compute Integral of Function Against Cumulative Distribution |
stienen |
Stienen Diagram |
stratrand |
Stratified random point pattern |
studpermu.test |
Studentised Permutation Test |
subfits |
Extract List of Individual Point Process Models |
subset.hyperframe |
Subset of Hyperframe Satisfying A Condition |
subset.ppp |
Subset of Point Pattern Satisfying A Condition |
suffstat |
Sufficient Statistic of Point Process Model |
summary.anylist |
Summary of a List of Things |
summary.im |
Summarizing a Pixel Image |
summary.kppm |
Summarizing a Fitted Cox or Cluster Point Process Model |
summary.listof |
Summary of a List of Things |
summary.owin |
Summary of a Spatial Window |
summary.ppm |
Summarizing a Fitted Point Process Model |
summary.ppp |
Summary of a Point Pattern Dataset |
summary.psp |
Summary of a Line Segment Pattern Dataset |
summary.quad |
Summarizing a Quadrature Scheme |
summary.solist |
Summary of a List of Spatial Objects |
summary.splitppp |
Summary of a Split Point Pattern |
sumouter |
Compute Quadratic Forms |
superimpose |
Superimpose Several Geometric Patterns |
superimpose.lpp |
Superimpose Several Point Patterns on Linear Network |
swedishpines |
Swedish Pines Point Pattern |
symbolmap |
Graphics Symbol Map |
tess |
Create a Tessellation |
texturemap |
Texture Map |
textureplot |
Plot Image or Tessellation Using Texture Fill |
thomas.estK |
Fit the Thomas Point Process by Minimum Contrast |
thomas.estpcf |
Fit the Thomas Point Process by Minimum Contrast |
tile.areas |
Compute Areas of Tiles in a Tessellation |
tilenames |
Names of Tiles in a Tessellation |
tiles |
Extract List of Tiles in a Tessellation |
timed |
Record the Computation Time |
transect.im |
Pixel Values Along a Transect |
transmat |
Convert Pixel Array Between Different Conventions |
treebranchlabels |
Label Vertices of a Tree by Branch Membership |
treeprune |
Prune Tree to Given Level |
triangulate.owin |
Decompose Window into Triangles |
trim.rectangle |
Cut margins from rectangle |
triplet.family |
Triplet Interaction Family |
tweak.colourmap |
Change Colour Values in a Colour Map |
union.quad |
Union of Data and Dummy Points |
unique.ppp |
Extract Unique Points from a Spatial Point Pattern |
unitname |
Name for Unit of Length |
unmark |
Remove Marks |
unnormdensity |
Weighted kernel smoother |
update.detpointprocfamily |
Set Parameter Values in a Determinantal Point Process Model |
update.kppm |
Update a Fitted Cluster Point Process Model |
update.ppm |
Update a Fitted Point Process Model |
update.rmhcontrol |
Update Control Parameters of Metropolis-Hastings Algorithm |
update.symbolmap |
Update a Graphics Symbol Map. |
urkiola |
Urkiola Woods Point Pattern |
valid |
Check Whether Point Process Model is Valid |
valid.detpointprocfamily |
Check Validity of a Determinantal Point Process Model |
valid.ppm |
Check Whether Point Process Model is Valid |
varblock |
Estimate Variance of Summary Statistic by Subdivision |
vargamma.estK |
Fit the Neyman-Scott Cluster Point Process with |
Variance |
Gamma kernel |
vargamma.estpcf |
Fit the Neyman-Scott Cluster Point Process with Variance Gamma kernel |
vcov.kppm |
Variance-Covariance Matrix for a Fitted Cluster Point Process Model |
vcov.mppm |
Calculate Variance-Covariance Matrix for Fitted Multiple Point Process Model |
vcov.ppm |
Variance-Covariance Matrix for a Fitted Point Process Model |
vcov.slrm |
Variance-Covariance Matrix for a Fitted Spatial Logistic Regression |
vertices |
Vertices of a Window |
vesicles |
Vesicles Data |
volume |
Volume of an Object |
waka |
Trees in Waka national park |
waterstriders |
Waterstriders data. Three independent replications of a point pattern formed by insects. |
whist |
Weighted Histogram |
will.expand |
Test Expansion Rule |
with.fv |
Evaluate an Expression in a Function Table |
with.hyperframe |
Evaluate an Expression in Each Row of a Hyperframe |
with.msr |
Evaluate Expression Involving Components of a Measure |
yardstick |
Text, Arrow or Scale Bar in a Diagram |
zapsmall.im |
Rounding of Pixel Values |
auc
bei
cells
chorley
> data("chorley")
> chorley %>% {
+ print(class(.))
+ str(., max.level = 2)
+ }
[1] "ppp"
List of 6
$ window :List of 5
..$ type : chr "polygonal"
..$ xrange: num [1:2] 343 366
..$ yrange: num [1:2] 410 432
..$ bdry :List of 1
..$ units :List of 3
.. ..- attr(*, "class")= chr "units"
..- attr(*, "class")= chr "owin"
$ n : int 1036
$ x : num [1:1036] 353 353 349 353 353 ...
$ y : num [1:1036] 428 422 418 421 422 ...
$ markformat: chr "vector"
$ marks : Factor w/ 2 levels "larynx","lung": 1 1 1 1 1 1 1 1 1 1 ...
- attr(*, "class")= chr "ppp"
finpines
hextess
> W <- Window(chorley)
> s <- 0.7
> plot(hextess(W, s))
is.empty
japanesepines
longleaf
mergeLevels
mppm
owin
owinクラスオブジェクトの作成
plot.textstring
> W <- Window(humberside)
> te <- textstring(centroid.owin(W), txt = remoji::sub_emoji("寿司食べたい :sushi:"), cex=2.5)
> plot(layered(W, te), main="")
plot.texturemap
ppp
点パターンの生成
> x <- runif(20)
> y <- runif(20)
> ppp(x, y, c(0,1), c(0,1))# %>% hextess(s = 0.7) %>% plot()
Planar point pattern: 20 points
window: rectangle = [0, 1] x [0, 1] units
slrm
spiders
spruces
swedishpines
urkiola
waka
waterstriders
whist
> # http://ito-hi.blog.so-net.ne.jp/2012-02-14
> set.seed(123)
>
> n <- 24
> x <- rnorm(n, 0, 1)
> y <- rnorm(n, 0, 1)
> xy <- cbind(x, y)
> s <- SpatialPoints(xy)
> coords <- coordinates(xy)
>
> plot(xy)
> #x y座標上にぷろっと
> text(x, y, 1:n, pos = 1)