spatstat.linnet-internal {spatstat.linnet} | R Documentation |
Internal spatstat.linnet functions
Description
Internal spatstat.linnet functions.
Usage
ApplyConnected(X, Engine, r, ..., rule, auxdata)
DoCountEnds(X, D, toler)
DoCountCrossEnds(X, I, J, DIJ, toler)
FDMKERNEL(lppobj, dtt, dtx, M, nsave, weights,
stepnames, setuponly, verbose)
## S3 method for class 'linfun'
as.linfun(X, ...)
## S3 method for class 'lintess'
as.owin(W, ...)
## S3 method for class 'lppm'
getglmdata(object, ...)
## S3 method for class 'lppm'
getglmfit(object, ...)
## S3 method for class 'lppm'
getglmsubset(object, ...)
## S3 method for class 'lppm'
hasglmfit(object)
default.linnet.tolerance(L)
makeLinnetTolerance(toler)
## S3 method for class 'lintess'
print(x, ...)
## S3 method for class 'summary.linim'
print(x, ...)
## S3 method for class 'summary.linnet'
print(x, ...)
## S3 method for class 'summary.lintess'
print(x, ...)
## S3 method for class 'lintess'
summary(object, ...)
## S3 method for class 'lintess'
nobjects(x)
## S3 method for class 'lintess'
Window(X, ...)
## S3 replacement method for class 'linnet'
Window(X, ..., check=TRUE) <- value
## S3 replacement method for class 'lpp'
Window(X, ..., check=TRUE) <- value
densitypointsLPP(x, sigma, ...,
weights, nsigma, leaveoneout, fast,
fastmethod, floored,
dx, dt, iterMax, verbose, debug)
flatdensityfunlpp(X, ..., disconnect, weights, what)
flatdensityatpointslpp(X, ..., leaveoneout, disconnect, weights, what)
local2lpp(L, seg, tp, X, df.only)
looHeatLPP(U0, Amatrix, npts, niter, nsave,
lixelweight, lixelmap, verbose)
looVoronoiLPP(X)
validate.lpp.coords(X, fatal, context)
## S3 method for class 'lppm'
as.ppm(object)
pointsAlongNetwork(L, delta)
lineardiscEngine(L, x, r, want)
linearEuclidEngine(X, fun, ..., r, reweight, denom,
samplesize, showworking, correction)
linearKengine(X, ..., r, reweight, denom, samplesize,
correction, ratio, showworking)
linearKmulti(X, I, J, r, ..., correction)
linearKmulti.inhom(X, I, J, lambdaI, lambdaJ, r, ..., correction,
normalise, sigma)
linearpcfengine(X, ..., r, reweight, denom, samplesize, correction, ratio)
linearpcfmulti(X, I, J, r, ..., correction)
linearpcfmulti.inhom(X, I, J, lambdaI, lambdaJ, r, ...,
correction, normalise,
sigma, adjust.sigma, bw, adjust.bw)
linearKmultiEngine(X, I, J, ...,
r, reweight, denom, samplesize, correction, showworking)
linearPCFmultiEngine(X, I, J, ...,
r, reweight, denom, samplesize, correction, showworking)
resampleNetworkDataFrame(df, template)
## S3 method for class 'lpp'
resolve.lambda(X, lambda, subset, ...,
update, leaveoneout, everywhere, loo.given, sigma, lambdaname)
sortalongsegment(df)
## S3 method for class 'lppm'
spatialCovariateEvidence(model, covariate, ..., lambdatype,
eps, dimyx, xy, rule.eps,
delta, nd, interpolate, jitter, jitterfactor,
modelname, covname, dataname, subset, clip.predict)
vnnFind(seg, tp, ns, nv, from, to, seglen, huge, tol, kmax)
ldtEngine(nv, ns, from, to, seglen, huge,
coUXord, vnndist, vnnwhich, vnnlab)
resolve.heat.steps(sigma, ..., dx, dt,
niter, iterMax, nsave,
seglengths, maxdegree, AMbound, L,
finespacing, fineNsplit, fineNlixels,
W, eps, dimyx, xy,
allow.adjust, warn.adjust,
verbose, stepnames)
rmaxEuclidean(L, verbose, show)
qkdeEngine(x, sigma, ..., at, what,
leaveoneout, diggle, raw, edge2D, edge,
weights, varcov, positive, shortcut,
precomputed, savecomputed)
## S3 method for class 'lppm'
updateData(model, X, ...)
Math(x, ...)
Ops(e1, e2)
Complex(z)
Summary(..., na.rm = FALSE)
LinimOp(e1, e2, op)
LinimListOp(e1, e2, op)
traceTessLinnet(A, L)
Details
These internal spatstat.linnet functions should not be called directly by the user. Their names and capabilities may change without warning from one version of spatstat.linnet to the next.
Value
The return values of these functions are not documented, and may change without warning.
[Package spatstat.linnet version 3.1-5 Index]