spatstat.linnet-internal | R Documentation |
Internal spatstat.linnet functions.
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)
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.
The return values of these functions are not documented, and may change without warning.
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