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 linfun
as.linfun(X, ...)
as.lintess(X, ...)
# S3 method for lintess
as.lintess(X, ...)
# S3 method for linnet
as.lintess(X, ...)
# S3 method for linearquadratcount
as.lintess(X, ...)
# S3 method for lintess
affine(X, ...)
# S3 method for lintess
as.owin(W, ...)
# S3 method for linearquadratcount
as.owin(W, ..., fatal)
# S3 method for linearquadratcount
Window(X, ...)
diagLppmEngine(object, ..., type, typename, opt,
sigma, compute.sd, compute.cts,
envelope, nsim, nrank,
rv, oldstyle, splineargs, verbose)
# S3 method for linearquadratcount
domain(X, ...)
# S3 method for lintess
flipxy(X, ...)
# S3 method for lppm
getglmdata(object, ...)
# S3 method for lppm
getglmfit(object, ...)
# S3 method for lppm
getglmsubset(object, ...)
# S3 method for lppm
hasglmfit(object)
default.linnet.tolerance(L)
evaluateNetCovariate(covariate, locations, ...)
evaluateNetCovariateAlongNetwork(covariate, locations, ..., types)
evaluateNetCovariateAtPoints(covariate, locations, ..., allow.column)
exactlppm(X, baseline, ..., subset)
# S3 method for linearquadratcount
intensity(X, ..., fun)
# S3 method for exactlppm
is.poisson(x)
# S3 method for exactlppm
is.stationary(x)
makeLinnetTolerance(toler)
marginalIntegralOfLinim(f, margin)
# S3 method for linearquadratcount
plot(x, ..., main, add, do.plot, textargs)
# S3 method for qqlppm
plot(x, ..., limits, monochrome, limcol)
# S3 method for exactlppm
predict(object, locations,...)
# S3 method for diaglppm
print(x, ...)
# S3 method for exactlppm
print(x, ...)
# S3 method for lintess
print(x, ...)
# S3 method for qqlppm
print(x, ...)
# S3 method for summary.linim
print(x, ...)
# S3 method for summary.linnet
print(x, ...)
# S3 method for summary.lintess
print(x, ...)
# S3 method for lintess
rescale(X, s, unitname)
# S3 method for exactlppm
response(object)
# S3 method for lintess
rotate(X, ...)
# S3 method for lintess
shift(X, ...)
# S3 method for linearquadratcount
shift(X, ...)
# S3 method for lintess
scalardilate(X, f,...)
# S3 method for lintess
summary(object, ...)
# S3 method for lintess
nobjects(x)
# S3 method for lintess
Window(X, ...)
# S3 method for linnet
Window(X, ..., check=TRUE) <- value
# S3 method for 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, metric)
validate.lpp.coords(X, fatal, context)
# S3 method for 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 lpp
resolve.lambda(X, lambda, subset, ...,
update, leaveoneout, everywhere, loo.given, sigma, lambdaname)
sortalongsegment(df)
# S3 method for lppm
spatialCovariateEvidence(model, covariate, ..., lambdatype,
eps, dimyx, xy, rule.eps,
delta, nd, interpolate, jitter, jitterfactor,
modelname, covname, dataname, subset, clip.predict, raster.action)
# S3 method for exactlppm
spatialCovariateEvidence(model, covariate, ...,
lambdatype, interpolate, jitter, jitterfactor,
modelname, covname, dataname, subset, clip.predict, raster.action)
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 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, epsfrac)The return values of these functions are not documented, and may change without warning.
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.