Usage
## S3 method for class 'hyperframe':
[(x, i, j, drop=FALSE, ...)
## S3 method for class 'hyperframe':
[(x, i, j) <- value
## S3 method for class 'hyperframe':
$(x, name)
## S3 method for class 'hyperframe':
$(x, i) <- value
acedist.show(X, Y, n, d, timelag = 0)
acedist.noshow(X, Y, n, d)
adjustthinrange(ur,vstep,vr)
affinexy(X, mat = diag(c(1, 1)), vec = c(0, 0), invert=FALSE)
affinexypolygon(p, mat, vec, detmat)
anycrossing.psp(A,B)
apply23sum(x)
area.xypolygon(polly)
areaGain.diri(u, X, r, ..., W=as.owin(X))
areaGain.grid(u, X, r, ..., W=NULL, ngrid=spatstat.options("ngrid.disc"))
areaLoss.diri(X, r, ..., W=as.owin(X), subset=NULL)
areaLoss.grid(X, r, ..., W=as.owin(X), subset=NULL, ngrid=spatstat.options("ngrid.disc"))
AsymmDistance.psp(X, Y, metric="Hausdorff", method="Fortran")
as.breakpts(...)
## S3 method for class 'fv':
as.data.frame(x, ...)
as.fv(x)
## S3 method for class 'hyperframe':
as.list(x, ...)
## S3 method for class 'scan.test':
as.im(X, \dots)
## S3 method for class 'linim':
as.im(X, \dots)
as.listof(x)
as.units(s)
badprobability(x, NAvalue)
beachcolours(heightrange, sealevel, monochrome, ncolours)
bermantestEngine(model, covariate, which, alternative, ..., modelname, covname, dataname)
bdrylength.xypolygon(polly)
bdry.mask(W)
blankcoefnames(x)
breakpts(val, maxi, even = FALSE, npos = NULL, step = NULL)
breakpts.from.r(r)
bt.frame(Q, trend=~1, interaction=NULL, ..., covariates=NULL,
correction="border", rbord=0, use.gam=FALSE, allcovar=FALSE)
bw.optim(cv, h, iopt, ..., xlab, ylab)
cartesian(pp, markset, fac = TRUE)
cat.factor(..., recursive=FALSE)
cellmiddles(W, nx, ny, npix, gi)
censtimeCDFest(o, cc, d, breaks, ..., KM, RS, HAN, RAW, han.denom, pmax)
checkfields(X,L)
check.finite(x, context, xname)
check.hist.lengths(hist,breaks)
check.named.list(x, nam, context, namopt)
check.named.vector(x, nam, context, namopt)
check.named.thing(x, nam, namopt, xtitle, valid, type, context, fatal)
check.nvector(v, npoints, fatal=TRUE, things="data points", naok=FALSE)
check.nmatrix(m, npoints, fatal=TRUE, things="data points", naok=FALSE, squarematrix=TRUE)
check.1.real(x, context, fatal)
check.testfun(f, f1, X)
clarkevansCalc(X, correction, clipregion, working)
clip.psp(x, window, check=TRUE)
cliprect.psp(x, window)
clippoly.psp(s, window)
closepairs(X,rmax,ordered)
## S3 method for class 'summary.ppm':
coef(object, \dots)
## S3 method for class 'rat':
compatible(A, B, \dots)
complaining(whinge, fatal, value)
compileK(D, r, weights, denom, check)
compilepcf(D, r, weights, denom, check, endcorrect, ...)
crosspairs(X,Y,rmax)
crosspaircounts(X,Y,r)
crossfikselterms(X,Y,r,kappa)
cobble.xy(x, y, f, fatal)
codetime(x)
commasep(x)
conform.imagelist(X, Zlist)
countingweights(id, areas, check = TRUE)
damaged.ppm(object)
default.clipwindow(object, epsilon)
default.n.tiling(X, nd, ntile, npix, verbose)
default.ntile(X)
densitypointsEngine(x, sigma, ...,
weights, edge, varcov,
leaveoneout, diggle, sorted)
diagnose.ppm.engine(object, ..., type="eem", typename, opt,
sigma=NULL, rbord = reach(object), compute.sd=TRUE,
compute.cts=TRUE, rv=NULL, oldstyle=FALSE)
dgsTerms(X, Y, idX, idY, rho)
diggraterms(X, Y, idX, idY, delta, rho)
digital.volume(range, nval, vside)
dilate.owin(...)
## S3 method for class 'fasp':
dim(x)
## S3 method for class 'hyperframe':
dim(x)
## S3 method for class 'im':
dim(x)
## S3 method for class 'msr':
dim(x)
## S3 method for class 'fasp':
dimnames(x)
## S3 method for class 'fasp':
dimnames(x) <- value
## S3 method for class 'msr':
dimnames(x)
distpl(p, l)
distppl(p, l)
distppll(p, l, mintype, method, listit)
distppllmin(p, l, big)
distributecbind(x)
dist2dpath(dist, method="C")
divisors(n)
do.as.im(x, action, ..., W, eps, dimyx, xy, na.replace)
do.call.matched(fun, arglist, funargs, extrargs)
do.iplot(panel)
do.istat(panel)
edge.Ripley(X, r, W, method)
edge.Trans(X, Y, W, exact, paired, trim)
edge.Trans.modif(X, Y, WX, WY, exact, paired, trim)
emptywindow(w)
ensure2vector(x)
envelopeEngine(X, fun, simul,
nsim=99, nrank=1, ...,
verbose=TRUE, clipdata=TRUE,
transform=NULL, global=FALSE, ginterval=NULL,
savefuns=FALSE, savepatterns=FALSE, nsim2=nsim,
VARIANCE=FALSE, nSD=2,
Yname=NULL, maxnerr=nsim, internal=NULL, cl=NULL,
envir.user=envir.user)
## S3 method for class 'matrix':
envelope(Y, ..., rvals, observed, theory, funX,
nsim, nsim2, jsim, jsim.mean,
type, csr, use.theory, nrank, ginterval, nSD,
check, Yname)
equalpairs(U, X, marked=FALSE)
equalpairs.quad(Q)
equals.quad(Q)
equalsfun.quad(Q)
eratosthenes(nmax)
erodemask(w,r,strict)
erode.owin(...)
evalCovar(model, covariate, ...,
dimyx, eps, jitter, modelname, covname, dataname)
evalCovariate(covariate, locations)
evalInteraction(X,P,E,interaction,correction,...,precomputed,savecomputed)
evalInterEngine(X,P,E,interaction,correction,...,precomputed,savecomputed)
even.breaks.owin(w)
evenly.spaced(x, tol)
exactdt(X, ...)
exactPdt(w)
explain.ifnot(expr, context)
## S3 method for class 'slrm':
extractAIC(fit, scale = 0, k = 2, ...)
f3engine(x, y, z, box, vside, range, nval, correction)
f3Cengine(x, y, z, box, vside, rmax, nrval)
fasp(fns, which, formulae, dataname, title, rowNames, colNames)
findCovariate(covname, scope, scopename=NULL)
findcbind(root, depth, maxdepth)
findmarktype(x)
firstfactor(x)
fii(interaction, coefs, Vnames, IsOffset)
fikselterms(U,X,r,kappa,EqualPairs)
fillNA(x, value)
flipxypolygon(p)
forbidNA(x, context, xname)
FormatFaspFormulae(f, argname)
## S3 method for class 'slrm':
formula(x, ...)
fvlabels(x, expand=FALSE)
fvlabels(x) <- value
fvlabelmap(x, dot=TRUE)
fvlegend(object, elang)
fvnames(X, a)
fvnames(X, a) <- value
g3engine(x, y, z, box, rmax, nrval, correction)
g3Cengine(x, y, z, box, rmax, nrval)
gpcmethod(fname, signature)
greatest.common.divisor(n,m)
getdataname(defaultvalue, ..., dataname)
getfields(X, L, fatal = TRUE)
getglmdata(object, drop=FALSE)
getglmfit(object)
getglmsubset(object)
geyercounts(U,X,r,sat,Xcounts,EqualPairs)
GLMpredict(fit, data, coefs, changecoef)
good.names(nama, defaults, suffices)
gridindex(x, y, xrange, yrange, nx, ny)
grid1index(x, xrange, nx)
grow.rectangle(W, xmargin=0, ymargin=xmargin)
handle.r.b.args(r = NULL, breaks = NULL, window, eps = NULL, rmaxdefault)
handle.rshift.args(W, ..., radius, width, height, edge, clip, edgedefault)
ho.engine(model, ..., nsim, nrmh, start, control, verb)
hsvNA(h, s, v, ...)
identical.formulae(x,y)
idorempty(w, r, caller)
implemented.for.K(correction, windowtype, explicit)
inpoint(W)
inside.triangle(x, y, xx, yy)
inside.xypolygon(pts, polly, test01, method)
intersect.ranges(a,b,fatal)
intX.owin(w)
intX.xypolygon(polly)
intY.owin(w)
intY.xypolygon(polly)
is.cadlag(s)
is.data(Q)
is.fv(x)
is.hole.xypolygon(polly)
is.hyperframe(x)
is.infline(x)
is.interact(x)
## S3 method for class 'default':
is.marked(\dots)
## S3 method for class 'psp':
is.marked(X, \dots)
## S3 method for class 'quad':
is.marked(X, na.action="warn", \dots)
is.mask(w)
## S3 method for class 'default':
is.multitype(\dots)
## S3 method for class 'quad':
is.multitype(X, na.action="warn", \dots)
is.parseable(x)
is.pp3(x)
is.ppx(x)
is.prime(n)
is.psp(x)
is.slrm(x)
is.tess(x)
k3engine(x, y, z, box, rmax, nrval, correction)
Kborder.engine(X, rmax, nr, correction, weights, ratio)
Kount(dIJ, bI, b, breaks)
Kwtsum(dIJ, bI, wIJ, b, w, breaks)
Kmulti.inhom(X, I, J, lambdaI=NULL, lambdaJ=NULL, ...,
r=NULL, breaks=NULL,
correction = c("border", "isotropic", "Ripley", "translate") ,
lambdaIJ=NULL, sigma=NULL, varcov=NULL,
Iname = "points satisfying condition I",
Jname = "points satisfying condition J")
Kpcf.kppm(model, what)
killinteraction(model)
km.rs.opt(o, cc, d, breaks, KM, RS)
least.common.multiple(n,m)
## S3 method for class 'im':
levels(x)
## S3 method for class 'im':
levels(x) <- value
licence.polygons()
license.polygons()
linequad(X, Y, ..., eps, nd)
linearKengine(X, ..., r, reweight, denom, correction, showworking)
linearpcfengine(X, ..., r, reweight, denom, correction)
listof(...)
localKengine(X, ..., wantL, lambda, correction, verbose, rvalue)
localpcfengine(X, ..., delta, rmax, nr, stoyan, lambda)
localpcfmatrix(X, i, ..., lambda, delta, rmax, nr, stoyan)
paste.expr(x)
## S3 method for class 'localpcfmatrix':
print(x, \dots)
## S3 method for class 'localpcfmatrix':
plot(x, \dots)
## S3 method for class 'localpcfmatrix':
[(x, i, ...)
lookup.im(Z, x, y, naok, strict)
majorminorversion(v)
make.even.breaks(bmax, npos, bstep)
make.parseable(x)
makeunits(sing, plur, mul)
markappend(...)
markcbind(...)
markformat(x)
## S3 method for class 'ppp':
markformat(x)
## S3 method for class 'psp':
markformat(x)
## S3 method for class 'default':
markformat(x)
mark.scale.default(marx, w, markscale=NULL, maxsize=NULL)
markspace.integral(X)
## S3 method for class 'default':
marks(x, \dots)
## S3 method for class 'quad':
marks(x, dfok=FALSE, \dots)
markappendop(x, y)
marksubset(x, index, format)
marksubsetop(x, i)
markreplicateop(x, n)
mask2df(w)
matcolall(x)
matcolany(x)
matcolsum(x)
matrixsample(mat, newdim, phase, scale, na.value)
matrowall(x)
matrowany(x)
matrowsum(x)
maxflow(costm)
meanlistfv(z)
meanX.owin(w)
meanY.owin(w)
## S3 method for class 'slrm':
model.matrix(object, ..., keepNA = TRUE)
model.se.image(fit, W, ..., what)
mpl.engine(Q, trend, interaction, ..., covariates, covfunargs, correction,
rbord, use.gam, gcontrol, famille,
forcefit, nd, allcovar, callstring, precomputed, savecomputed, preponly)
mpl.get.covariates(covariates, locations, type, covfunargs)
mpl.prepare(Q, X, P, trend, interaction, covariates,
want.trend, want.inter, correction, rbord, Pname,
callstring, ..., covfunargs, allcovar, precomputed, savecomputed,
vnamebase, vnameprefix)
MultiPair.checkmatrix(mat, n, matname, naok, zerook)
multiply.only.finite.entries(x, a)
na.handle.im(X, na.replace)
## S3 method for class 'hyperframe':
names(x)
## S3 method for class 'hyperframe':
names(x) <- value
nearest.pixel(x, y, im)
nearest.valid.pixel(x, y, im)
newstyle.coeff.handling(object)
nncleanEngine(kthNND, k, d, ..., tol, plothist, verbose, maxit)
nndcumfun(X, ..., r)
no.trend.ppm(x)
nobjects(x)
## S3 method for class 'ppp':
nobjects(x)
## S3 method for class 'ppx':
nobjects(x)
## S3 method for class 'psp':
nobjects(x)
n.quad(Q)
numalign(i, nmax, zero)
numeric.columns(M, logical, others)
nzpaste(..., sep, collapse)
offsetsinformula(x)
onecolumn(m)
ordinal(k)
outdated.interact(object)
overlap.owin(A,B)
overlap.trapezium(xa, ya, xb, yb, verb = FALSE)
overlap.xypolygon(P, Q)
oversize.quad(Q, ..., nU, nX)
owinpolycheck(W, verbose=TRUE)
owinpoly2mask(w, rasta, check=TRUE)
## S3 method for class 'listof':
pairs(\dots, plot=TRUE)
param.quad(Q)
paren(x, type)
partialModelMatrix(X,D,model,callstring,...)
pcf3engine(x, y, z, box, rmax, nrval, correction, delta)
pcfmulti.inhom(X, I, J, lambdaI = NULL, lambdaJ = NULL, ...,
r = NULL, breaks = NULL,
kernel = "epanechnikov", bw = NULL, stoyan = 0.15,
correction = c("translate", "Ripley"),
sigma = NULL, varcov = NULL,
Iname = "points satisfying condition I",
Jname = "points satisfying condition J")
pickoption(what="option", key, keymap, ...,
exact=FALSE, list.on.err=TRUE, die=TRUE, multi=FALSE)
ploterodewin(W1, W2, col.edge, col.inside, ...)
ploterodeimage(W, Z, ..., Wcol, rangeZ, colsZ)
## S3 method for class 'barplotdata':
plot(x, \dots)
## S3 method for class 'bw.optim':
plot(x, \dots, add)
## S3 method for class 'fii':
plot(x, \dots)
## S3 method for class 'minconfit':
plot(x, \dots)
## S3 method for class 'pppmatching':
plot(x, addmatch = NULL, main = NULL, \dots)
## S3 method for class 'plotpairsim':
plot(x, \dots)
## S3 method for class 'profilepl':
plot(x, \dots, add=FALSE, main=NULL, tag=TRUE, coeff=NULL, xvariable=NULL)
## S3 method for class 'qqppm':
plot(x, \dots, limits=TRUE, monochrome=FALSE,
limcol=if(monochrome) "black" else "red")
## S3 method for class 'quadratcount':
plot(x, \dots, add, entries, dx, dy, show.tiles)
## S3 method for class 'quadrattest':
plot(x, \dots)
## S3 method for class 'scan.test':
plot(x, \dots, do.window)
polynom(x, ...)
ppllengine(X, Y, action="project", check=FALSE)
ppmCovariates(model)
ppm.influence(fit,
what = c("leverage","influence","dfbetas","derivatives"),
..., iScore = NULL, iHessian = NULL, iArgs=list(), drop = FALSE,
method=c("C", "interpreted"))
pppdist.mat(X, Y, cutoff = 1, q = 1, matching = TRUE, precision = 9, approximation = 10)
pppdist.prohorov(X, Y, n, dfix, type, cutoff = 1, matching = TRUE, ccode = TRUE, precision = 9, approximation = 10)
prange(x)
prefixfv(x, tagprefix, descprefix, lablprefix, whichtags)
primefactors(n, prmax)
## S3 method for class 'bt.frame':
print(x, \dots)
## S3 method for class 'bw.optim':
print(x, \dots)
## S3 method for class 'colourmap':
print(x, \dots)
## S3 method for class 'diagppm':
print(x, \dots)
## S3 method for class 'envelope':
print(x, \dots)
## S3 method for class 'fasp':
print(x, \dots)
## S3 method for class 'fii':
print(x, \dots)
## S3 method for class 'fv':
print(x, \dots)
## S3 method for class 'hyperframe':
print(x, ...)
## S3 method for class 'interact':
print(x, \dots, family=TRUE, brief=FALSE)
## S3 method for class 'isf':
print(x, \dots)
## S3 method for class 'layered':
print(x, \dots)
## S3 method for class 'linim':
print(x, \dots)
## S3 method for class 'lut':
print(x, \dots)
## S3 method for class 'minconfit':
print(x, \dots)
## S3 method for class 'msr':
print(x, \dots)
## S3 method for class 'plotppm':
print(x, \dots)
## S3 method for class 'plotpairsim':
print(x, \dots)
## S3 method for class 'pppmatching':
print(x, \dots)
## S3 method for class 'profilepl':
print(x, \dots)
## S3 method for class 'quadrattest':
print(x, \dots)
## S3 method for class 'qqppm':
print(x, \dots)
## S3 method for class 'rat':
print(x, \dots)
## S3 method for class 'rmhcontrol':
print(x, \dots)
## S3 method for class 'rmhmodel':
print(x, \dots)
## S3 method for class 'rmhstart':
print(x, \dots)
## S3 method for class 'rmhInfoList':
print(x, \dots)
## S3 method for class 'slrm':
print(x, ...)
## S3 method for class 'splitppp':
print(x, \dots)
## S3 method for class 'summary.fii':
print(x, \dots)
## S3 method for class 'summary.hyperframe':
print(x, ...)
## S3 method for class 'summary.listof':
print(x, \dots)
## S3 method for class 'summary.owin':
print(x, \dots)
## S3 method for class 'summary.ppp':
print(x, \dots, dp=3)
## S3 method for class 'summary.psp':
print(x, \dots)
## S3 method for class 'summary.splitppp':
print(x, \dots)
## S3 method for class 'summary.units':
print(x, \dots)
## S3 method for class 'tess':
print(x, \dots, brief=FALSE)
prolongseq(x, newrange)
quad(data, dummy, w, param)
rectquadrat.breaks(xr, yr, nx = 5, ny = nx, xbreaks = NULL, ybreaks = NULL)
rectquadrat.countEngine(x, y, xbreaks, ybreaks, weights)
rgbNA(red, green, blue, ...)
rhs.of.formula(x)
quadrat.testEngine(X, nx, ny, ..., Xcount, xbreaks, ybreaks, tess=NULL, fit=NULL, Xname=NULL, fitname=NULL)
quadscheme.replicated(data, dummy, method = "grid", ...)
quadscheme.spatial(data, dummy, method = "grid", ...)
pointgrid(W, ngrid)
rastersample(X, Y)
rasterx.im(x)
rastery.im(x)
## S3 method for class 'fii':
reach(x, \dots, epsilon)
rebadge.fv(x, new.ylab, new.fname, tags, new.desc, new.labl, new.yexp,
new.dotnames, new.preferred, new.formula, new.tags)
rebound(x, rect)
## S3 method for class 'im':
rebound(x, rect)
## S3 method for class 'ppp':
rebound(x, rect)
## S3 method for class 'psp':
rebound(x, rect)
## S3 method for class 'owin':
rebound(x, rect)
reconcile.fv(...)
repair.old.factor.image(x)
reincarnate.interact(object)
resid4plot(RES, plot.neg="image", plot.smooth="imagecontour",
spacing=0.1, srange=NULL,monochrome=FALSE, main=NULL, ...)
resid1plot(RES, opt, plot.neg="image", plot.smooth="imagecontour",
srange=NULL, monochrome=FALSE, main=NULL, ...)
resid1panel(observedX, observedV,
theoreticalX, theoreticalV, theoreticalSD, xlab,ylab, ...)
resolve.defaults(..., .StripNull=FALSE)
resolve.2D.kernel(..., sigma, varcov, x, mindist, adjust, bwfun)
restrict.mask(M, W)
reverse.xypolygon(p, adjust=FALSE)
revcumsum(x)
rmax.rule(fun, W, lambda)
rotxy(X, angle = pi/2)
rotxypolygon(p, angle = pi/2)
rmhResolveControl(control, model)
rmhResolveExpansion(win, control, imagelist, itype)
rmhResolveTypes(model, start, control)
## S3 method for class 'rmhcontrol':
rmhcontrol(\dots)
## S3 method for class 'list':
rmhcontrol(\dots)
rmhEngine(InfoList, ..., verbose, track, kitchensink, preponly)
## S3 method for class 'rmhmodel':
rmhmodel(model, \dots)
## S3 method for class 'rmhstart':
rmhstart(start, \dots)
## S3 method for class 'list':
rmhstart(start, \dots)
rmpoint.I.allim(n, f, types)
## S3 method for class 'hyperframe':
row.names(x)
## S3 method for class 'hyperframe':
row.names(x) <- value
rpoint.multi(n, f, fmax=NULL, marks = NULL, win = unit.square(), giveup = 1000, verbose = FALSE)
runifpoispp(lambda, win = owin(c(0, 1), c(0, 1)))
runifpoisppOnLines(lambda, L)
runifrect(n, win = owin(c(0, 1), c(0, 1)))
safelookup(Z, X, factor, warn)
samefunction(f, g)
scanmeasure(X, ...)
## S3 method for class 'ppp':
scanmeasure(X, r, \dots)
## S3 method for class 'im':
scanmeasure(X, r, \dots)
scanPoisLRTS(nZ, nG, muZ, muG, alternative)
scanBinomLRTS(nZ, nG, muZ, muG, alternative)
scanLRTS(X, r, ..., method, baseline, case, alternative)
second.moment.calc(x, sigma=NULL, edge=TRUE, what="Kmeasure", debug=FALSE,
..., varcov=NULL, expand=FALSE)
second.moment.engine(x, sigma=NULL, edge=TRUE, what="Kmeasure", debug=FALSE,
..., obswin=as.owin(x), varcov=NULL, npts=NULL)
sensiblevarname(guess, fallback, maxlen)
sewpcf(d, w, denargs, lambda2area)
sewsmod(d, ff, wt, Ef, rvals, method="smrep", ..., nwtsteps=500)
shiftxy(X, vec = c(0, 0))
shiftxypolygon(p, vec = c(0, 0))
simplify.xypolygon(p, dmin)
simulrecipe(type, expr, envir, csr, pois)
singlestring(s, coll)
slr.prepare(CallInfo, envir, data, dataAtPoints, splitby)
slrAssemblePixelData(Y, Yname, W, covimages, dataAtPoints, pixelarea)
smoothpointsEngine(x, values, sigma, ...,
weights, varcov, leaveoneout, sorted)
## S3 method for class 'im':
sort(x, \dots)
spatstat.rawdata.location(...)
spatialCDFframe(model, covariate, ...)
spatialCDFtest(model, covariate, test, ..., dimyx, eps, jitter, modelname, covname, dataname)
sphere.volume(range, nval = 10)
sp.foundclass(cname, inlist, formalname, argsgiven)
sp.foundclasses(cnames, inlist, formalname, argsgiven)
stratrand(window, nx, ny, k = 1)
strausscounts(U,X,r,EqualPairs)
suffloc(object)
suffstat.generic(model, X, callstring)
suffstat.poisson(model, X, callstring)
## S3 method for class 'envelope':
summary(object,\dots)
## S3 method for class 'fii':
summary(object,\dots)
## S3 method for class 'hyperframe':
summary(object, ..., brief=FALSE)
## S3 method for class 'profilepl':
summary(object, \dots)
## S3 method for class 'pppmatching':
summary(object, \dots)
## S3 method for class 'ppx':
summary(object, \dots)
superimposeMarks(arglist, nobj)
sympoly(x, y, n)
## S3 method for class 'slrm':
terms(x, ...)
termsinformula(x)
test.crossing.psp(A,B)
test.selfcrossing.psp(A)
tilecentroids(W, nx, ny)
tilenames(x)
trianglediameters(iedge, jedge, edgelength, ..., nvert, check)
trim.mask(M, R, tolerant)
tweak.fv.entry(x, current.tag, new.labl=NULL, new.desc=NULL, new.tag=NULL)
## S3 method for class 'default':
unitname(x)
## S3 method for class 'default':
unitname(x) <- value
## S3 method for class 'interact':
update(object, \dots)
## S3 method for class 'slrm':
update(object, ..., evaluate = TRUE, env = parent.frame())
validradius(r, caller)
validate.mask(w, fatal=TRUE)
validate.quad(Q, fatal, repair, announce)
validposint(n, caller, fatal)
vanilla.fv(x)
variablesinformula(x)
## S3 method for class 'slrm':
vcov(object, ...)
verbalogic(x, op)
versionstring.interact(object)
versionstring.ppm(object)
versionstring.spatstat()
verifyclass(X, C, N = deparse(substitute(X)), fatal = TRUE)
verify.xypolygon(p, fatal=TRUE)
warn.ignored.args(..., context)
## S3 method for class 'msr':
with(data, expr, \dots)
w.quad(Q)
x.quad(Q)
y.quad(Q)
## S3 method for class 'im':
xtfrm(x)
xypolyselfint(p, eps, proper, yesorno, checkinternal)
xypolygon2psp(p, w, check)