Usage
## S3 method for class 'splitppx':
[(x, \dots)
## S3 method for class 'splitppx':
[(x, \dots) <- value
## S3 method for class 'diagramobj':
[(x, \dots)
acedist.show(X, Y, n, d, timelag)
acedist.noshow(X, Y, n, d)
active.interactions(object)
adjustthinrange(ur,vstep,vr)
affinexy(X, mat, vec, invert)
affinexypolygon(p, mat, vec, detmat)
ang2rad(ang, unit, start, clockwise)
anycrossing.psp(A,B)
apply23sum(x)
applytolayers(L, FUN, ...)
applyPolyclipArgs(x, p)
Area.xypolygon(polly)
areadelta2(X, r, ...)
areaGain.diri(u, X, r, ..., W)
areaGain.grid(u, X, r, ..., W, ngrid)
areaLoss.diri(X, r, ..., W, subset)
areaLoss.grid(X, r, ..., W, subset,
method = c("count", "distmap"),
ngrid = spatstat.options("ngrid.disc"),
exact = FALSE)
articlebeforenumber(k)
assemble.plot.objects(xlim, ylim, ..., lines, polygon)
AsymmDistance.psp(X, Y, metric, method)
as.breakpts(...)
## S3 method for class 'units':
as.character(x, \dots)
## S3 method for class 'fv':
as.data.frame(x, \dots)
## S3 method for class 'bw.optim':
as.data.frame(x, \dots)
## S3 method for class 'im':
as.double(x, \dots)
## S3 method for class 'hyperframe':
as.list(x, \dots)
as.listof(x)
as.units(s)
as2vector(x)
asNumericMatrix(x)
augment.msr(x, ..., sigma)
badprobability(x, NAvalue)
bbEngine(...)
bermantestEngine(model, covariate, which, alternative, ..., modelname, covname, dataname)
bdrylength.xypolygon(polly)
bdry.mask(W)
bibliotheque(nom, dont)
bind.ratfv(x, numerator, denominator, labl, desc, preferred, ratio)
blankcoefnames(x)
blockdiagmatrix(...)
blockdiagarray(...)
bounding.box3(...)
break.holes(x, splitby, depth, maxdepth)
breakpts(val, maxi, even = FALSE, npos = NULL, step = NULL)
breakpts.from.r(r)
bt.frame(Q, trend, interaction, ..., covariates,
correction, rbord, use.gam, allcovar)
bw.optim(cv, h, iopt, ..., cvname, hname, criterion)
can.be.formula(x)
cannot.update(...)
cartesian(pp, markset, fac = TRUE)
cat.factor(..., recursive=FALSE)
cellmiddles(W, nx, ny, npix, distances)
censtimeCDFest(o, cc, d, breaks, ...,
KM, RS, HAN, RAW, han.denom, tt, pmax)
change.default.expand(x, newdefault)
checkbigmatrix(n, m, fatal, silent)
checkfields(X,L)
check.finite(x, context, xname, fatal, usergiven)
check.hist.lengths(hist,breaks)
check.in.range(x, r, fatal)
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, things, naok, warn)
check.nmatrix(m, npoints, fatal, things, naok, squarematrix, matchto, warn)
check.1.integer(x, context, fatal)
check.1.real(x, context, fatal)
check.range(x, fatal)
check.rpanel()
check.testfun(f, f1, X)
choptext(..., prefix)
circticks(R, at, unit, start, clockwise, labels)
clarkevansCalc(X, correction, clipregion, working)
clip.psp(x, window, check=TRUE)
cliprect.psp(x, window)
clippoly.psp(s, window)
closethresh(X,R,S,ordered)
## S3 method for class 'summary.kppm':
coef(object, \dots)
## S3 method for class 'summary.ppm':
coef(object, \dots)
## S3 method for class 'vblogit':
coef(object, \dots)
coerce.marks.numeric(X, warn)
## S3 method for class 'rat':
compatible(A, B, \dots)
complaining(whinge, fatal, value)
compileCDF(D, B, r, ..., han.denom, check)
compileK(D, r, weights, denom, check, ratio, fname)
compilepcf(D, r, weights, denom, check, endcorrect, ..., fname)
conform.ratfv(x)
crosspairquad(Q,rmax,what)
cobble.xy(x, y, f, fatal, ...)
codetime(x, hms, what)
col.args.to.grey(x)
colouroutputs(x)
colouroutputs(x) <- value
commasep(x, join, flatten)
commonPolyclipArgs(..., p)
conform.imagelist(X, Zlist)
countingweights(id, areas, check = TRUE)
CressieReadStatistic(OBS,EXP,lambda)
CressieReadSymbol(lambda)
CressieReadName(lambda)
damaged.ppm(object)
data.mppm(x)
datagen.runifpointOnLines(n, L)
datagen.runifpoisppOnLines(lambda, L)
datagen.rpoisppOnLines(lambda, L, lmax, ..., check)
default.clipwindow(object, epsilon)
default.n.tiling(X, nd, ntile, npix, eps, random, quasi, verbose)
default.ntile(X)
deltasuffstat(model, ..., restrict, dataonly, force)
dflt.redraw(button, name, env)
densitycrossEngine(Xdata, Xquery, sigma, ...,
weights, edge, varcov,
diggle, sorted)
densitypointsEngine(x, sigma, ...,
weights, edge, varcov,
leaveoneout, diggle, sorted, spill)
diagnose.ppm.engine(object, ..., type, typename, opt,
sigma, rbord, compute.sd, compute.cts,
envelope, nsim, nrank,
rv, oldstyle, splineargs, verbose)
diagramobj(X, ...)
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 'owin':
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, matchfirst, sieve, skipargs)
do.call.plotfun(fun, arglist, ...)
do.call.without(fun, ..., avoid)
do.istat(panel)
doMultiStraussHard(iradii, hradii, types)
dotexpr.to.call(expr, dot, evaluator)
dropifsingle(x)
dround(x)
emptywindow(w)
ensure2vector(x)
ensure3Darray(x)
envelopeEngine(X, fun, simul,
nsim, nrank, ...,
verbose, clipdata,
transform, global, ginterval, use.theory,
alternative,
savefuns, savepatterns, saveresultof,
weights,
nsim2, VARIANCE, nSD,
Yname, maxnerr, internal, cl,
envir.user, expected.arg, do.pwrong)
envelopeProgressData(X, fun, ..., exponent, normalize, deflate)
envelopeTest(X, ..., exponent, alternative,
rinterval, use.theo, tie.rule,
save.envelope, savefuns, savepatterns,
Xname, verbose, internal)
## S3 method for class 'matrix':
envelope(Y, \dots, rvals, observed, theory, funX,
nsim, nsim2, jsim, jsim.mean,
type, alternative, csr, use.theory, nrank, ginterval, nSD,
savefuns, check, Yname, do.pwrong, weights, precomputed)
equalpairs(U, X, marked=FALSE)
equalpairs.quad(Q)
equals.quad(Q)
equalsfun.quad(Q)
eratosthenes(nmax, startset)
erodemask(w,r,strict)
erode.owin(...)
evalCovar(model, covariate, ...)
## S3 method for class 'ppm':
evalCovar(model, covariate, \dots, lambdatype,
dimyx, eps, jitter, modelname, covname, dataname)
## S3 method for class 'lppm':
evalCovar(model, covariate, \dots, lambdatype,
eps, nd, jitter, modelname, covname, dataname)
evalCovariate(covariate, locations)
evalInteraction(X,P,E,interaction,correction,...,precomputed,savecomputed)
evalInterEngine(X,P,E,interaction,correction,...,
Reach,precomputed,savecomputed)
evalPairPotential(X,P,E,pairpot,potpars,R)
even.breaks.owin(w)
evenly.spaced(x, tol)
exactdt(X, ...)
exactPdt(w)
exhibitStringList(prefix, strings)
expand.polynom(f)
expandSpecialLists(x, special)
expandwinPerfect(W, expand, amount)
explain.ifnot(expr, context)
## S3 method for class 'slrm':
extractAIC(fit, scale = 0, k = 2, \dots)
extractAtomicQtests(x)
fakecallstring(fname, parlist)
fakemaintitle(bb, main, ...)
## S3 method for class 'vblogit':
family(object, \dots)
fave.order(x)
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, checkfv)
fillseq(x)
findbestlegendpos(...)
findCovariate(covname, scope, scopename=NULL)
findcbind(root, depth, maxdepth)
findfirstfactor(x)
firstfactor(x)
fii(interaction, coefs, Vnames, IsOffset)
fillNA(x, value)
flat.deparse(x)
flatfname(x)
flipxypolygon(p)
fontify(x, font)
forbidNA(x, context, xname, fatal, usergiven)
forbid.logi(object)
FormatFaspFormulae(f, argname)
fvexprmap(x)
fvlabels(x, expand=FALSE)
fvlabels(x) <- value
fvlabelmap(x, dot=TRUE)
fvlegend(object, elang)
g3engine(x, y, z, box, rmax, nrval, correction)
g3Cengine(x, y, z, box, rmax, nrval)
greatest.common.divisor(n,m)
getdataname(defaultvalue, ..., dataname)
getdataobjects(nama, envir, datalist, fatal)
getfields(X, L, fatal = TRUE)
getglmdata(object, drop=FALSE)
getglmfit(object)
getglmsubset(object)
getlambda.lpp(lambda, X, ..., update)
getlastshift(X)
getppmdatasubset(object)
getppmOriginalCovariates(object)
getSpatstatVariable(name)
getSumFun(abbreviation, classname, ismarked, fatal)
geyercounts(U,X,r,sat,Xcounts,EqualPairs)
geyerdelta2(X,r,sat)
GLMpredict(fit, data, coefs, changecoef)
good.names(nama, defaults, suffices)
good.correction.K(X)
graphicsPars(key)
gridindex(x, y, xrange, yrange, nx, ny)
grid1index(x, xrange, nx)
grow.mask(M, xmargin=0, ymargin=xmargin)
gsubdot(replacement, x)
HermiteCoefs(order)
handle.r.b.args(r = NULL, breaks = NULL, window, pixeps = NULL, rmaxdefault)
handle.rshift.args(W, ..., radius, width, height, edge, clip,
edgedefault)
## S3 method for class 'hyperframe':
head(x,n,\dots)
hierarchicalordering(i, s)
hiermat(x, h)
ho.engine(model, ..., nsim, nrmh, start, control, verb)
hsvNA(h, s, v, ...)
IdenticalRows(i,j,a,b)
identical.formulae(x,y)
idorempty(w, r, caller)
ifelseAB(test, a, b)
ifelseAX(test, a, x)
ifelseXB(test, x, b)
ifelseXY(test, x, y)
ifelse1NA(test)
ifelse0NA(test)
ifelseNegPos(test, x)
illegal.iformula(ifmla, itags, dfvarnames)
implemented.for.K(correction, windowtype, explicit)
impliedpresence(tags, formula, df, extranames=character(0))
impliedcoefficients(object, tag)
inject.expr(base, expr)
inpoint(W)
inside.range(x, r)
inside.triangle(x, y, xx, yy)
inside.xypolygon(pts, polly, test01, method)
instantiate.interact(x, par)
intermaker(f, blank)
intersect.ranges(a,b,fatal)
intX.owin(w)
intX.xypolygon(polly)
intY.owin(w)
intY.xypolygon(polly)
invokeColourmapRule(colfun, x, ..., zlim, colargs)
is.atomicQtest(x)
is.cadlag(s)
is.col.argname(x)
is.data(Q)
is.expandable(x)
## S3 method for class 'ppm':
is.expandable(x)
## S3 method for class 'rmhmodel':
is.expandable(x)
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.mppm(x)
## S3 method for class 'default':
is.multitype(X, \dots)
## S3 method for class 'quad':
is.multitype(X, na.action="warn", \dots)
is.parseable(x)
## S3 method for class 'mppm':
is.poisson(x)
is.pp3(x)
is.ppx(x)
is.prime(n)
is.psp(x)
is.sob(x)
is.tess(x)
k3engine(x, y, z, box, rmax, nrval, correction)
Kborder.engine(X, rmax, nr, correction, weights, ratio)
Knone.engine(X, rmax, nr, weights, ratio)
Krect.engine(X, rmax, nr, correction, weights, ratio, fname)
Kount(dIJ, bI, b, breaks)
Kwtsum(dIJ, bI, wIJ, b, w, breaks)
Kpcf.kppm(model, what)
killinteraction(model)
km.rs.opt(o, cc, d, breaks, KM, RS)
kppmComLik(X, Xname, po, clusters, control, weightfun, rmax,
algorithm, ...)
kppmMinCon(X, Xname, po, clusters, control, statistic, statargs,
algorithm, ...)
kppmPalmLik(X, Xname, po, clusters, control, weightfun, rmax,
algorithm, ...)
## S3 method for class 'ppm':
labels(object, \dots)
least.common.multiple(n,m)
## S3 method for class 'im':
levels(x)
## S3 method for class 'im':
levels(x) <- value
lhs.of.formula(x)
linequad(X, Y, ..., eps, nd)
linearKengine(X, ..., r, reweight, denom, correction, showworking)
linearKmulti(X, I, J, r, ..., correction)
linearKmulti.inhom(X, I, J, lambdaI, lambdaJ, r, ..., correction, normalise)
linearpcfengine(X, ..., r, reweight, denom, correction)
linearpcfmulti(X, I, J, r, ..., correction)
linearpcfmulti.inhom(X, I, J, lambdaI, lambdaJ, r, ...,
correction, normalise)
linearKmultiEngine(X, I, J, ...,
r, reweight, denom, correction, showworking)
linearPCFmultiEngine(X, I, J, ...,
r, reweight, denom, correction, showworking)
listof(...)
localKengine(X, ..., wantL, lambda, correction, verbose, rvalue)
localpcfengine(X, ..., delta, rmax, nr, stoyan, lambda)
localpcfmatrix(X, i, ..., lambda, delta, rmax, nr, stoyan)
local2lpp(L, seg, tp, X)
logi.dummy(X, dummytype, nd, mark.repeat, ...)
logi.engine(Q, trend, interaction, ...,
covariates, subsetexpr, correction, rbord, covfunargs, allcovar,
vnamebase, vnameprefix, justQ, savecomputed, precomputed,
VB)
## S3 method for class 'vblogit':
logLik(object, \dots)
lty2char(i)
padtowidth(a, b, justify)
## S3 method for class 'interact':
parameters(model, \dots)
## S3 method for class 'fii':
parameters(model, \dots)
parbreak(terse)
passthrough(.Fun, ..., .Fname)
paste.expr(x)
plan.legend.layout(B, ..., side, sep, size, sep.frac, size.frac,
started, map)
PoisSaddleApp(beta, fi)
polytileareaEngine(P, xrange, yrange, nx, ny)
prettyinside(x, ...)
prettydiscrete(x, n)
## S3 method for class 'localpcfmatrix':
print(x, \dots)
## S3 method for class 'localpcfmatrix':
plot(x, \dots)
putSpatstatVariable(name, value)
## S3 method for class 'localpcfmatrix':
[(x, i, \dots)
## S3 method for class 'pp3':
[(x, i, \dots)
lookup.im(Z, x, y, naok, strict)
majorminorversion(v)
make.even.breaks(bmax, npos, bstep)
makefvlabel(op, accent, fname, sub, argname)
make.parseable(x)
makeunits(sing, plur, mul)
mapstrings(x, map)
markappend(...)
markcbind(...)
markformat(x)
## S3 method for class 'ppp':
markformat(x)
## S3 method for class 'ppx':
markformat(x)
## S3 method for class 'psp':
markformat(x)
## S3 method for class 'default':
markformat(x)
mark.scale.default(marx, w, markscale, maxsize, meansize, characters)
markspace.integral(X)
## S3 method for class 'default':
marks(x, \dots)
## S3 method for class 'quad':
marks(x, dfok=FALSE, \dots)
markappendop(x, y)
x %mapp% y
marksubset(x, index, format)
marksubsetop(x, i)
x %msub% i
markreplicateop(x, n)
x %mrep% 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)
model.se.image(fit, W, ..., what)
mpl.engine(Q, trend, interaction, ...,
covariates, subsetexpr, covfunargs, correction,
rbord, use.gam, gcontrol, famille,
forcefit, nd, eps, allcovar, callstring,
precomputed, savecomputed, preponly,
rename.intercept, justQ, weightfactor)
mpl.get.covariates(covariates, locations, type, covfunargs, need.deriv)
mpl.prepare(Q, X, P, trend, interaction, covariates,
want.trend, want.inter, correction, rbord, Pname,
callstring, ...,
subsetexpr,
covfunargs, allcovar, precomputed, savecomputed,
vnamebase, vnameprefix, warn.illegal, warn.unidentifiable,
weightfactor, skip.border)
mpl.usable(x)
MultiPair.checkmatrix(mat, n, matname, naok, zerook, asymmok)
multiplicityNumeric(x)
multiply.only.finite.entries(x, a)
na.handle.im(X, na.replace)
## S3 method for class 'fv':
names(x) <- value
## 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)
newformula(old, change, eold, enew)
newstyle.coeff.handling(object)
niceround(x, m)
nncleanEngine(kthNND, k, d, ..., tol, maxit,
plothist, lineargs, verbose, Xname)
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)
objsurfEngine(objfun, optpar, objargs,
..., dotargs, objname,
ngrid, ratio, verbose)
offsetsinformula(x)
onecolumn(m)
optimStatus(x, call)
printStatus(x, errors.only)
signalStatus(x, errors.only)
ordinal(k)
a %orifnull% b
outdated.interact(object)
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)
## S3 method for class 'solist':
pairs(\dots, plot=TRUE)
param.quad(Q)
paren(x, type)
partialModelMatrix(X,D,model,callstring,...)
pasteFormula(f)
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)
plotEachLayer(x, ..., main, plotargs, add, show.all, do.plot)
ploterodewin(W1, W2, col.edge, col.inside, do.plot, ...)
ploterodeimage(W, Z, ..., Wcol, rangeZ, colsZ, do.plot)
plot3Dpoints(xyz, eye, org,
...,
type, xlim, ylim, zlim,
add, box, main, cex, box.back, box.front)
plotPolygonBdry(x, ...)
## S3 method for class 'addvar':
plot(x, \dots, do.points=FALSE)
## S3 method for class 'barplotdata':
plot(x, \dots)
## S3 method for class 'bw.frac':
plot(x, \dots)
## S3 method for class 'bw.optim':
plot(x, \dots, showopt, optargs)
## S3 method for class 'lurk':
plot(x, \dots, shade)
## S3 method for class 'minconfit':
plot(x, \dots)
## S3 method for class 'parres':
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, main, tag, coeff, xvariable,
col, lty, lwd, col.opt, lty.opt, lwd.opt)
## S3 method for class 'qqppm':
plot(x, \dots, limits=TRUE,
monochrome=spatstat.options('monochrome'),
limcol=if(monochrome) "black" else "red")
## S3 method for class 'spatialcdf':
plot(x, \dots, xlab, ylab)
## S3 method for class 'studpermutest':
plot(x, fmla, \dots,
lty = NULL, col = NULL, lwd = NULL,
lty.theo = NULL, col.theo = NULL, lwd.theo = NULL,
lwd.mean = if (meanonly) 1 else NULL, lty.mean = lty, col.mean = col,
separately = FALSE, meanonly = FALSE,
main = if (meanonly) "group means" else NULL,
xlim = NULL, ylim = NULL, ylab = NULL, legend = !add,
legendpos = "topleft", lbox = FALSE, add = FALSE)
polynom(x, ...)
ppllengine(X, Y, action="project", check=FALSE)
## S3 method for class 'default':
ppm(Q, trend, interaction,
\dots, covariates, data, covfunargs, subset,
correction, rbord, use.gam, method, forcefit, project,
prior.mean, prior.var,
nd, eps, gcontrol, nsim, nrmh, start, control,
verb, callstring)
ppmCovariates(model)
ppmDerivatives(fit, what, Dcovfun, loc, covfunargs)
ppmInfluence(fit, what, ..., iScore, iHessian, iArgs,
drop, method, precomputed)
pppdist.mat(X, Y, cutoff = 1, q = 1, matching = TRUE,
precision = 9, approximation = 10)
pppdist.prohorov(X, Y, n, dfix, type, cutoff, matching,
ccode, auction, precision, approximation)
ppsubset(X, I)
prange(x)
## S3 method for class 'vblogit':
predict(object, newdata, type, se.fit, dispersion,
terms, na.action, \dots)
prefixfv(x, tagprefix, descprefix, lablprefix, whichtags)
prepareTitle(main)
primefactors(n, prmax)
primesbelow(nmax)
## S3 method for class 'addvar':
print(x, \dots)
## S3 method for class 'anylist':
print(x, \dots)
## S3 method for class 'autoexec':
print(x, \dots)
## S3 method for class 'bt.frame':
print(x, \dots)
## S3 method for class 'bw.frac':
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 'distfun':
print(x, \dots)
## S3 method for class 'envelope':
print(x, \dots)
## S3 method for class 'ewcdf':
print(x, digits, \dots)
## S3 method for class 'fasp':
print(x, \dots)
## S3 method for class 'funxy':
print(x, \dots)
## S3 method for class 'fv':
print(x, \dots, tight)
## S3 method for class 'fvfun':
print(x, \dots)
## S3 method for class 'hierarchicalordering':
print(x, \dots)
## S3 method for class 'hyperframe':
print(x, \dots)
## S3 method for class 'influence.ppm':
print(x, \dots)
## S3 method for class 'interact':
print(x, \dots, family, brief, banner)
## S3 method for class 'intermaker':
print(x, \dots)
## S3 method for class 'isf':
print(x, \dots)
## S3 method for class 'layered':
print(x, \dots)
## S3 method for class 'leverage.ppm':
print(x, \dots)
## S3 method for class 'lut':
print(x, \dots)
## S3 method for class 'minconfit':
print(x, \dots)
## S3 method for class 'mppm':
print(x, \dots)
## S3 method for class 'msr':
print(x, \dots)
## S3 method for class 'nnfun':
print(x, \dots)
## S3 method for class 'onearrow':
print(x, \dots)
## S3 method for class 'parres':
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 'rmhexpand':
print(x, \dots, prefix=TRUE)
## 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 'simplepanel':
print(x, \dots)
## S3 method for class 'Smoothfun':
print(x, \dots)
## S3 method for class 'solist':
print(x, \dots)
## S3 method for class 'splitppp':
print(x, \dots)
## S3 method for class 'splitppx':
print(x, \dots)
## S3 method for class 'summary.hyperframe':
print(x, \dots)
## S3 method for class 'summary.linnet':
print(x, \dots)
## S3 method for class 'summary.listof':
print(x, \dots)
## S3 method for class 'summary.logiquad':
print(x, \dots, dp=3)
## S3 method for class 'summary.lut':
print(x, \dots)
## S3 method for class 'summary.mppm':
print(x, \dots, brief)
## S3 method for class 'summary.owin':
print(x, \dots)
## S3 method for class 'summary.ppp':
print(x, \dots, dp)
## S3 method for class 'summary.psp':
print(x, \dots)
## S3 method for class 'summary.rmhexpand':
print(x, \dots)
## S3 method for class 'summary.splitppp':
print(x, \dots)
## S3 method for class 'summary.solist':
print(x, \dots)
## S3 method for class 'summary.splitppx':
print(x, \dots)
## S3 method for class 'summary.units':
print(x, \dots)
## S3 method for class 'symbolmap':
print(x, \dots)
## S3 method for class 'textstring':
print(x, \dots)
## S3 method for class 'texturemap':
print(x, \dots)
## S3 method for class 'tess':
print(x, \dots, brief=FALSE)
## S3 method for class 'timed':
print(x, \dots)
## S3 method for class 'vblogit':
print(x, \dots)
## S3 method for class 'yardstick':
print(x, \dots)
project3Dhom(xyz, eye, org, vert)
prolongseq(x, newrange, step)
putlastshift(X, vec)
quad(data, dummy, w, param)
quad.mppm(x)
RandomFieldsSafe()
ratfv(df, numer, denom, ..., ratio)
recognise.spatstat.type(x)
rectquadrat.breaks(xr, yr, nx = 5, ny = nx, xbreaks = NULL, ybreaks = NULL)
rectquadrat.countEngine(x, y, xbreaks, ybreaks, weights)
reduceformula(fmla, deletevar, verbose)
repair.image.xycoords(x)
resolveEinfo(x, what, fallback, warn)
resolve.vargamma.shape(..., nu.ker, nu.pcf, default = FALSE)
rgbNA(red, green, blue, ...)
rhs.of.formula(x, tilde)
rhohatEngine(model, covariate, reference, volume, ...,
weights, method, horvitz, smoother, resolution,
n, bw, adjust, from, to,
bwref, covname, covunits, confidence, modelcall, callstring)
rhohatCalc(ZX, Zvalues, lambda, denom, ...,
weights, lambdaX,
method, horvitz, smoother,
n, bw, adjust, from, to,
bwref, covname, confidence,
covunits, modelcall, callstring, savestuff)
rigidradius(X)
RmhExpandRule(nama)
romansort(x)
rmhsnoop(..., Wsim, Wclip, R, xcoords, ycoords, mlevels, mcodes, irep, itype,
proptype, proplocn, propmark, propindx, numerator, denominator)
roseContinuous(ang, rad, unit, ...,
start, clockwise, main, labels, at, do.plot)
ruletextline(ch, n, terse)
quadrat.testEngine(X, nx, ny, alternative, method, conditional, CR,
..., nsim, Xcount, xbreaks, ybreaks, tess, fit, Xname, fitname)
quadscheme.replicated(data, dummy, method, ...)
quadscheme.spatial(data, dummy, method, ...)
pointgrid(W, ngrid)
rastersample(X, Y)
rasterx.mask(w, drop)
rastery.mask(w, drop)
rasterxy.mask(w, drop)
rasterx.im(x)
rastery.im(x)
rasterxy.im(x, drop)
rebadge.fv(x, new.ylab, new.fname, tags, new.desc, new.labl, new.yexp,
new.dotnames, new.preferred, new.formula, new.tags)
rebadge.as.crossfun(x, main, sub, i, j)
rebadge.as.dotfun(x, main, sub, i)
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, plot.smooth,
spacing, outer, srange, monochrome, main,
xlab, ylab, rlab, ...)
resid1plot(RES, opt, plot.neg, plot.smooth,
srange, monochrome, main,
add, show.all, do.plot, ...)
resid1panel(observedX, observedV,
theoreticalX, theoreticalV, theoreticalSD,
xlab,ylab, ..., do.plot)
resolve.defaults(..., .MatchNull=TRUE, .StripNull=FALSE)
resolve.1.default(.A, ...)
resolve.2D.kernel(...,
sigma, varcov, x, mindist, adjust, bwfun, allow.zero)
restrict.mask(M, W)
reverse.xypolygon(p, adjust=FALSE)
reversePolyclipArgs(x, p)
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)
rmhSnoopEnv(Xinit, Wclip, R)
## S3 method for class 'rmhcontrol':
rmhcontrol(\dots)
## S3 method for class 'list':
rmhcontrol(\dots)
rmhEngine(InfoList, ..., verbose, kitchensink, preponly, snoop)
## 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, marks, win, giveup, verbose, warn, nsim, drop)
runifpoispp(lambda, win, ..., nsim, drop)
runifpoisppOnLines(lambda, L, nsim)
runifrect(n, win, nsim, drop)
safedeldir(X)
safelookup(Z, X, factor, warn)
samefunction(f, g)
## S3 method for class 'breakpts':
scalardilate(X, f, \dots)
## S3 method for class 'diagramobj':
scalardilate(X, f, \dots)
## S3 method for class 'msr':
scalardilate(X, f, \dots)
scanmeasure(X, ...)
## S3 method for class 'ppp':
scanmeasure(X, r, \dots, method)
## S3 method for class 'im':
scanmeasure(X, r, \dots)
scanPoisLRTS(nZ, nG, muZ, muG, alternative)
scanBinomLRTS(nZ, nG, muZ, muG, alternative)
second.moment.calc(x, sigma=NULL, edge=TRUE, what="Kmeasure", debug=FALSE,
..., varcov=NULL, expand=FALSE)
second.moment.engine(x, sigma, edge, what, ...,
kernel, obswin, varcov, npts, debug)
sensiblevarname(guess, fallback, maxlen)
sewpcf(d, w, denargs, lambda2area, divisor)
sewsmod(d, ff, wt, Ef, rvals, method="smrep", ..., nwtsteps=500)
## S3 method for class 'diagramobj':
shift(X, \dots)
## S3 method for class 'influence.ppm':
shift(X, \dots)
## S3 method for class 'leverage.ppm':
shift(X, \dots)
## S3 method for class 'msr':
shift(X, \dots)
## S3 method for class 'quadratcount':
shift(X, \dots)
## S3 method for class 'quadrattest':
shift(X, \dots)
shiftxy(X, vec = c(0, 0))
shiftxypolygon(p, vec = c(0, 0))
short.deparse(x, maxlen)
simplenumber(x, unit, multiply, tol)
simplify.xypolygon(p, dmin)
## S3 method for class 'profilepl':
simulate(object, \dots)
simulrecipe(type, expr, envir, csr, pois, constraints)
singlestring(s, coll)
slr.prepare(CallInfo, envir, data, dataAtPoints, splitby, clip)
slrAssemblePixelData(Y, Yname, W, covimages, dataAtPoints, pixelarea)
## S3 method for class 'solist':
Smooth(X, \dots)
smoothcrossEngine(Xdata, Xquery, values, sigma, ...,
weights, varcov, sorted)
smoothpointsEngine(x, values, sigma, ...,
weights, varcov, leaveoneout, sorted)
## S3 method for class 'im':
sort(x, \dots)
spatstat.rawdata.location(...)
spatstatClusterModelInfo(name, onlyPCP)
spatstatLocator(n, ...)
spatstatRmhInfo(cifname)
spatialCDFframe(model, covariate, ...)
spatialCDFtest(model, covariate, test, ...,
dimyx, eps, jitter, nsim, verbose, modelname, covname, dataname)
sphere.volume(range, nval = 10)splitHybridInteraction(coeffs, inte)
sp.foundclass(cname, inlist, formalname, argsgiven)
sp.foundclasses(cnames, inlist, formalname, argsgiven)
startinrange(x0, dx, r)
store.versionstring.spatstat()
## S3 method for class 'hyperframe':
str(object, \dots)
strausscounts(U,X,r,EqualPairs)
strsplitretain(x, split)
substringcount(x,y)
suffloc(object)
suffstat.generic(model, X, callstring)
suffstat.poisson(model, X, callstring)
summarise.trend(trend, w, a)
## S3 method for class 'envelope':
summary(object,\dots)
## S3 method for class 'hyperframe':
summary(object, \dots, brief=FALSE)
## S3 method for class 'logiquad':
summary(object, \dots, checkdup=FALSE)
## S3 method for class 'lut':
summary(object, \dots)
## S3 method for class 'mppm':
summary(object, \dots, 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)
## S3 method for class 'rmhexpand':
summary(object, \dots)
## S3 method for class 'splitppx':
summary(object, \dots)
## S3 method for class 'vblogit':
summary(object, \dots)
sumsymouter(x, w)
superimposeMarks(arglist, nobj)
symbolmaptype(x)
sympoly(x, y, n)
## S3 method for class 'hyperframe':
tail(x,n,\dots)
termsinformula(x)
test.crossing.psp(A,B)
test.selfcrossing.psp(A)
there.is.no.try(...)
tilecentroids(W, nx, ny)
tileindex(x, y, Z)
transradius(W)
trap.extra.arguments(..., .Context, .Fatal)
trianglediameters(iedge, jedge, edgelength, ..., nvert, check)
trim.mask(M, R, tolerant)
truncline(x, nc)
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
unparen(x)
## S3 method for class 'interact':
update(object, \dots)
## S3 method for class 'im':
update(object, \dots)
## S3 method for class 'ippm':
update(object, \dots, envir)
## S3 method for class 'rmhstart':
update(object, \dots)
uptrimat(x)
validradius(r, caller)
validate.angles(angles, unit, guess)
validate.mask(w, fatal=TRUE)
validate.quad(Q, fatal, repair, announce)
validposint(n, caller, fatal)
vanilla.fv(x)
variablesinformula(x)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)
warn.once(key, ...)
waxlyrical(type, terse)
weighted.var(x, w, na.rm)
windows.mppm(x)
w.quad(Q)
x.quad(Q)
y.quad(Q)
xy.grid(xr, yr, nx, ny, dx, dy)
X2testEngine(OBS, EXP, ..., method, CR, df, nsim,
conditional, alternative, testname, dataname)
## S3 method for class 'im':
xtfrm(x)
xypolyselfint(p, eps, proper, yesorno, checkinternal)
xypolygon2psp(p, w, check)