Usage
## S3 method for class 'splitppx':
[(x, \dots)
## S3 method for class 'splitppx':
[(x, \dots) <- value
acedist.show(X, Y, n, d, timelag = 0)
acedist.noshow(X, Y, n, d)
active.interactions(object)
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)
applytolayers(L, FUN, ...)
area.xypolygon(polly)
areadelta2(X, r, ...)
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,
method = c("count", "distmap"),
ngrid = spatstat.options("ngrid.disc"),
exact = FALSE)
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 'hyperframe':
as.list(x, \dots)
## S3 method for class 'linim':
as.im(X, \dots)
as.listof(x)
as.units(s)
as2vector(x)
augment.msr(x, ..., sigma)
badprobability(x, NAvalue)
bbEngine(...)
bermantestEngine(model, covariate, which, alternative, ..., modelname, covname, dataname)
bdrylength.xypolygon(polly)
bdry.mask(W)
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=~1, interaction=NULL, ..., covariates=NULL,
correction="border", rbord=0, use.gam=FALSE, allcovar=FALSE)
bw.optim(cv, h, iopt, ..., cvname, hname, criterion)
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)
checkfields(X,L)
check.finite(x, context, xname, fatal, usergiven)
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, 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.testfun(f, f1, X)
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.ppm':
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)
commasep(x, join, flatten)
conform.imagelist(X, Zlist)
countingweights(id, areas, check = TRUE)
damaged.ppm(object)
data.mppm(x)
datagen.runifpointOnLines(n, L)
datagen.runifpoisppOnLines(lambda, L)
datagen.rpoisppOnLines(lambda, L, lmax, ..., check=TRUE)
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)
diagnose.ppm.engine(object, ..., type, typename, opt,
sigma, rbord, compute.sd,
compute.cts, rv, oldstyle, splineargs)
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, matchfirst, sieve, skipargs)
do.call.plotfun(fun, arglist, ...)
do.istat(panel)
doMultiStraussHard(iradii, hradii, types)
dotexpr.to.call(expr, dot, evaluator)
dropifsingle(x)
emptywindow(w)
ensure2vector(x)
ensure3Darray(x)
envelopeEngine(X, fun, simul,
nsim=99, nrank=1, ...,
verbose=TRUE, clipdata=TRUE,
transform=NULL, global=FALSE, ginterval=NULL,
savefuns=FALSE, savepatterns=FALSE, saveresultof=NULL,
weights=NULL,
nsim2=nsim, VARIANCE=FALSE, nSD=2,
Yname=NULL, maxnerr=nsim, internal=NULL, cl=NULL,
envir.user=envir.user, expected.arg="r", do.pwrong=FALSE)
envelopeProgressData(X, fun, ..., expo, normalize, deflate)
envelopeTest(X, ...,
power, 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, 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,
dimyx, eps, jitter, modelname, covname, dataname)
## S3 method for class 'lppm':
evalCovar(model, covariate, \dots,
eps, nd, jitter, modelname, covname, dataname)
evalCovariate(covariate, locations)
evalInteraction(X,P,E,interaction,correction,...,precomputed,savecomputed)
evalInterEngine(X,P,E,interaction,correction,...,precomputed,savecomputed)
evalPairPotential(X,P,E,pairpot,potpars,R)
even.breaks.owin(w)
evenly.spaced(x, tol)
exactdt(X, ...)
exactPdt(w)
expand.polynom(f)
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, ...)
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)
findbestlegendpos(...)
findCovariate(covname, scope, scopename=NULL)
findcbind(root, depth, maxdepth)
firstfactor(x)
fii(interaction, coefs, Vnames, IsOffset)
fillNA(x, value)
flatfname(x)
flipxypolygon(p)
forbidNA(x, context, xname, fatal, usergiven)
forbid.logi(object)
FormatFaspFormulae(f, argname)
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)
getfields(X, L, fatal = TRUE)
getglmdata(object, drop=FALSE)
getglmfit(object)
getglmsubset(object)
getlambda.lpp(lambda, X, ...)
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)
gridindex(x, y, xrange, yrange, nx, ny)
grid1index(x, xrange, nx)
grow.rectangle(W, xmargin=0, ymargin=xmargin)
grow.mask(M, xmargin=0, ymargin=xmargin)
gsubdot(replacement, x)
HermiteCoefs(order)
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, ...)
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)
inpoint(W)
inside.range(x, r)
inside.triangle(x, y, xx, yy)
inside.xypolygon(pts, polly, test01, method)
instantiate.interact(x, par)
intersect.ranges(a,b,fatal)
intX.owin(w)
intX.xypolygon(polly)
intY.owin(w)
intY.xypolygon(polly)
is.atomicQtest(x)
is.cadlag(s)
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.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)
kppmMinCon(X, Xname, po, clusters, statistic, statargs, ...)
kppmComLik(X, Xname, po, clusters, control, weightfun, rmax, ...)
## 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, correction, rbord, covfunargs, allcovar,
vnamebase, vnameprefix, justQ, savecomputed, precomputed)
lty2char(i)
parbreak(terse)
passthrough(.Fun, ..., .Fname)
paste.expr(x)
plan.legend.layout(B, ..., side, sep, size, sep.frac, size.frac,
started, map)
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)
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=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)
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, 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, ...,
covfunargs, allcovar, precomputed, savecomputed,
vnamebase, vnameprefix, warn.illegal, warn.unidentifiable,
weightfactor, skip.border)
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 '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)
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)
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, do.plot, ...)
ploterodeimage(W, Z, ..., Wcol, rangeZ, colsZ, do.plot)
## 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 '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=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")
polynom(x, ...)
ppllengine(X, Y, action="project", check=FALSE)
## S3 method for class 'default':
ppm(Q, trend, interaction,
\dots, covariates, data, covfunargs,
correction, rbord, use.gam, method, forcefit,
project, 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 = 1, matching = TRUE,
ccode = TRUE, precision = 9, approximation = 10)
ppsubset(X, I)
prange(x)
prefixfv(x, tagprefix, descprefix, lablprefix, whichtags)
primefactors(n, prmax)
primesbelow(nmax)
## S3 method for class 'addvar':
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 'symbolmap':
print(x, \dots)
## S3 method for class 'Smoothfun':
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=TRUE, brief=FALSE)
## 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 'linim':
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 '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 '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.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=3)
## 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.splitppx':
print(x, \dots)
## S3 method for class 'summary.units':
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)
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)
rgbNA(red, green, blue, ...)
rhs.of.formula(x, tilde)
rhohatEngine(model, covariate, reference, volume, ...,
method, smoother, resolution,
n, bw, adjust, from, to,
bwref, covname, covunits, confidence, modelcall, callstring)
rhohatCalc(ZX, Zvalues, lambda, denom, ...,
method, smoother,
n, bw, adjust, from, to,
bwref, covname, confidence,
covunits, modelcall, callstring, savestuff)
RmhExpandRule(nama)
rmhsnoop(..., Wsim, Wclip, R, xcoords, ycoords, mlevels, mcodes, irep, itype,
proptype, proplocn, propmark, propindx, numerator, denominator)
quadrat.testEngine(X, nx, ny, alternative, method, conditional,
..., nsim, Xcount, xbreaks, ybreaks, tess, fit, Xname, fitname)
quadscheme.replicated(data, dummy, method = "grid", ...)
quadscheme.spatial(data, dummy, method = "grid", ...)
pointgrid(W, ngrid)
rastersample(X, Y)
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=0.1, srange=NULL,monochrome=FALSE, main=NULL, ...)
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)
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)
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, 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, ...,
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 '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)
simplify.xypolygon(p, dmin)
simulrecipe(type, expr, envir, csr, pois)
singlestring(s, coll)
slr.prepare(CallInfo, envir, data, dataAtPoints, splitby, clip)
slrAssemblePixelData(Y, Yname, W, covimages, dataAtPoints, pixelarea)
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)
spatstatRmhInfo(cifname)
spatialCDFframe(model, covariate, ...)
spatialCDFtest(model, covariate, test, ...,
dimyx, eps, jitter, modelname, covname, dataname)
sphere.volume(range, nval = 10)
splat(...)
splitHybridInteraction(coeffs, inte)
sp.foundclass(cname, inlist, formalname, argsgiven)
sp.foundclasses(cnames, inlist, formalname, argsgiven)
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)
sumsymouter(x, w)
superimposeMarks(arglist, nobj)
symbolmaptype(x)
sympoly(x, y, n)
termsinformula(x)
test.crossing.psp(A,B)
test.selfcrossing.psp(A)
tilecentroids(W, nx, ny)
tileindex(x, y, Z)
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) <- valueunparen(x)
## S3 method for class 'interact':
update(object, \dots)
## S3 method for class 'rmhstart':
update(object, \dots)
uptrimat(x)
validradius(r, caller)
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)
## S3 method for class 'msr':
with(data, expr, \dots)
w.quad(Q)
x.quad(Q)
y.quad(Q)
xy.grid(xr, yr, nx, ny, dx, dy)
X2testEngine(OBS, EXP, ..., method, df, nsim,
conditional, alternative, testname, dataname)
## S3 method for class 'im':
xtfrm(x)
xypolyselfint(p, eps, proper, yesorno, checkinternal)
xypolygon2psp(p, w, check)