spatstat (version 1.34-1)

spatstat-internal: Internal spatstat functions

Description

Internal spatstat functions.

Usage

## S3 method for class 'hyperframe':
[(x, i, j, drop=FALSE, \dots)
## S3 method for class 'hyperframe':
[(x, i, j) <- value
## S3 method for class 'hyperframe':
$(x, name)
## S3 method for class 'hyperframe':
$(x, i) <- value
## 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)
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 '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 'scan.test':
as.im(X, \dots)
## S3 method for class 'linim':
as.im(X, \dots)
as.listof(x)
as.units(s)
badprobability(x, NAvalue)
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)
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)
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, 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=TRUE, things="data points", naok=FALSE)
check.nmatrix(m, npoints, fatal=TRUE, things="data points", naok=FALSE,
              squarematrix=TRUE, matchto="nrow")
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)
clear.simplepanel(P)
clip.psp(x, window, check=TRUE)
cliprect.psp(x, window)
clippoly.psp(s, window)
closepairs(X,rmax,ordered,what)
closethresh(X,R,S,ordered)
## S3 method for class 'summary.ppm':
coef(object, \dots)
## 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)
compilepcf(D, r, weights, denom, check, endcorrect, ...)
conform.ratfv(x)
crosspairs(X,Y,rmax,what)
crosspaircounts(X,Y,r)
crosspairquad(Q,rmax,what)
cobble.xy(x, y, f, fatal, ...)
codetime(x, hms)
commasep(x, join)
conform.imagelist(X, Zlist)
countingweights(id, areas, check = TRUE)
damaged.ppm(object)
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, verbose)
default.ntile(X)
deltasuffstat(model, ..., restrict, dataonly, force)
dflt.redraw(button, name, env)
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)
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, sieve)
do.istat(panel)
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)
explain.ifnot(expr, context)
## S3 method for class 'slrm':
extractAIC(fit, scale = 0, k = 2, \dots)
extractAtomicQtests(x)
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)
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)
fvnames(X, a)
fvnames(X, a) <- value
g3engine(x, y, z, box, rmax, nrval, correction)
g3Cengine(x, y, z, box, rmax, nrval)
greatest.common.divisor(n,m)
getdataname(defaultvalue, ..., dataname)
getfields(X, L, fatal = TRUE)
getglmdata(object, drop=FALSE)
getglmfit(object)
getglmsubset(object)
getlambda.lpp(lambda, X, ...)
getppmdatasubset(object)
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.simplepanel(P, side, len, new.clicks, new.redraws, ..., aspect)
gsubdot(replacement, x)
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)
ifelseAB(test, a, b)
ifelseAX(test, a, x)
ifelseXB(test, x, b)
ifelseXY(test, x, y)
ifelse1NA(test)
ifelse0NA(test)
ifelseNegPos(test, x)
implemented.for.K(correction, windowtype, explicit)
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)
## S3 method for class 'default':
is.multitype(X, \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.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)
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)
layout.boxes(B, n, horizontal, aspect, usefrac)
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)
passthrough(.Fun, ..., .Fname)
paste.expr(x)
prettyinside(x, ...)
## S3 method for class 'localpcfmatrix':
print(x, \dots)
## S3 method for class 'localpcfmatrix':
plot(x, \dots)
## 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)
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)
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)
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, 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)
optimStatus(x, call)
printStatus(x, errors.only)
redraw.simplepanel(P, verbose)
run.simplepanel(P, verbose)
signalStatus(x, errors.only)
simplepanel(title, B, boxes, clicks, redraws, exit, env)
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, ...)
ploterodeimage(W, Z, ..., Wcol, rangeZ, colsZ)
## 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")
## 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, ..., 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 'fasp':
print(x, \dots)
## S3 method for class 'funxy':
print(x, \dots)
## S3 method for class 'fv':
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 '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 '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.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 'tess':
print(x, \dots, brief=FALSE)
## S3 method for class 'timed':
print(x, \dots)
prolongseq(x, newrange)
quad(data, dummy, w, param)
RandomFieldsSafe()
ratfv(df, numer, denom, ..., ratio)
rectquadrat.breaks(xr, yr, nx = 5, ny = nx, xbreaks = NULL, ybreaks = NULL)
rectquadrat.countEngine(x, y, xbreaks, ybreaks, weights)
repair.image.xycoords(x)
resolveEinfo(x, what, fallback, warn)
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, baseline, ...,
           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)
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(..., .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)
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, edge, what, ...,
      obswin, varcov, npts, debug)
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))
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)
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)
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)
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 '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)
sympoly(x, y, n)
termsinformula(x)
test.crossing.psp(A,B)
test.selfcrossing.psp(A)
tilecentroids(W, nx, ny)
trap.extra.arguments(..., .Context, .Fatal)
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) <- valueunparen(x)
## S3 method for class 'interact':
update(object, \dots) 
## S3 method for class 'rmhstart':
update(object, \dots)
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)
weighted.var(x, w, na.rm)
## 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)

Arguments

Details

These internal spatstat functions are not usually called directly by the user. Their names and capabilities may change without warning from one version of spatstat to the next.