## S3 method for class 'localpcfmatrix'
x[i, ...]
## S3 method for class 'rat'
x[...]
accumulateStatus(x, stats)
active.interactions(object)
adaptcoef(new.coef, fitcoef, drop)
adjust.ratfv(f, columns, numfactor, denfactor)
## S3 method for class 'msr'
affine(X, mat, vec, ...)
ang2rad(ang, unit, start, clockwise)
areadelta2(X, r, ..., sparseOK)
assemble.plot.objects(xlim, ylim, ..., lines, polygon)
## S3 method for class 'rppm'
as.ppm(object)
## S3 method for class 'bw.optim'
as.data.frame(x, ...)
## S3 method for class 'fv'
as.data.frame(x, ...)
augment.msr(x, ..., sigma, recompute)
bandwidth.is.infinite(sigma)
BartCalc(fY, fK)
bermantestCalc(fram, which, alternative, ...)
bermantestEngine(model, covariate, which, alternative, ...,
                 modelname, covname, dataname)
bigvaluerule(objfun, objargs, startpar, ...)
bind.ratfv(x, numerator, denominator, labl, desc, preferred,
           ratio, quotient)
blankcoefnames(x)
bt.frame(Q, trend, interaction, ..., covariates,
         correction, rbord, use.gam, allcovar)
bw.optim(cv, h, iopt, ..., cvname, hname, criterion,
         optimum, warnextreme, hargnames, unitname)
calc.DR(COV, z, Dim)
calc.NNIR(COV, z, pos, Dim)
calc.SAVE(COV, z, Dim)
calc.SIR(COV, z)
calc.TSE(COV, z, pos, Dim1, Dim2)
cannot.update(...)
censtimeCDFest(o, cc, d, breaks, ...,
     KM, RS, HAN, RAW, han.denom, tt, pmax)
change.default.expand(x, newdefault)
check.separable(dmat, covname, isconstant, fatal)
check.testfun(f, f1, X)
circticks(R, at, unit, start, clockwise, labels)
clarkevansCalc(X, correction, clipregion, working)
## S3 method for class 'summary.kppm'
coef(object, ...)
## S3 method for class 'summary.ppm'
coef(object, ...)
## S3 method for class 'vblogit'
coef(object, ...) 
## S3 method for class 'rat'
compatible(A, B, ...) 
compileCDF(D, B, r, ..., han.denom, check)
condSimCox(object, nsim, ..., window, n.cond, w.cond,
           giveup, maxchunk, verbose, drop)
conform.ratfv(x)
CressieReadStatistic(OBS,EXP,lambda,normalise,named)
CressieReadSymbol(lambda)
CressieReadName(lambda)
cutoff2Dkernel(kernel, sigma, varcov, ..., scalekernel, cutoff, fatal)
CVforPCF(bw, stuff)
damaged.ppm(object)
data.mppm(x)
datagen.runifpointOnLines(n, L)
datagen.runifpoisppOnLines(lambda, L)
datagen.rpoisppOnLines(lambda, L, lmax, ..., check)
default.clipwindow(object, epsilon)
deltasuffstat(model, ...,
              restrict, dataonly, sparseOK, quadsub,
              force, warn.forced, verbose, use.special)
Deviation(x, ref, leaveout, n, xi)
## S3 method for class 'ppmInfluence'
dfbetas(model, ...)
densitycrossEngine(Xdata, Xquery, sigma, ...,
                    kernel, scalekernel,
                    weights, edge, varcov,
                    diggle, sorted, cutoff)
densitypointsEngine(x, sigma, ...,
                    kernel, scalekernel,
                    weights, edge, varcov,
                    leaveoneout, diggle, sorted, spill, cutoff,
                    debug)
diagnose.ppm.engine(object, ..., type, typename, opt,
                         sigma, rbord, compute.sd, compute.cts,
                         envelope, nsim, nrank,
                         rv, oldstyle, splineargs, verbose)
digestCovariates(..., W)
digital.volume(range, nval, vside)
## S3 method for class 'fasp'
dim(x)
## S3 method for class 'msr'
dim(x)
## S3 method for class 'fasp'
dimnames(x)
## S3 replacement method for class 'fasp'
dimnames(x) <- value
## S3 method for class 'msr'
dimnames(x)
distributecbind(x)
doMultiStraussHard(iradii, hradii, types)
dppmFixIntensity(DPP, lambda, po)
dppmFixAlgorithm(algorithm, changealgorithm, clusters, startpar)
envelopeEngine(X, fun, simul,
           nsim, nrank, ..., funargs, funYargs,
           verbose, clipdata, 
           transform, global, ginterval, use.theory,
           alternative, scale, clamp,
           savefuns, savepatterns, saveresultof,
           weights,
           nsim2, VARIANCE, nSD,
           Yname,
           maxnerr, rejectNA, silent, maxerr.action,
           internal, cl,
           envir.user, expected.arg, do.pwrong,
           foreignclass, collectrubbish)
envelopeProgressData(X, fun, ..., exponent,
                     alternative, leaveout, scale, clamp,
                     normalize, deflate, rmin, 
                     save.envelope, savefuns, savepatterns)
envelopeTest(X, ..., exponent, alternative,
            rinterval, leaveout, scale, clamp, tie.rule,
            interpolate, save.interpolant,
            save.envelope, savefuns, savepatterns,
            Xname, badXfatal, verbose)
## S3 method for class 'hasenvelope'
envelope(Y, ..., Yname)
## S3 method for class 'matrix'
envelope(Y, ..., rvals, observed, theory, funX,
  nsim, nsim2, jsim, jsim.mean,
  type, alternative, scale, clamp, csr, use.theory, nrank, ginterval, nSD,
  savefuns, check, Yname, do.pwrong, weights, precomputed, gaveup)
equalpairs(U, X, marked=FALSE)
evalCovar(model, covariate, ...)
## S3 method for class 'ppm'
evalCovar(model, covariate, ..., lambdatype,
          dimyx, eps, interpolate, jitter, jitterfactor,
          modelname, covname, dataname, subset) 
evalCovariate(covariate, locations)
evalInteraction(X,P,E,interaction,correction,splitInf,...,
                precomputed,savecomputed)
evalInterEngine(X,P,E,interaction,correction,splitInf,...,
                Reach,precomputed,savecomputed)
evalPairPotential(X,P,E,pairpot,potpars,R)
evaluate2Dkernel(kernel, x, y, sigma, varcov, ..., scalekernel)
expandwinPerfect(W, expand, amount)
ExpSmoothLog(X, ..., at, weights)
## S3 method for class 'slrm'
extractAIC(fit, scale = 0, k = 2, ...)
extractAtomicQtests(x)
fakeNeyScot(Y, lambda, win, saveLambda, saveparents)
## S3 method for class 'vblogit'
family(object, ...)
fasp(fns, which, formulae, dataname, title, rowNames, colNames, checkfv)
f3engine(x, y, z, box, vside, range, nval, correction)
f3Cengine(x, y, z, box, vside, rmax, nrval)
fill.coefs(coefs, required)
findCovariate(covname, scope, scopename=NULL)
findbestlegendpos(...)
findcbind(root, depth, maxdepth)
fii(interaction, coefs, Vnames, IsOffset, vnameprefix)
flatfname(x)
## S3 method for class 'msr'
flipxy(X)
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)
getdataname(defaultvalue, ..., dataname)
getglmdata(object, drop=FALSE)
getglmfit(object)
getglmsubset(object)
getppmdatasubset(object)
getppmOriginalCovariates(object)
getRandomFieldsModelGen(model)
getSumFun(abbreviation, classname, ismarked, fatal)
geyercounts(U,X,r,sat,Xcounts,EqualPairs)
geyerdelta2(X,r,sat,...,sparseOK, correction)
GLMpredict(fit, data, coefs, changecoef, type)
good.correction.K(X)

hackglmmPQL(fixed, random, family, data, correlation, weights,
            control, niter, verbose, subset, ..., reltol)
hasenvelope(X, E)
hasglmfit(object)
HermiteCoefs(order)
handle.rshift.args(W, ..., radius, width, height,
                   edge, clip, edgedefault)
hierarchicalordering(i, s)
hiermat(x, h)
ho.engine(model, ..., nsim, nrmh, start, control, verb)
illegal.iformula(ifmla, itags, dfvarnames)
implemented.for.K(correction, windowtype, explicit)
impliedpresence(tags, formula, df, extranames=character(0))
impliedcoefficients(object, tag)
## S3 method for class 'ppmInfluence'
influence(model, ...)
instantiate.interact(x, par)
interactionfamilyname(x)
intermaker(f, blank)
is.atomicQtest(x)
is.cadlag(s)
is.expandable(x)
## S3 method for class 'ppm'
is.expandable(x)  
## S3 method for class 'rmhmodel'
is.expandable(x) 
is.interact(x)
## S3 method for class 'mppm'
is.marked(X, ...)
## S3 method for class 'msr'
is.marked(X, ...)
is.mppm(x)
## S3 method for class 'mppm'
is.multitype(X, ...)
## S3 method for class 'msr'
is.multitype(X, ...)
## S3 method for class 'mppm'
is.poisson(x)
is.scov(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, use.integers)
Kount(dIJ, bI, b, breaks)
Kwtsum(dIJ, bI, wIJ, b, w, breaks, fatal)
Kpcf.kppm(model, what)
killinteraction(model)
km.rs.opt(o, cc, d, breaks, KM, RS)
kppmComLik(X, Xname, po, clusters, control, weightfun, rmax,
           algorithm, DPP, ..., pint)
kppmMinCon(X, Xname, po, clusters, control, statistic, statargs,
           algorithm, DPP, ...)
kppmPalmLik(X, Xname, po, clusters, control, weightfun, rmax, 
           algorithm, DPP, ..., pint)
kraever(package, fatal)
kraeverRandomFields()
## S3 method for class 'ppm'
labels(object, ...)
## S3 method for class 'ppmInfluence'
leverage(model, ...)
localKengine(X, ..., wantL, lambda, rmax, correction, verbose, rvalue)
localKmultiEngine(X, from, to,
           lambdaFrom, lambdaTo, ..., rmax, wantL,
           correction, verbose, rvalue, sigma, varcov,
           lambdaX, update, leaveoneout,
           Iexplain, Jexplain, Ikey, Jkey, miss.update, miss.leave)
localpcfengine(X, ..., delta, rmax, nr, stoyan, lambda, rvalue)
localpcfmatrix(X, i, ..., lambda, delta, rmax, nr, stoyan)
logi.engine(Q, trend, interaction, ..., 
            covariates, subsetexpr, clipwin,
            correction, rbord, covfunargs, allcovar, 
            vnamebase, vnameprefix, justQ, savecomputed, precomputed,
            VB)
## S3 method for class 'vblogit'
logLik(object, ...)
lookup2DkernelInfo(kernel)
makefvlabel(op, accent, fname, sub, argname)
maskLaslett(X, ..., eps, dimyx, xy, oldX, verbose, plotit)
match.kernel(kernel)
match2DkernelName(kernel)
mctestSigtraceEngine(R, devdata, devsim, ...,
     interpolate, confint, alpha, exponent, unitname)
meanlistfv(z, ...)
model.se.image(fit, W, ..., what)
modelFrameGam(formula, ...)
mpl.engine(Q, trend, interaction, ...,
         covariates, subsetexpr, clipwin, covfunargs, correction,
	 rbord, use.gam, gcontrol,
         GLM, GLMfamily, GLMcontrol, 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, clip.interaction, splitInf)
mpl.usable(x)
MultiPair.checkmatrix(mat, n, matname, naok, zerook, asymmok)
## S3 replacement method for class 'fv'
names(x) <- value
newformula(old, change, eold, enew, expandpoly)
newstyle.coeff.handling(object)
nncleanEngine(kthNND, k, d, ..., tol, maxit,
              plothist, lineargs, verbose, Xname)
nndcumfun(X, ..., r)
no.trend.ppm(x)
objsurfEngine(objfun, optpar, objargs,
              ..., dotargs, objname,
              ngrid, ratio, verbose)
optimConverged(x)
optimStatus(x, call)
outdated.interact(object)
oversize.quad(Q, ..., nU, nX, p)
PairPotentialType(pairpot)
## S3 method for class 'listof'
pairs(..., plot=TRUE)
## S3 method for class 'solist'
pairs(..., plot=TRUE)
## S3 method for class 'localpcfmatrix'
plot(x, ...)
PoisSaddle(beta, fi)
PoisSaddleArea(beta, fi)
PoisSaddleGeyer(beta, fi)
PoisSaddlePairwise(beta, fi)
polyLaslett(X, ..., oldX, verbose, plotit)
PPMmodelmatrix(object, data, ..., subset, Q, keepNA, irregular,
               splitInf)
printStatus(x, errors.only)
printStatusList(stats)
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")
ploterodewin(W1, W2, col.edge, col.inside, do.plot, ...)
ploterodeimage(W, Z, ..., Wcol, rangeZ, colsZ, do.plot)
## S3 method for class 'addvar'
plot(x, ..., do.points=FALSE)
## S3 method for class 'bw.frac'
plot(x, ...)
## S3 method for class 'bw.optim'
plot(x, ..., showopt, optargs)
## S3 method for class 'lurk'
plot(x, ..., shade)
## S3 method for class 'minconfit'
plot(x, ...)
## S3 method for class 'parres'
plot(x, ...)
## S3 method for class 'plotpairsim'
plot(x, ...)
## S3 method for class 'qqppm'
plot(x, ..., limits=TRUE,
           monochrome=spatstat.options('monochrome'),
           limcol=if(monochrome) "black" else "red")
## S3 method for class 'spatialcdf'
plot(x, ..., xlab, ylab)
## Default S3 method:
ppm(Q, trend, interaction,
       ..., covariates, data, covfunargs, subset, clipwin,
       correction, rbord, use.gam, method, forcefit, emend, project,
       prior.mean, prior.var,
       nd, eps, gcontrol, nsim, nrmh, start, control,
       verb, callstring)
ppmCovariates(model)
ppmDerivatives(fit, what, Dcovfun, loc, covfunargs)
ppmInfluenceEngine(fit, what, ..., iScore, iHessian, iArgs,
              drop, method, fine, precomputed, sparseOK,
              fitname, multitypeOK, entrywise, matrix.action,
              dimyx, eps,
              geomsmooth)
## S3 method for class 'vblogit'
predict(object, newdata, type, se.fit, dispersion,
                          terms, na.action, ...)
## S3 method for class 'profilepl'
predict(object, ...)
prefixfv(x, tagprefix, descprefix, lablprefix, whichtags)
## S3 method for class 'addvar'
print(x, ...)
## S3 method for class 'bt.frame'
print(x, ...)
## S3 method for class 'bw.frac'
print(x, ...)
## S3 method for class 'bw.optim'
print(x, ...)
## S3 method for class 'densityfun'
print(x, ...)
## S3 method for class 'diagppm'
print(x, ...)
## S3 method for class 'detpointprocfamily'
print(x, ...)
## S3 method for class 'detpointprocfamilyfun'
print(x, ...)
## S3 method for class 'envelope'
print(x, ...)
## S3 method for class 'fasp'
print(x, ...)
## S3 method for class 'fv'
print(x, ..., tight)
## S3 method for class 'fvfun'
print(x, ...)
## S3 method for class 'hasenvelope'
print(x, ...)
## S3 method for class 'hierarchicalordering'
print(x, ...)
## S3 method for class 'influence.ppm'
print(x, ...)
## S3 method for class 'interact'
print(x, ..., family, brief, banner)       
## S3 method for class 'intermaker'
print(x, ...)
## S3 method for class 'isf'
print(x, ...)
## S3 method for class 'laslett'
print(x, ...)
## S3 method for class 'leverage.ppm'
print(x, ...)
## S3 method for class 'localpcfmatrix'
print(x, ...)
## S3 method for class 'lurk'
print(x, ...)
## S3 method for class 'minconfit'
print(x, ...)
## S3 method for class 'mppm'
print(x, ...)
## S3 method for class 'msr'
print(x, ...)
## S3 method for class 'parres'
print(x, ...)
## S3 method for class 'plotppm'
print(x, ...)
## S3 method for class 'plotpairsim'
print(x, ...)
## S3 method for class 'profilepl'
print(x, ...)
## S3 method for class 'quadrattest'
print(x, ...)
## S3 method for class 'qqppm'
print(x, ...)
## S3 method for class 'rat'
print(x, ...)
## S3 method for class 'rmhcontrol'
print(x, ...)
## S3 method for class 'rmhexpand'
print(x, ..., prefix=TRUE)
## S3 method for class 'rmhmodel'
print(x, ...)
## S3 method for class 'rmhstart'
print(x, ...)
## S3 method for class 'rmhInfoList'
print(x, ...)
## S3 method for class 'rppm'
print(x, ...)
## S3 method for class 'Smoothfun'
print(x, ...)
## S3 method for class 'summary.mppm'
print(x, ..., brief)
## S3 method for class 'summary.rmhexpand'
print(x, ...)
## S3 method for class 'summary.ssf'
print(x, ...)
## S3 method for class 'vblogit'
print(x, ...)
quad.mppm(x)
quadBlockSizes(nX, nD, p, nMAX, announce)
RandomFieldsSafe()
ratfv(df, numer, denom, ..., ratio)
rebadge.as.crossfun(x, main, sub, i, j)
rebadge.as.dotfun(x, main, sub, i)
rebadge.fv(x, new.ylab, new.fname, tags, new.desc, new.labl, new.yexp,
           new.dotnames, new.preferred, new.formula, new.tags)
rebadgeLabels(x, new.fname)
reconcile.fv(...)
reduceformula(fmla, deletevar, verbose)
reheat(model, invtemp)
RelevantDeviation(x, alternative, clamp, scaling)
rename.fv(x, fname, ylab, yexp)
## S3 method for class 'msr'
rescale(X, s, unitname)
resolveEinfo(x, what, fallback, warn, atomic)
resolve.foxall.window(X, Y, W, warn.trim)
resolve.lambda(X, lambda, ..., sigma, varcov, leaveoneout, update)
resolve.lambda.cross(X, I, J, lambdaI, lambdaJ, ..., lambdaX,
                     sigma, varcov, leaveoneout, update, lambdaIJ,
                     Iexplain, Jexplain, miss.update, miss.leave,
                     caller)
resolve.vargamma.shape(..., nu.ker, nu.pcf, default)
roseContinuous(ang, rad, unit, ...,
               start, clockwise, main, labels, at, do.plot)
## S3 method for class 'msr'
rotate(X, angle, ..., centre)
quadrat.testEngine(X, nx, ny, alternative, method, conditional, CR, 
     ..., nsim, Xcount, xbreaks, ybreaks, tess, fit, df.est, Xname, fitname)
reincarnate.interact(object)
resid4plot(RES, plot.neg, plot.smooth,
           spacing, outer, srange, monochrome, main,
           xlab, ylab, rlab, col.neg, col.smooth, ...)
resid1plot(RES, opt, plot.neg, plot.smooth,
              srange, monochrome, main,
              add, show.all, do.plot, col.neg, col.smooth, ...)
resid1panel(observedX, observedV,
            theoreticalX, theoreticalV, theoreticalSD,
            xlab,ylab, ..., do.plot)
resolve.2D.kernel(...,
            sigma, varcov, x, mindist, adjust, bwfun, allow.zero)
rhohatEngine(model, covariate, reference, volume, ...,
               subset, 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, positiveCI, markovCI,
           covunits, modelcall, callstring, savestuff)
rMaternInhibition(type, kappa, r, win, stationary, ..., nsim, drop)
rmax.Rigid(X, g)
rmax.rule(fun, W, lambda)
## S3 method for class 'rmhcontrol'
rmhcontrol(...) 
## S3 method for class 'list'
rmhcontrol(...) 
rmhEngine(InfoList, ..., verbose, kitchensink, preponly, snoop,
                           overrideXstart, overrideclip) 
RmhExpandRule(nama)
rmhResolveControl(control, model)
rmhResolveExpansion(win, control, imagelist, itype)
rmhResolveTypes(model, start, control)
rmhsnoop(..., Wsim, Wclip, R, xcoords, ycoords, mlevels, mcodes, irep, itype, 
     proptype, proplocn, propmark, propindx, numerator, denominator,
     panel.only)
rmhSnoopEnv(Xinit, Wclip, R)
## S3 method for class 'rmhmodel'
rmhmodel(model, ...) 
## S3 method for class 'rmhstart'
rmhstart(start, ...) 
## S3 method for class 'list'
rmhstart(start, ...) 
rmpoint.I.allim(n, f, types)
rocData(covariate, nullmodel, ..., high)
rocModel(lambda, nullmodel, ..., high)
rpoint.multi(n, f, fmax, marks, win, giveup, verbose, warn, nsim, drop)
runifpoispp(lambda, win, ..., nsim, drop)
runifpoisppOnLines(lambda, L, nsim, drop)
safevalue(x, default)
## S3 method for class 'msr'
scalardilate(X, f, ...)
scanmeasure(X, ...)
## S3 method for class 'ppp'
scanmeasure(X, r, ..., method) 
## S3 method for class 'im'
scanmeasure(X, r, ...)
scanPoisLRTS(nZ, nG, muZ, muG, alternative)
scanBinomLRTS(nZ, nG, muZ, muG, alternative)
second.moment.calc(x, sigma, edge, what, ...,
                   varcov, expand, obswin, npts, debug)
second.moment.engine(x, sigma, edge, what, ...,
      kernel, scalekernel, obswin, varcov, npts, debug, fastgauss)
sewpcf(d, w, denargs, lambda2area, divisor)
sewsmod(d, ff, wt, Ef, rvals, method="smrep", ..., nwtsteps=500)
## S3 method for class 'influence.ppm'
shift(X, ...)
## S3 method for class 'leverage.ppm'
shift(X, ...)
## S3 method for class 'msr'
shift(X, ...)
## S3 method for class 'quadrattest'
shift(X, ...)
signalStatus(x, errors.only)
## S3 method for class 'profilepl'
simulate(object, ...)
simulrecipe(type, expr, envir, csr, pois, constraints)
slr.prepare(CallInfo, envir, data, dataAtPoints, splitby, clip)
slrAssemblePixelData(Y, Yname, W, covimages, dataAtPoints, pixelarea)
## S3 method for class 'solist'
Smooth(X, ...)
smoothcrossEngine(Xdata, Xquery, values, sigma, ...,
                    weights, varcov,
                    kernel, scalekernel, sorted, cutoff)
smoothpointsEngine(x, values, sigma, ...,
                   kernel, scalekernel,
                   weights, varcov, leaveoneout, sorted, cutoff, debug)
spatstatClusterModelInfo(name, onlyPCP)
spatstatDPPModelInfo(model)
spatstatRmhInfo(cifname)
spatialCDFframe(model, covariate, ..., jitter)
spatialCDFtest(model, covariate, test, ...,
         dimyx, eps, interpolate, jitter,
         nsim, verbose, modelname, covname, dataname)
spatialCDFtestCalc(fra, test, ..., details)
sphere.volume(range, nval = 10)
splitHybridInteraction(coeffs, inte)
sp.foundclass(cname, inlist, formalname, argsgiven)             
sp.foundclasses(cnames, inlist, formalname, argsgiven)
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,...)
## S3 method for class 'mppm'
summary(object, ..., brief=FALSE)
## S3 method for class 'msr'
summary(object, ...)
## S3 method for class 'profilepl'
summary(object, ...)
## S3 method for class 'rmhexpand'
summary(object, ...)
## S3 method for class 'vblogit'
summary(object, ...)
thinjump(n, p)
tweak.coefs(model, new.coef)
tweak.fv.entry(x, current.tag, new.labl, new.desc, new.tag)
tweak.ratfv.entry(x, ...)
twostage.test(X, ..., exponent, nsim, nsimsub,
              alternative, reuse, leaveout, interpolate,
              savefuns, savepatterns, verbose, badXfatal, testblurb)
twostage.envelope(X, ..., nsim, nsimsub, nrank,
                  alternative, reuse, leaveout, interpolate,
                  savefuns, savepatterns, verbose, badXfatal, testlabel)
## S3 method for class 'msr'
unitname(x) 
## S3 replacement method for class 'msr'
unitname(x) <- value 
## S3 method for class 'ippm'
update(object, ..., envir) 
## S3 method for class 'msr'
update(object, ...) 
## S3 method for class 'rmhstart'
update(object, ...)
validate2Dkernel(kernel, fatal)
validate.angles(angles, unit, guess)
validate.weights(x, recip, how, allowzero, allowinf)
vanilla.fv(x)
varcountEngine(g, B, lambdaB, f)


versionstring.interact(object)
versionstring.ppm(object)
weightedclosepairs(X, r, correction, what)
windows.mppm(x)
X2testEngine(OBS, EXP, ..., method, CR, df, nsim,
     conditional, alternative, testname, dataname)