R: Internal spatstat.core functions

spatstat.core-internal {spatstat.core} | R Documentation

## Internal spatstat.core functions

### Description

Internal spatstat.core functions.

### Usage

    ## 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 'summary.slrm'
    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)
    dppDpcf(model, ...)
    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)
    ## S3 method for class 'slrm'
    evalCovar(model, covariate, ..., lambdatype,
              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, ...)
    ## S3 method for class 'slrm'
    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 'slrm'
    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)
    ## S3 method for class 'slrm'
    Kmodel(model, ...)
    killinteraction(model)
    km.rs.opt(o, cc, d, breaks, KM, RS)
    kppmComLik(X, Xname, po, clusters, control, weightfun, rmax,
               algorithm, DPP, ..., pspace)
    kppmMinCon(X, Xname, po, clusters, control, statistic, statargs,
               algorithm, DPP, ...)
    kppmPalmLik(X, Xname, po, clusters, control, weightfun, rmax,
               algorithm, DPP, ..., pspace)
    kppmCLadap(X, Xname, po, clusters, control, weightfun,
               rmax, epsilon, DPP, algorithm, ...,
               startpar, globStrat)
    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)
    optimNsteps(x)
    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")
    ## S3 method for class 'slrm'
    pcfmodel(model, ...)
    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.slrm'
    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)
    ## S3 method for class 'slrm'
    reach(x, ...)
    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, evalCovarArgs,
                   n, bw, adjust, from, to,
                   bwref, covname, covunits, confidence,
                   breaks,
                   modelcall, callstring)
    rhohatCalc(ZX, Zvalues, lambda, denom, ...,
               weights, lambdaX,
               method, horvitz, smoother,
               n, bw, adjust, from, to,
               bwref, covname, confidence, breaks, 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)
    slrmInfluence(model, what, ...)
    ## 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, R, what)

    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)

### Details

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

### Value

The return values of these functions are not documented, and may change without warning.

[Package spatstat.core version 2.3-1 Index]