spatstat.model-internal: Internal spatstat.model functions

In spatstat.model: Parametric Statistical Modelling and Inference for the 'spatstat' Family

Internal spatstat.model functions

Description

Internal spatstat.model functions.

Usage

accumulateStatus(x, stats)
active.interactions(object)
adaptcoef(new.coef, fitcoef, drop)
## S3 method for class 'msr'
affine(X, mat, vec, ...)
areadelta2(X, r, ..., sparseOK)
as.isf(object)
augment.msr(x, ..., sigma, recompute)
blankcoefnames(x)
bt.frame(Q, trend, interaction, ..., covariates,
         correction, rbord, use.gam, allcovar)
bigvaluerule(objfun, objargs, startpar, ...)
cannot.update(...)
check.separable(dmat, covname, isconstant, fatal)
## 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, ...) 
condSimCox(object, nsim, ..., window, n.cond, w.cond,
           giveup, maxchunk, saveLambda, verbose, drop)
damaged.ppm(object)
data.mppm(x)
deltasuffstat(model, ...,
              restrict, dataonly, sparseOK, quadsub,
              force, warn.forced, verbose, use.special)
## S3 method for class 'ppmInfluence'
dfbetas(model, ...)
diagnose.ppm.engine(object, ..., type, typename, opt,
                         sigma, rbord, compute.sd, compute.cts,
                         envelope, nsim, nrank,
                         rv, oldstyle, splineargs, verbose)
## S3 method for class 'msr'
dim(x)
## S3 method for class 'msr'
dimnames(x)
doMultiStraussHard(iradii, hradii, types)
dppDpcf(model, ...)
dppmFixIntensity(DPP, lambda, po)
dppmFixAlgorithm(algorithm, changealgorithm, clusters, startpar)
DPPSaddle(beta, fi)
DPPSaddlePairwise(beta, fi)
enet.engine(model, ..., standardize, lambda, alpha, adaptive) 
equalpairs(U, X, marked=FALSE)
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)
evalPairwiseTerm(fint, d)
expandDot(f, dotvars)
## S3 method for class 'slrm'
extractAIC(fit, scale = 0, k = 2, ...)
fakefii(model)
## S3 method for class 'hackglmmPQL'
family(object, ...)
## S3 method for class 'vblogit'
family(object, ...)
fill.coefs(coefs, required)
findCovariate(covname, scope, scopename=NULL)
fii(interaction, coefs, Vnames, IsOffset, vnameprefix)
## S3 method for class 'msr'
flipxy(X)
forbid.logi(object)
## S3 method for class 'hackglmmPQL'
formula(x, ...)
getdataname(defaultvalue, ..., dataname)
getglmdata(object, ...)
## S3 method for class 'ppm'
getglmdata(object, ..., drop=FALSE)
## S3 method for class 'mppm'
getglmdata(object, ...)
## S3 method for class 'slrm'
getglmdata(object, ...)
getglmfit(object, ...)
## S3 method for class 'ppm'
getglmfit(object, ...)
## S3 method for class 'mppm'
getglmfit(object, ...)
## S3 method for class 'slrm'
getglmfit(object, ...)
getglmsubset(object, ...)
## S3 method for class 'ppm'
getglmsubset(object, ...)
## S3 method for class 'mppm'
getglmsubset(object, ...)
## S3 method for class 'slrm'
getglmsubset(object, ...)
getppmdatasubset(object)
getppmOriginalCovariates(object)
geyercounts(U,X,r,sat,Xcounts,EqualPairs)
geyerdelta2(X,r,sat,...,sparseOK, correction)
GLMpredict(fit, data, coefs, changecoef, type)
hackglmmPQL(fixed, random, family, data, correlation, weights,
            control, niter, verbose, subset, ..., reltol)
hasglmfit(object)
## S3 method for class 'mppm'
hasglmfit(object)
## S3 method for class 'ppm'
hasglmfit(object)
## S3 method for class 'slrm'
hasglmfit(object)
hierarchicalordering(i, s)
hiermat(x, h)
ho.engine(model, ..., nsim, nrmh, start, control, verb)
illegal.iformula(ifmla, itags, dfvarnames)
impliedpresence(tags, formula, df, extranames=character(0))
impliedcoefficients(object, tag, new.coef)
## S3 method for class 'ppmInfluence'
influence(model, ...)
instantiate.interact(x, par)
interactionfamilyname(object)
intermaker(f, blank)
## S3 method for class 'ppm'
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 'rppm'
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 'rppm'
is.multitype(X, ...)
## S3 method for class 'slrm'
is.multitype(X, ...)
## S3 method for class 'mppm'
is.poisson(x)
## S3 method for class 'rppm'
is.poisson(x)
Kpcf.kppm(model, what)
## S3 method for class 'slrm'
Kmodel(model, ...)
killinteraction(model)
kppmComLik(X, Xname, po, clusters, control, stabilize, weightfun, rmax,
           algorithm, DPP, ..., pspace)
kppmMinCon(X, Xname, po, clusters, control, stabilize, statistic, statargs,
           algorithm, DPP, ..., pspace)
kppmPalmLik(X, Xname, po, clusters, control, stabilize, weightfun, rmax, 
           algorithm, DPP, ..., pspace)
kppmCLadap(X, Xname, po, clusters, control, weightfun, 
           rmax, epsilon, DPP, algorithm, ...,
           startpar, globStrat)
## S3 method for class 'ppm'
labels(object, ...)
## S3 method for class 'ppmInfluence'
leverage(model, ...)
## S3 method for class 'objsurf'
lines(x, ..., directed)
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, ...)
LurkEngine(object, type, cumulative, plot.sd, 
           quadpoints, wts, Z, subQset, 
           covvalues, resvalues, 
           clip, clipwindow, cov.is.im, covrange, 
           typename, covname,
           cl, clenv,
           oldstyle, check,
           verbose, nx, splineargs,
           envelope, nsim, nrank, Xsim,
           internal, checklength)
make.pspace(..., canonical, adjusted, trace, save, trajectory,
             nhalfgrid, strict, penalised, penalty,
             penal.args, tau, clusters, fitmethod,
             flatness, C0factor, xval, xval.args,
             debug, transfo)
mapInterVars(object, subs, mom)
Mayer(fi, exponent)
model.se.image(fit, W, ..., what, new.coef)
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)
newformula(old, change, eold, enew, expandpoly, dotvars)
newstyle.coeff.handling(object)
nndcumfun(X, ..., r)
no.trend.ppm(x)
objsurfEngine(objfun, optpar, objargs,
              ..., dotargs, objname,
              new.objargs, parmap, 
              ngrid, xlim, ylim, ratio, verbose)
optimConverged(x)
optimStatus(x, call)
optimNsteps(x)
outdated.interact(object)
oversize.quad(Q, ..., nU, nX, p)
PairPotentialType(pairpot)
## S3 method for class 'detpointprocfamily'
parameters(model, ...)
partialModelMatrix(X,D,model,callstring,...)
## 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 'lurk'
plot(x, ..., shade)
## S3 method for class 'minconfit'
plot(x, ...)
## S3 method for class 'parres'
plot(x, ...)
## S3 method for class 'qqppm'
plot(x, ..., limits=TRUE,
           monochrome=spatstat.options('monochrome'),
           limcol=if(monochrome) "black" else "red")
poisson.fits.better(object)
PoissonCompareCalc(object)
PoisSaddle(beta, fi)
PoisSaddleArea(beta, fi)
PoisSaddleGeyer(beta, fi)
PoisSaddlePairwise(beta, fi)
PPMmodelmatrix(object, data, ..., subset, Q, keepNA, irregular,
               splitInf)
## Default S3 method:
ppm(Q, trend, interaction,
       ..., covariates, data, covfunargs, subset, clipwin,
       correction, rbord, use.gam, method, forcefit,
       improve.type, improve.args, 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, rule.eps,
              geomsmooth)
## S3 method for class 'vblogit'
predict(object, newdata, type, se.fit, dispersion,
                          terms, na.action, ...)
## S3 method for class 'profilepl'
predict(object, ...)
printStatus(x, errors.only)
printStatusList(stats)
## S3 method for class 'addvar'
print(x, ...)
## S3 method for class 'bt.frame'
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 '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 'leverage.ppm'
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 'profilepl'
print(x, ...)
## S3 method for class 'qqppm'
print(x, ...)
## S3 method for class 'rppm'
print(x, ...)
## S3 method for class 'summary.mppm'
print(x, ..., brief)
## S3 method for class 'summary.slrm'
print(x, ...)
## S3 method for class 'vblogit'
print(x, ...)
quad.mppm(x)
quadBlockSizes(nX, nD, p, nMAX, announce)
## S3 method for class 'slrm'
reach(x, ...)
reduceformula(fmla, deletevar, verbose)
reincarnate.interact(object)
## S3 method for class 'msr'
rescale(X, s, unitname)
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)
## S3 method for class 'msr'
rotate(X, angle, ..., centre)
SaddleApprox(beta, fi, approx)
safeFiniteValue(x, default)
safePositiveValue(x, default)
## S3 method for class 'msr'
scalardilate(X, f, ...)
## S3 method for class 'influence.ppm'
shift(X, ...)
## S3 method for class 'leverage.ppm'
shift(X, ...)
## S3 method for class 'msr'
shift(X, ...)
signalStatus(x, errors.only)
## S3 method for class 'profilepl'
simulate(object, ...)
slr.prepare(CallInfo, envir, data, dataAtPoints, splitby, clip)
slrAssemblePixelData(Y, Yname, W, covimages, dataAtPoints, pixelarea)
slrmInfluence(model, what, ...)
## S3 method for class 'ppm'
spatialCovariateEvidence(model, covariate, ..., lambdatype,
          dimyx, eps, rule.eps, interpolate, jitter, jitterfactor,
          modelname, covname, dataname, subset, clip.predict) 
## S3 method for class 'slrm'
spatialCovariateEvidence(model, covariate, ..., lambdatype,
          jitter, jitterfactor,
          modelname, covname, dataname, subset, raster.action) 
spatialCovariateUnderModel(model, covariate, ...)
## S3 method for class 'ppm'
spatialCovariateUnderModel(model, covariate, ...)
## S3 method for class 'kppm'
spatialCovariateUnderModel(model, covariate, ...)
## S3 method for class 'dppm'
spatialCovariateUnderModel(model, covariate, ...)
## S3 method for class 'slrm'
spatialCovariateUnderModel(model, covariate, ...)
spatstatDPPModelInfo(model)
splitHybridInteraction(coeffs, inte)
sp.foundclass(cname, inlist, formalname, argsgiven)             
sp.foundclasses(cnames, inlist, formalname, argsgiven)
strausscounts(U,X,r,EqualPairs)
stripGLMM(object)
suffloc(object)
suffstat.generic(model, X, callstring)
suffstat.poisson(model, X, callstring)
## 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 'vblogit'
summary(object, ...)
## S3 method for class 'rppm'
terms(x, ...)
tweak.coefs(model, new.coef)
## 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 'ppm'
updateData(model, X, ..., warn)
## S3 method for class 'kppm'
updateData(model, X, ...)
## S3 method for class 'dppm'
updateData(model, X, ...)
## S3 method for class 'slrm'
updateData(model, X, ...)
varcountEngine(g, B, lambdaB, f, R, what)
versionstring.interact(object)
versionstring.ppm(object)
windows.mppm(x)

Details

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

Value

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

spatstat.model documentation built on May 29, 2024, 2:42 a.m.