Internal spatstat.model functions.
accumulateStatus(x, stats)
active.interactions(object)
adaptcoef(new.coef, fitcoef, drop)
# S3 method for 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 summary.kppm
coef(object, ...)
# S3 method for summary.ppm
coef(object, ...)
# S3 method for summary.slrm
coef(object, ...)
# S3 method for 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 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 msr
dim(x)
# S3 method for 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 slrm
extractAIC(fit, scale = 0, k = 2, ...)
fakefii(model)
# S3 method for hackglmmPQL
family(object, ...)
# S3 method for vblogit
family(object, ...)
fill.coefs(coefs, required)
findCovariate(covname, scope, scopename=NULL)
fii(interaction, coefs, Vnames, IsOffset, vnameprefix)
# S3 method for msr
flipxy(X)
forbid.logi(object)
# S3 method for hackglmmPQL
formula(x, ...)
getdataname(defaultvalue, ..., dataname)
getglmdata(object, ...)
# S3 method for ppm
getglmdata(object, ..., drop=FALSE)
# S3 method for mppm
getglmdata(object, ...)
# S3 method for slrm
getglmdata(object, ...)
getglmfit(object, ...)
# S3 method for ppm
getglmfit(object, ...)
# S3 method for mppm
getglmfit(object, ...)
# S3 method for slrm
getglmfit(object, ...)
getglmsubset(object, ...)
# S3 method for ppm
getglmsubset(object, ...)
# S3 method for mppm
getglmsubset(object, ...)
# S3 method for 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 mppm
hasglmfit(object)
# S3 method for ppm
hasglmfit(object)
# S3 method for 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 ppmInfluence
influence(model, ...)
instantiate.interact(x, par)
interactionfamilyname(object)
intermaker(f, blank)
# S3 method for ppm
is.expandable(x)
is.interact(x)
# S3 method for mppm
is.marked(X, ...)
# S3 method for msr
is.marked(X, ...)
# S3 method for rppm
is.marked(X, ...)
# S3 method for slrm
is.marked(X, ...)
is.mppm(x)
# S3 method for mppm
is.multitype(X, ...)
# S3 method for msr
is.multitype(X, ...)
# S3 method for rppm
is.multitype(X, ...)
# S3 method for slrm
is.multitype(X, ...)
# S3 method for mppm
is.poisson(x)
# S3 method for rppm
is.poisson(x)
Kpcf.kppm(model, what)
# S3 method for 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 ppm
labels(object, ...)
# S3 method for ppmInfluence
leverage(model, ...)
# S3 method for objsurf
lines(x, ..., directed)
logi.engine(Q, trend, interaction, ...,
quad.args,
covariates, subsetexpr, clipwin,
correction, rbord, covfunargs, allcovar,
vnamebase, vnameprefix, justQ, savecomputed, precomputed,
VB)
# S3 method for 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, quad.args, 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 detpointprocfamily
parameters(model, ...)
partialModelMatrix(X,D,model,callstring,...)
# S3 method for slrm
pcfmodel(model, ...)
ploterodewin(W1, W2, col.edge, col.inside, do.plot, ...)
ploterodeimage(W, Z, ..., Wcol, rangeZ, colsZ, do.plot)
# S3 method for addvar
plot(x, ..., do.points=FALSE)
# S3 method for lurk
plot(x, ..., shade)
# S3 method for minconfit
plot(x, ...)
# S3 method for parres
plot(x, ...)
# S3 method for 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)
# S3 method for default
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, quad.args, 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 vblogit
predict(object, newdata, type, se.fit, dispersion,
terms, na.action, ...)
# S3 method for profilepl
predict(object, ...)
printStatus(x, errors.only)
printStatusList(stats)
# S3 method for addvar
print(x, ...)
# S3 method for bt.frame
print(x, ...)
# S3 method for diagppm
print(x, ...)
# S3 method for detpointprocfamily
print(x, ...)
# S3 method for detpointprocfamilyfun
print(x, ...)
# S3 method for hierarchicalordering
print(x, ...)
# S3 method for influence.ppm
print(x, ...)
# S3 method for interact
print(x, ..., family, brief, banner)
# S3 method for intermaker
print(x, ...)
# S3 method for isf
print(x, ...)
# S3 method for leverage.ppm
print(x, ...)
# S3 method for lurk
print(x, ...)
# S3 method for minconfit
print(x, ...)
# S3 method for mppm
print(x, ...)
# S3 method for msr
print(x, ...)
# S3 method for parres
print(x, ...)
# S3 method for plotppm
print(x, ...)
# S3 method for profilepl
print(x, ...)
# S3 method for qqppm
print(x, ...)
# S3 method for rppm
print(x, ...)
# S3 method for summary.mppm
print(x, ..., brief)
# S3 method for summary.slrm
print(x, ...)
# S3 method for vblogit
print(x, ...)
quad.mppm(x)
quadBlockSizes(nX, nD, p, nMAX, announce)
# S3 method for slrm
reach(x, ...)
reduceformula(fmla, deletevar, verbose)
reincarnate.interact(object)
# S3 method for 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 exactppm
response(object)
# S3 method for msr
rotate(X, angle, ..., centre)
SaddleApprox(beta, fi, approx)
safeFiniteValue(x, default)
safePositiveValue(x, default)
# S3 method for msr
scalardilate(X, f, ...)
# S3 method for influence.ppm
shift(X, ...)
# S3 method for leverage.ppm
shift(X, ...)
# S3 method for msr
shift(X, ...)
signalStatus(x, errors.only)
# S3 method for profilepl
simulate(object, ...)
slr.prepare(CallInfo, envir, data, dataAtPoints, splitby, clip)
slrAssemblePixelData(Y, Yname, W, covimages, dataAtPoints, pixelarea)
slrmInfluence(model, what, ...)
# S3 method for ppm
spatialCovariateEvidence(model, covariate, ..., lambdatype,
dimyx, eps, rule.eps, interpolate, jitter, jitterfactor,
modelname, covname, dataname, subset, clip.predict)
# S3 method for slrm
spatialCovariateEvidence(model, covariate, ..., lambdatype,
jitter, jitterfactor,
modelname, covname, dataname, subset, raster.action)
spatialCovariateUnderModel(model, covariate, ...)
# S3 method for ppm
spatialCovariateUnderModel(model, covariate, ...)
# S3 method for kppm
spatialCovariateUnderModel(model, covariate, ...)
# S3 method for dppm
spatialCovariateUnderModel(model, covariate, ...)
# S3 method for 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 mppm
summary(object, ..., brief=FALSE)
# S3 method for msr
summary(object, ...)
# S3 method for profilepl
summary(object, ...)
# S3 method for vblogit
summary(object, ...)
# S3 method for rppm
terms(x, ...)
tweak.coefs(model, new.coef)
# S3 method for msr
unitname(x)
# S3 method for msr
unitname(x) <- value
# S3 method for ippm
update(object, ..., envir)
# S3 method for msr
update(object, ...)
# S3 method for ppm
updateData(model, X, ..., warn)
# S3 method for kppm
updateData(model, X, ...)
# S3 method for dppm
updateData(model, X, ...)
# S3 method for slrm
updateData(model, X, ...)
varcountEngine(g, B, lambdaB, f, R, what)
versionstring.interact(object)
versionstring.ppm(object)
windows.mppm(x)The return values of these functions are not documented, and may change without warning.
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.