spatstat.model-internal | R Documentation |
Internal spatstat.model functions.
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, ...,
quad.args,
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, 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 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, 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 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 'exactppm'
response(object)
## 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)
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.
The return values of these functions are not documented, and may change without warning.
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