useDynLib(robustbase, .registration=TRUE)

if(FALSE) {##MM
    stopifnot(require(codetoolsBioC), require(robustbase))
    findExternalDeps("robustbase")
}
importFrom("grDevices", dev.interactive, extendrange)
importFrom("graphics",
           abline, axis,
           box, legend, lines, matplot, mtext,
           panel.smooth, par, plot, points, strheight, text, title)
importFrom("stats", .lm.fit,
           aggregate, alias, as.formula, binomial,
           confint.lm, dummy.coef.lm, # want to register these as S3 {confint}{lmrob} and {dummy.coef}{..}
           coef, cor, cov, cov.wt, cov2cor, delete.response, deviance, dnorm, dpois,
           family, fitted, fivenum, formula,
           gaussian, glm, glm.fit, hatvalues,
           integrate, is.empty.model, lm.fit, lm.wfit,
           mad, mahalanobis, median, model.frame, model.matrix, model.matrix.lm,
           model.offset, model.response, model.weights,
           na.fail, na.omit, na.pass, napredict, naprint, naresid,
           nlminb, nls, nls.control, nobs,
           optim, optimize, pbinom, pchisq, pf, pgamma, pnorm, poisson, ppois,
           predict, printCoefmat, pt,
           qchisq, qnorm, qpois, qqline, qqnorm, qt, quantile,
           resid, residuals, residuals.lm, setNames, splinefun, symnum,
           terms, uniroot, var, vcov, weights, .checkMFClasses, .getXlevels,

           ## S3 generics (*not* shown yet by  findExternalDeps() above):
           anova, case.names, confint,
           dummy.coef, logLik, profile, variable.names
           )


## ^^^^ MASS has a bit more; take it as example
if(getRversion() >= "3.3.0") {
    importFrom("stats", sigma)
} else {
    export(sigma)
    S3method(sigma, nls)
}

importFrom("utils", globalVariables, str)

## MASS has many rlm S3 methods; should we use some of them - for rnls() ?!
## we also currently use MASS::cov.rob(); but probably only temporarily
importFrom("methods", is, new, setClass, setMethod, slot, "slot<-",
	   ## needed, e.g. for 'robustlmm' to work w/o warning:
	   as, "as<-", coerce, "coerce<-")

importFrom("DEoptimR", JDEoptim)

## Functions defined in this package
export(Sn, Qn, Qn.old,
       s_Sn, s_Qn, s_mad, s_IQR,

       summarizeRobWeights,
       wgt.himedian,

       h.alpha.n,
       covMcd, .MCDcons, .MCDcnp2, .MCDcnp2.rew, .MCDsingularityMsg,
       robMD, mahalanobisD, # <- still "internal"
       ltsReg,
       tolEllipsePlot,
       ## RENAME ?!? :
       covPlot, ltsPlot,
       ## NO! ddplot, distplot, chi2qqplot
       rrcov.control,##  << RENAME --- FIXME
       huberM,
       huberize,
       colMedians, rowMedians,
       covOGK, covGK, hard.rejection, scaleTau2,
       covComed,
       ## comedian, COM, -- not yet
       smoothWgt, .wgtFUN.covMcd, .wgtFUN.covComed,
       psiFunc, huberPsi, hampelPsi,
## Not yet:
##     tukeyPsi, # = biweight / bisquare
       tukeyChi, tukeyPsi1, # TODO deprecate: see ./TODO
       Mpsi, Mchi, Mwgt, MrhoInf, .Mpsi, .Mchi, .Mwgt, .MrhoInf,
       .Mwgt.psi1,
       .Mchi.tuning.default,  .Mpsi.tuning.default, .regularize.Mpsi,
       .Mchi.tuning.defaults, .Mpsi.tuning.defaults,
       .psi2ipsi, .psi.const, .psi.ggw.findc, .psi.lqq.findc,

       lmrob, lmrob.fit,
       lmrob.fit.MM, lmrob..M..fit, lmrob..D..fit,
       lmrob.S, lmrob.lar, lmrob.M.S,
       lmrob.control,
       .lmrob.hat, # was lmrob.leverages()
       splitFrame,
       outlierStats,

       mc, # Mia Hubers's medcouple
       lmc, rmc, # left and right mc, robust measures of tail weight
       adjbox,
       adjboxStats,
       adjOutlyingness,
       fullRank,
       glmrob,
       nlrob, nlrob.control
       , glmrobMqle.control, glmrobBY.control, glmrobMT.control
       , BYlogreg ## R/BYlogreg.R FIXME: add to glmrob() and "deprecate"
       ## , glmrobMT ## R/MTestimador2.R
       , estimethod
       ## related to detMCD() and to be used in rrcov etc:
       , r6pack, doScale
       , rankMM, classPC, .signflip
       )


## S3 methods for ``our own'' S3 generics:
S3method(ltsReg, default)
S3method(ltsReg, formula)

S3method(adjbox, default)
S3method(adjbox, formula)


## Register all the methods for S3 generics elsewhere
## in case namespace is loaded but not currently attached.

S3method(anova, lmrob)
S3method(anova, glmrob)

S3method(alias, lmrob)
S3method(case.names, lmrob)
S3method(confint,    lmrob, confint.lm)## -> R bug (see below) & in R/lmrob.R
S3method(confint, nlrob)
S3method(dummy.coef, lmrob, dummy.coef.lm)# (R bug ...)
S3method(estimethod, nlrob)
S3method(family, lmrob)
S3method(hatvalues, lmrob)
S3method(kappa, lmrob)
S3method(labels, lmrob)
S3method(model.matrix, lmrob)
S3method(nobs, lmrob)
S3method(nobs, lmrob.S, nobs.lmrob)# use the same as "lmrob"
S3method(nobs, mcd)
S3method(residuals, lmrob)
S3method(residuals, lmrob.S)
S3method(variable.names, lmrob)
S3method(print, lmrobCtrl)
S3method(update, lmrobCtrl)
## R Bug {fixed in svn rev 84463}: needs within.list in our NS:
S3method(within, lmrobCtrl, within.list)
S3method(weights, glmrob)
S3method(weights, lmrob)
S3method(weights, lmrob.S, weights.lmrob)# use the same as "lmrob"
S3method(weights, nlrob, weights.lmrob)# use the same as "lmrob"

S3method(formula, nlrob)
S3method(fitted, nlrob)
S3method(plot, lts)
S3method(plot, mcd)
S3method(plot, lmrob)
S3method(predict, lmrob)
S3method(predict, glmrob)
S3method(predict, nlrob)

S3method(print, glmrob)
S3method(print, lts)
S3method(print, mcd)
S3method(print, nlrob)
S3method(print, lmrob)
S3method(print, lmrob.S)
S3method(print, summary.glmrob)
S3method(print, summary.lmrob)
S3method(print, summary.nlrob)
S3method(print, summary.lts)

S3method(qr, lmrob)
## lmrob uses residuals.default
S3method(residuals, nlrob)
S3method(residuals, glmrob)

S3method(summary, glmrob)
S3method(summary, lmrob)
S3method(summary, lts)
S3method(summary, mcd)
S3method(summary, nlrob)

S3method(sigma, lmrob)
S3method(sigma, nlrob)
S3method(vcov, glmrob)
S3method(vcov, lmrob)
S3method(vcov, nlrob)
S3method(print, summary.mcd)

## S4 Generics {only those defined in this package}:
export(
       chgDefaults
       )

exportClasses(
              "functionX",   # function(x, <tune_par>): VECTORIZED in 'x'
              "functionXal", # a functional: function of tuning par.s only
              "psi_func"     # containing  rho(), psi(), psi'(), ...
              )

exportMethods(
              chgDefaults,
              plot
              )

