.mt.BLIM
.mt.RandSeed
.mt.naNUM
mt.number2na(x,na)
mt.na2number(x,na)
mt.getmaxB(classlabel,test,B, verbose)
mt.transformL(classlabel,test)
mt.transformV(V,classlabel,test,na,nonpara)
mt.transformX(X,classlabel,test,na,nonpara)
mt.checkothers(side="abs",fixed.seed.sampling="y", B=10000,
na=.mt.naNUM, nonpara="n")
mt.checkX(X,classlabel,test)
mt.checkV(V,classlabel,test)
mt.checkclasslabel(classlabel,test)
mt.niceres<-function(res,X,index)
mt.legend(x, y = NULL, legend, fill = NULL, col = "black", lty, 
    lwd, pch, angle = 45, density = NULL, bty = "o", bg = par("bg"), 
    pt.bg = NA, cex = 1, pt.cex = cex, pt.lwd = lwd, xjust = 0, 
    yjust = 1, x.intersp = 1, y.intersp = 1, adj = c(0, 0.5), 
    text.width = NULL, text.col = par("col"), merge = do.lines && 
        has.pch, trace = FALSE, plot = TRUE, ncol = 1, horiz = FALSE,...)
corr.Tn(X, test, alternative, use = "pairwise") 
diffs.1.N(vec1, vec2, e1, e2, e21, e22, e12) 
IC.Cor.NA(IC, W, N, M, output) 
IC.CorXW.NA(X, W, N, M, output)
insert.NA(orig.NA, res.vec)
marg.samp(marg.null, marg.par, m, B, ncp)