mice
.is.passive(string)
.norm.draw(y, ry, x)
padModel(data, method, predictorMatrix, visitSequence, post,
nmis, nvar)
.pmm.match(z, yhat = yhat, y = y)
sampler(p, data, m, imp, r, visitSequence, fromto, printFlag)
squeeze(x, bounds = c(min(x[r]), max(x[r])), r = rep(TRUE,
length(x)))
augment(y, ry, x)
remove.lindep(x, y, ry, eps = 0.0001, maxcor = 0.99)
find.collinear(x, threshold=0.999)
updateLog(out=NULL, meth=NULL, frame=2)