Nothing
.imputation <- function(x, impMeth = c("norm" , "seq", "rseq"), alpha=0.5)
{
impMeth <- match.arg(impMeth)
if(is.data.frame(x))
x <- data.matrix(x)
else if (!is.matrix(x))
x <- matrix(x, length(x), 1,
dimnames = list(names(x), deparse(substitute(x))))
## drop all rows which contain only missings
na.x <- rowSums(ifelse(is.na(x),1,0)) == ncol(x)
ok <- !na.x
x <- x[ok, , drop = FALSE]
dx <- dim(x)
dimn <- dimnames(x)
n <- dx[1]
p <- dx[2]
if(impMeth == "norm")
{
## impute the missing data using package norm
s <- prelim.norm(x) # do preliminary manipulations
thetahat <- em.norm(s, showits=FALSE) # find the mle
rngseed(1234567) # set random number generator seed
ximp <- imp.norm(s, thetahat, x) # impute missing data under the MLE
}else if(impMeth == "seq")
{
ximp <- impSeq(x)
}else if(impMeth == "rseq")
{
ximp <- impSeqRob(x, alpha=alpha)$x
}else
stop("Undefined imputation method in .cov.na.imp(): ", impMeth)
return(ximp)
}
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