meclight(x, ...)
"meclight"(x, grouping, r = 1, fold = 10, ...)
"meclight"(formula, data = NULL, ..., subset, na.action = na.fail)
"meclight"(x, ...)
"meclight"(x, grouping, ..., subset, na.action = na.fail)
groups ~ x1 + x2 + ...
. That is, the response is the grouping factor and
the right hand side specifies the (non-factor) discriminators. na.omit
,
which leads to rejection of cases with missing values on any required variable.
(NOTE: If given, this argument must be named.) lda
.lda
error rate.lda
. In contrast to the reference function minimization is
done by Nelder-Mead in optim
.predict.meclight
data(iris)
meclight.obj <- meclight(Species ~ ., data = iris)
meclight.obj
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