rowMean_if calculates the mean of every row in a numeric or logical
matrix conditional on the frequency of observed data. If the frequency of
observed values in that row is less than (or equal to) that specified by
ov.min, then NA is returned for that row.
numeric or logical matrix. If not a matrix, it will be coerced to one.
minimum frequency of observed values required per row. If
logical vector of length 1 specifying whether
logical vector of length 1 specifying whether the mean
should be calculated if the frequency of observed values in a row is
exactly equal to
Conceptually this function does:
apply(X = x, MARGIN = 1, FUN =
mean_if, ov.min = ov.min, prop = prop, inclusive = inclusive). But for
computational efficiency purposes it does not because then the observed
values conditioning would not be vectorized. Instead, it uses
and then inserts NAs for rows that have too few observed values
numeric vector of length =
nrow(x) with names =
rownames(x) providing the mean of each row or NA depending on the
frequency of observed values.
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