The value of center
determines how column centering is
performed. If center
is a numeric-alike vector with length equal to
the number of columns of x
, then each column of x
has
the corresponding value from center
subtracted from it. If
center
is TRUE
then centering is done by subtracting the
column means (omitting NA
s) of x
from their
corresponding columns, and if center
is FALSE
, no
centering is done.
The value of scale
determines how column scaling is performed
(after centering). If scale
is a numeric-alike vector with length
equal to the number of columns of x
, then each column of
x
is divided by the corresponding value from scale
.
If scale
is TRUE
then scaling is done by dividing the
(centered) columns of x
by their standard deviations if
center
is TRUE
, and the root mean square otherwise.
If scale
is FALSE
, no scaling is done.
The root-mean-square for a (possibly centered) column is defined as
\(\sqrt{\sum(x^2)/(n-1)}\), where \(x\) is
a vector of the non-missing values and \(n\) is the number of
non-missing values. In the case center = TRUE
, this is the
same as the standard deviation, but in general it is not. (To scale
by the standard deviations without centering, use
scale(x, center = FALSE, scale = apply(x, 2, sd, na.rm = TRUE))
.)