| var {base} | R Documentation |
var computes the variance of x and the
covariance of x and y if x and y
are vectors. If x and y are matrices then
the covariance between the columns of x and the
the columns of y are computed.
var(x, y = x, na.rm = FALSE, use)
x |
a numeric matrix or vector. |
y |
a numeric matrix or vector. |
na.rm |
logical. |
use |
an optional character string giving a
method for computing covariances in the presence
of missing values. This must be one of "all.obs",
"complete.obs" or "pairwise.complete.obs",
with abbreviation being permitted. |
If na.rm is TRUE then the complete observations (rows)
are used to compute the variance. If na.rm is FALSE
and there are missing values, then var will fail.
The argument use can also be used for describing how
to handle missing values.
Specifying use = "all" is equivalent to specifying
na.rm = FALSE and specifying use = "pair" is equivalent to
na.rm = TRUE.
If use = "pair", then all the observations which are
complete for a pair of variables are used to compute the
covariance for that pair of variables.
This can result in covariance matrices which are not
positive semidefinite.
cov with the same functionality for the
multivariate case.
var(1:10)# 9.166667 var(1:5,1:5)# 2.5