

   var {base}                                   R Documentation

   CCoovvaarriiaannccee MMaattrriicceess

   DDeessccrriippttiioonn::

        `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.

   UUssaaggee::

        var(x, y = x, na.rm = FALSE, use)

   AArrgguummeennttss::

          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"', `"com-
             plete.obs"' or `"pairwise.complete.obs"', with
             abbreviation being permitted.

   DDeettaaiillss::

        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.

   SSeeee AAllssoo::

        `cov' with the same functionality for the multivariate
        case.

   EExxaammpplleess::

        var(1:10)# 9.166667

        var(1:5,1:5)# 2.5

