cov.wt {stats} | R Documentation |
Returns a list containing estimates of the weighted covariance matrix and the mean of the data, and optionally of the (weighted) correlation matrix.
cov.wt(x, wt = rep(1/nrow(x), nrow(x)), cor = FALSE, center = TRUE)
x |
a matrix or data frame. As usual, rows are observations and columns are variables. |
wt |
a non-negative and non-zero vector of weights for each
observation. Its length must equal the number of rows of x . |
cor |
A logical indicating whether the estimated correlation weighted matrix will be returned as well. |
center |
Either a logical or a numeric vector specifying the
centers to be used when computing covariances. If TRUE , the
(weighted) mean of each variable is used, if FALSE , zero is
used. If center is numeric, its length must equal the number
of columns of x . |
The covariance matrix is divided by one minus the sum of squares of the weights, so if the weights are the default (1/n) the conventional unbiased estimate of the covariance matrix with divisor (n - 1) is obtained. This differs from the behaviour in S-PLUS.
A list containing the following named components:
cov |
the estimated (weighted) covariance matrix |
center |
an estimate for the center (mean) of the data. |
n.obs |
the number of observations (rows) in x . |
wt |
the weights used in the estimation. Only returned if given as an argument. |
cor |
the estimated correlation matrix. Only returned if
cor is TRUE . |