R: Weighted Covariance Matrices

Weighted Covariance Matrices

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`.

Returns a list containing estimates of the weighted covariance matrix and the mean of the data, and optionally of the (weighted) correlation matrix.

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`.