cov.wt
Weighted Covariance Estimation
Description
Returns a list containing estimates of the covariance matrix and
of the mean vector for the data, and optionally of the correlation matrix.
Usage
cov.wt(x, wt = rep(1/nrow(x), nrow(x)), cor = FALSE, center = TRUE,
method = c("unbiased", "ML"))
Arguments
| x |
a matrix of data. Rows represent observations and columns represent variables.
Only finite values are accepted.
|
| wt |
a vector of weights for each observation.
This vector must have the same length as the number of rows in x. Missing
values are not accepted. Weights should not be negative.
|
| cor |
a logical flag. If TRUE, then the estimated correlation matrix is
returned as a component of the answer. The default is FALSE.
|
| center |
a logical value or a numeric vector providing the center about which
the covariance is to be taken.
- If center is TRUE (the default), then the mean of each column is used.
- If center is FALSE, then zero is used for each variable.
- If center is numeric, then its length must equal the number of columns
in x.
|
| method |
a character string specifying whether to use the unbiased estimator (the default)
or the maximum likelihood estimator of the covariance matrix.
|
Value
returns a list with the following components:
| cov |
the estimated covariance matrix.
|
| center |
an estimate for the center (mean) of the data.
|
| wt |
the weights that were used in the computation.
This is returned only if the wt argument was given.
|
| n.obs |
the number of observations (rows) in x.
|
| cor |
the estimated correlation matrix for the data.
This is returned only if the input cor is TRUE.
|
See Also
Examples
cov.wt(Sdatasets::freeny.x) # unweighted estimate
cov.wt(Sdatasets::freeny.x, center=FALSE) # take covariance about zero