cscov {FoCo2} | R Documentation |
Cross-sectional covariance matrix approximation
Description
Extended version of the
FoReco::cscov
function, introducing two new approximations for the covariance matrix
(both shrunk and sample versions). Specifically, shrbe
/sambe
assume no correlation between experts, while shrbv
/sambv
assume no correlation between variables.
Usage
## S3 method for class 'shrbe'
cscov(comb = "shrbe", ..., n = NULL, p = NULL, matNA = NULL,
res = NULL, mse = TRUE, shrink_fun = NULL)
## S3 method for class 'sambe'
cscov(comb = "sambe", ..., n = NULL, p = NULL, matNA = NULL,
res = NULL, mse = TRUE)
## S3 method for class 'shrbv'
cscov(comb = "shrbv", ..., n = NULL, p = NULL, matNA = NULL,
res = NULL, mse = TRUE, shrink_fun = NULL)
## S3 method for class 'sambv'
cscov(comb = "sambv", ..., n = NULL, p = NULL, matNA = NULL,
res = NULL, mse = TRUE)
Arguments
comb |
A string specifying the reconciliation method.
|
... |
Arguments passed on to
|
n |
Total number of variables, |
p |
Total number of experts, |
matNA |
A ( |
res |
A list of |
mse |
If |
shrink_fun |
Shrinkage function of the covariance matrix,
|
Value
A (m \times m
) symmetric positive (semi-)definite matrix, with
m = \sum_{j = 1}^p n_j
, n_j \leq n
.
See Also
Other Optimal combination:
csmtc()
,
csocc()
,
occmat()