cov_check: Covariance Check
In ChrisDienes/SeaClass: Interactive GUI for analyzing a binary response variable

Description Usage Arguments Details Value See Also Examples

Checks a covariance matrix and identifies variables which should be dropped due to zero variance or high dependence.

1	cov_check(cov, cut_point = 0.9999)

`cov`	a matrix.
`cut_point`	threshold which signifies two variables are highly dependent and one should be omitted. Specifically, when a group of variables are highly dependent, only the first variable is kept and all others are dropped. Defaults to 0.9999.

Used to flag variables which will likely cause the covariance matrix to be singular or near singular; and hence, non-invertible.

remove_vars locations of variables to be dropped.
remove_length number of variables to be dropped.
remove_text a message detailing the recommended action.

cov_diag_check, cov_offdiag_check

cov1 <- matrix(c(1,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1),ncol=4,nrow=4)
cov2 <- diag(c(1,1,1,1))
cov_check(cov1, cut_point = 0.9999)
cov_check(cov2, cut_point = 0.9999)