cov_offdiag_check: Covariance Off Diagonal Check
In ChrisDienes/SeaClass: Interactive GUI for analyzing a binary response variable

Description Usage Arguments Details Value See Also Examples

Converts a covariance matrix to a correlation matrix and then identifies variables which should be dropped due to high dependence.

1	cov_offdiag_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.

Intended to be a helper function for flagging highly dependent variables which 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 an action taken by the covariance check wrapper function cov_check().

cov_check

cov1 <- matrix(c(1,0,0,0,1,1,0,1,1),ncol=3,nrow=3)
cov2 <- diag(c(1,1,1))
cov_offdiag_check(cov1, cut_point = 0.9999)
cov_offdiag_check(cov2, cut_point = 0.9999)