adjusted_eigen_values: Regularized eigen-values

In GabrielHoffman/mvIC: Multivariate Information Criteria to identify important predictors in high dimensional multivariate regression

Regularized eigen-values

Description

Regularized eigen-values for low rank matrix

Usage

adjusted_eigen_values(
  X,
  shrink.method = c("var_equal", "var_unequal", "none"),
  lambda
)

Arguments

X	data matrix
shrink.method	Shrink covariance estimates to be positive definite. Using "var_equal" assumes all variance on the diagonal are equal. This method is the fastest because it is linear time. Using "var_unequal" allows each response to have its own variance term, however this method is quadratic time. Using "none" does not apply shrinkge, but is only valid when there are very few responses
lambda	specify lambda instead of estimating (development, do not use)

GabrielHoffman/mvIC documentation built on Aug. 30, 2022, 7:58 p.m.