mvIC_from_residuals: Evaluate multivariate BIC from matrix of residuals

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

Evaluate multivariate BIC from matrix of residuals

Description

Evaluate multivariate BIC from matrix of residuals

Usage

mvIC_from_residuals(
  residMatrix,
  m,
  criterion = c("BIC", "sum BIC", "AIC", "AICC", "CAIC", "sum AIC"),
  shrink.method = c("EB", "none", "var_equal", "var_unequal"),
  ...
)

Arguments

residMatrix	matrix of residuals where rows are features
m	number of parameters for each model
criterion	multivariate criterion ('AIC', 'BIC') or summing score assuming independence of reponses ('sum AIC', 'sum BIC')
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
...	other arguments passed to logDet

GabrielHoffman/mvBIC documentation built on Sept. 5, 2022, 1:57 a.m.