Evaluate multivariate BIC from matrix of residuals

Evaluate multivariate BIC from matrix of residuals

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