approximate cross-validation (ACV) methods may be slow and inaccurate in GLM problems with high data dimension

We are grateful to the reviewers for their helpful feedback. And we provide an efficiently computable upper bound on the error of our ACV method. We agree with R1 that we do not focus on asymptotic analysis. R1 suggests using principal components analysis (PCA) to reduce dimensionality of the covariate matrix. So, for (2), there is real interest in the full-covariate GLM.