This function computes false discovery rate (FDR) for sparse element of the true coefficients given threshold.
conf_fdr(x, y, ...)# S3 method for summary.bvharsp
conf_fdr(x, y, truth_thr = 0, ...)
FDR value in confusion table
summary.bvharsp object.
True inclusion variable.
not used
Threshold value when using non-sparse true coefficient matrix. By default, 0 for sparse matrix.
When using this function, the true coefficient matrix \(\Phi\) should be sparse. False discovery rate (FDR) is computed by $$FDR = \frac{FP}{TP + FP}$$ where TP is true positive, and FP is false positive.
Bai, R., & Ghosh, M. (2018). High-dimensional multivariate posterior consistency under global-local shrinkage priors. Journal of Multivariate Analysis, 167, 157-170.
confusion()