conf_fdr {bvhar}

Evaluate the Sparsity Estimation Based on FDR

Description

This function computes false discovery rate (FDR) for sparse element of the true coefficients given threshold.

Usage

conf_fdr(x, y, ...)

## S3 method for class 'summary.bvharsp'
conf_fdr(x, y, truth_thr = 0, ...)

Arguments

x

summary.bvharsp object.

y

True inclusion variable.

...

not used

truth_thr

Threshold value when using non-sparse true coefficient matrix. By default, 0 for sparse matrix.

Details

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.

Value

FDR value in confusion table

References

Bai, R., & Ghosh, M. (2018). High-dimensional multivariate posterior consistency under global–local shrinkage priors. Journal of Multivariate Analysis, 167, 157–170.

See Also

confusion()