Evaluate the Sparsity Estimation Based on Precision

This function computes precision for sparse element of the true coefficients given threshold.

Usage

conf_prec(x, y, ...)

# S3 method for class 'summary.bvharsp'
conf_prec(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.

Value

Precision value in confusion table

Details

If the element of the estimate \(\hat\Phi\) is smaller than some threshold, it is treated to be zero. Then the precision is computed by $$precision = \frac{TP}{TP + FP}$$ where TP is true positive, and FP is false positive.

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()