conf_fnr: Evaluate the Sparsity Estimation Based on FNR

In bvhar: Bayesian Vector Heterogeneous Autoregressive Modeling

Evaluate the Sparsity Estimation Based on FNR

Description

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

Usage

conf_fnr(x, y, ...)

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

False negative rate (FNR) is computed by

FNR = \frac{FN}{TP + FN}

where TP is true positive, and FN is false negative.

Value

FNR 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()

bvhar documentation built on June 25, 2025, 9:07 a.m.