true_negative_rate

Computes the True Negative Rate (Specificity) between a
 reference matrix and an estimated matrix. TNR = TN / (TN + FP), where
 negatives are zero entries in the reference matrix.

A wrapper for sparse VAR (Vector Autoregression) and
VECM (Vector Error Correction Model) time series models estimation
using penalties like ENET (Elastic Net), SCAD (Smoothly Clipped
Absolute Deviation) and MCP (Minimax Concave Penalty).
Based on the work of Basu and Michailidis (2015)
<doi:10.1214/15-AOS1315>.

Simone Vazzoler

sparsevar

Sparse VAR (Vector Autoregression) / VECM (Vector Error
Correction Model) Estimation

true_negative_rate function

<dl><dt>reference_m</dt>
<dd>the reference (ground truth) matrix</dd>
<dt>a</dt>
<dd>the estimated matrix to compare against the reference</dd></dl>

Arguments

True Negative Rate — true_negative_rate

<dl>

<dt>reference_m</dt>
<dd>the reference (ground truth) matrix</dd>


<dt>a</dt>
<dd>the estimated matrix to compare against the reference</dd>

</dl>

true_negative_rate: True Negative Rate

Description

Usage

Value

Arguments