From: A method for partitioning trends in genetic mean and variance to understand breeding practices
Scenario | Statistic | Concordance correlation | \({\widehat{\rho }}\) | \({\widehat{C}}_{b}\) | RMSD | ||||
---|---|---|---|---|---|---|---|---|---|
\({\widehat{\rho }}_{\tiny {\text{ c }}}\) | Lower | Upper | Est. | Lower | Upper | ||||
Medium accuracy | \(\mu _{a_t}\) vs. \(E\left( \widehat{{\mathbf{a}}}_t\right)\) | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.10 | 0.08 | 0.15 |
\(\sigma ^2_{a_t}\) vs. \(Var\left( \widehat{{\mathbf{a}}}_t\right)\) | 0.95 | 0.93 | 0.96 | 0.96 | 0.99 | 0.11 | 0.09 | 0.14 | |
High accuracy | \(\mu _{a_t}\) vs. \(E\left( \widehat{{\mathbf{a}}}_t\right)\) | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.15 | 0.11 | 0.20 |
\(\sigma ^2_{a_t}\) vs. \(Var\left( \widehat{{\mathbf{a}}}_t\right)\) | 0.87 | 0.83 | 0.90 | 0.97 | 0.89 | 0.18 | 0.15 | 0.21 |