Table 2.
Residual | Correlation | ||||
---|---|---|---|---|---|
Model for gi | AIC | variance§ | θ | Fitted value$ | TBV# |
Independent | 6789.1 | 51.89 | |||
Ridge Regression (RR) | 6418.5 | 28.17 | 0.734 | 0.889 | |
Spatial models | |||||
Linear | 6425.8 | 12.00 | 0.974 | 0.880 | |
Quadratic | 6418.5 | 28.17 | 0.734 | 0.889 | |
Power | 6428.9 | 12.16 | 0.99 | 0.974 | 0.879 |
Exponential | 6428.5 | 11.48 | 216.52 | 0.977 | 0.879 |
Gaussian | 6420.5 | 28.08 | 124.59 | 0.737 | 0.889 |
Spherical | 6427.8 | 11.96 | 959.97 | 0.974 | 0.880 |
§ The error variance was pooled with that for vi into a single residual variance.
$ The Pearson correlation between GEBV and fitted values (yi600) of the phenotyped individuals.
# The Pearson correlation between GEBV and true breeding values (TBV) of the non- phenotyped individuals.