The equivalent noise variance is expressed as σ ~ 2 = N 0 ~ 2 ⇒ σ ~ 2 = 1 2 SNR.
The total explained variance is expressed in adjusted R squares.
The prior variance is expressed as precision, which is simply the inverse of the variance.
Therefore, phenotypic variance was expressed for the "default" situation, i.e., for a population that consists of unrelated individuals.
The size of the GP practice level variance (between GP-practice variation) and the size of the individual-level variance are expressed relative to the overall variance.
Mean and variance are expressed in terms of the parameter λ > 0 as E { X } = 1 / λ and Var{ X} = 1/ λ, respectively [ 15].
The variance was expressed as squared correlation coefficients (R), interpreted as follows: < 0.1 very weak correlation; 0.1 0.25 weak; 0.25 0.50 moderate; 0.5 0.75 strong; 0.75 0.9 very strong; > 0.9 exceptionally strong correlation.
The additive genetic variance is expressed as: var [ g 1 g 2 ] = G 0 ⊗ A where A is the numerator relationship matrix and G 0 is a 2×2 covariance matrix with the purebred and crossbred variances in the diagonals and the covariances in the off-diagonals.
The normally distributed variances were expressed as the mean ± SD.
Note that all variances are expressed in proportion to the global model innovation variance V.10 The effective variances of the two component models are respectively (V_{P}=0.1311) and (V_{I}=0.01461). .
