(3) Outfit MNSQ for CAT was determined by the average squared residuals (i.e., squared observation minus the expected score and then divided by the variance, see Additional file 1) across all items.
Part of the observed broadening is easily explained by thermal motions, since v2, the averaged squared speed, is proportional to T/m, where T is the temperature and m is the mass of the atom.
The performances of the different models were quantified by computing the average mean square error (AMSE), and the average correlation coefficient (ACC) between the true and estimated visual parameters, defined as ϵ = 1 4 T ∑ r = 1 4 1 σ v r 2 ∑ t = 1 T õ v r t - o v r t 2, (11) ρ = 1 4 T ∑ r = 1 4 ∑ t = 1 T ( o v r t - μ v r ) ( õ v r t - μ ~ v r ) σ v r σ ~ v r, (12).
How precisely the decoding can be done is assessed by calculating the average mean square error of the decoder.
Root mean squared (RMS) errors were calculated by subtracting the predicted values from the corresponding observed values, squaring them, and then taking the square root of the averaged squared errors.
Since averaging over all genes gives a much better estimate of residual variation than single gene estimates of error variance, we estimated the effect sizes for each of the three effects (genotype, treatment, and genotype × treatment) as standardized coefficients for each gene, i.e., by dividing the effects by the average of the square root of the residual variance over all genes.
Therefore, these half-sisters contributed little extra information for genomic prediction.> -wrap-foot> * r v is equal to the correlation between the estimated breeding and the DRP divided by the average of the square root of the reliability of the DRP in the validation cows.
The position estimation accuracy is measured by the average root-mean-square error (RMSE) in the form of RMSE = 1 K max ∑ k = 1 K max ∥ p ̂ k - p k ∥ 2 2, where Kmax is the tracking duration, and p ̂ k is obtained as in (6).
MSE was computed by the average of the squares of the differences between the estimate and the true value fixed by simulation.
Biomolecular systems were stable in the cMD and aMD simulations with the chosen E and α as shown by the average root-mean-square deviation of the Cα atoms of the protein and heavy atoms of ligands, as well as the average helical content of the helices during the simulations (Table 1).
