Each predictor variable x i (i = 1, 2,..., d) is standardized before presentation to the network, so as to have zero mean and unit standard deviation, because standardization has been shown to increase the efficiency of ANN training.
Both the spatial and temporal semi-variograms were fitted with an asymptotic value (the sill) of one since the standardized flows have a unit standard deviation.
Prior to each analysis, LRS values were corrected for differences between cohort years and areas, and standardized to zero mean and unit standard deviation.
Outcome variables were Winsorized at the 1st percentile and standardized with zero mean and unit standard deviation.
Since the studied characters are of different types (size, ratio, ordinal), the PCA has been performed on the correlation matrix (data standardized to mean zero and unit standard deviation) for all characters.
Conveniently, standardization leads to zero mean and unit standard deviation over the genome (see Methods and Figures 1 2).
Each study dataset is then standardized to have zero mean and unit standard deviation.
To facilitate the interpretation of main and interaction effects, all of the continuous independent variables were standardized to have zero mean and unit standard deviation [ 33].
On the other hand, the pairwise distances between two samples are large or even huge mathematically, even if each sample is standardized as a zero-mean point with unit standard deviation.
All variables used in selection analyses were standardized to a mean of zero with unit standard deviation, except our fitness variable (survival), which was scaled by the mean [ 32, 42].
Prior to integration of the four data sets each gene expression was standardized to the distribution of the mean of zero and unit standard deviation (z-score transformation).
