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The performance of the method is investigated by computing several examples and error estimates of the approximation are stated.
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Changes in interaction forces between adjacent medium and large particles were investigated by computing the radial distribution function and the interaction potential.
The involvement of this phage in the observed pattern was investigated by computing data from the three quantitative experiments in a GLM.
Mating structure was investigated by computing FIS values per field as well as for the entire population.
Group differences were investigated by computing a general linear model of cortical thickness at each vertex of the cortical surface.
Whether this holds for a particular application can be investigated by computing correlations between GEBV after different numbers of iterations with "final" estimates, as outlined above.
The genomic organization among T6SS loci was investigated by computing the number of loci in which every pair of COGs could potentially be co-transcribed (i.e. two COGs are encoded in tandem and co-oriented).
Genetic diversity was investigated by computing the proportion of polymorphic loci (PPL) at the 5% level and Nei's gene diversity (Hj, analogous to He) using standardized sample sizes (i.e. with a maximum of eight samples per population).
The influence of parameters N, TF and RM was investigated by computing the Diagnostic Odds Ratio (DOR with 95% CI) from the relevant TN/FP and TP/FN data per parameter setting of each study parameter per alpha level (Table 1), using Meta-DiSc Version 1.4 statistical software.
Potential confounding factors were investigating by computing the significance of partial correlations between HER2 and AI while holding grade and ER constant as mitigating factors.
Effects of thermal diffusion and chemical kinetics on the flame structure are investigated by comparing computed results with experimental data.
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