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Over successive generations, models were evolved towards a state of pure epistasis and maximal penetrance table variance (PTV) in an effort to generate interesting models.
We evaluate three metrics as predictors of relative model detection difficulty derived from previous works: (1) Penetrance table variance (PTV), (2) customized odds ratio (COR), and (3) our own Ease of Detection Measure (EDM), calculated from the penetrance values and respective genotype frequencies of each simulated genetic model.
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Intensity differences between genes were the largest contributor, accounting for 79% of the variation (Table 3, variance %).
Table 1 Variance components and percentage Effect Holistic scoring Analytic scoring Variance component % of Total variance Variance component % of Total variance Person 2.53 78 2.92 82 Rater 0.13 4 0.05 2 Error 0.56 18 0.56 17.
Table 1 Variance and AIC for each model Model Variance AIC PREM 133.4 – PREM with time shift 76.2 1620.3 CG6 76.2 1585.6.
Table 6 Variance decompositions after ten periods Variables Percentage of the variance explained by Immigration penetration Regional employment rate disparities Immigration penetration 0.997 0.003 Regional employment rate disparities 0.065 0.935.
Table 9 Variance decomposition result for all companies Period aS.E.
Table 3 Variance decomposition Proxy variables forp Mean Decomposition Std.
Table 5 Variance Decomposition of Pakistan Stock Exchange Pre-crises period Post-crises period Period S.E.
Table 7 Variance ratios of the differentials and F test results (**p 0.05) of the TFIDF and MaxConf (DF) temporal clusters of 7 Net Shopping TFIDF MaxConfnf (DF) Variance Var.
Table 8 Variance ratios of the differentials and F test results (**p < 0.05) of the TFIDF and MaxConf (DF) temporal clusters of AmazonJP TFIDF MaxConK (DF) Variance Var.
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