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PLSR leads to models with maximal q2 values for the three properties of 0.74, 0.53 and 0.31, respectively.
The analyses presented allow the selection of optimal scoring models, with maximal discriminative power to distinguish true miRNA hairpins from other genomic (or random) hairpins for a selected set and a given data set.
The ROC statistic identified five potential models (with maximal performance on the LOOVC test): functional gene signatures containing 105, 107, 108, 109 and 111 features all attained ROC statistic = 0.814.
The data collected and analyses presented allowed the selection of optimal scoring models, with maximal discriminative power to distinguish true miRNA hairpins from other genomic (or random) hairpins for any given case.
β-Coefficients with 95% CIs were computed to assess the effect size of each predictor on the MMR, MMRAO and iAMR, and the change in the R was used to determine the final models with maximal goodness-of-fit, minimal number of explanatory variables and minimal collinearity.
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With our choice to include both small and large model versions, users can choose between a model with maximal predictive performance or a smaller model with slightly less predictive performance.
In the model with maximal control for confounding, the RR significantly increased by about 40% over the IQR of NO2.
Sequential modelling began with maximal models in which all putative explanatory variables were fitted simultaneously.
Nuclear RNaseP (not shown), on the other hand, is well separated from these three models with a maximal score of 24 bit.
The last case study illustrates the optimal design of experiments for estimating model parameters with maximal accuracy.
In contrast, grasshoppers, which are not time limited, exhibited spring stiffness that maximized elastic energy storage when modelled with a maximal muscle contraction.
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