This can be explained from genetic and statistical perspectives.
The reported AUCs are disappointing ranging from 0.50 to 0.84, with one or two exceptions, which can be explained by statistical or methodological differences in study design.
The study found that the increase could not be explained by statistical anomalies, like a loosening in the criteria for diagnosis.
Of course, results for which the statistical significance was confirmed can hardly be explained by insufficient statistical power.
The differences between the results of these studies may be explained by methodological and statistical factors.
The discrepancy may be explained by differences in statistical power as well as methodologies.
This might be explained by a lack of statistical power.
This result might be explained by the fact that CoM2 exploits more statistical information from the signal (second and FO cumulants) than CCA (second-order cumulants).
The statistical properties of the SVM forecast error will be explained in this subsection.
From these statistical evaluations we conclude the following: First, the high number of periodic genes connected to the SCC cannot be explained by chance.
Statistical tests (stepwise regression with forward selection) reveal that each species distribution is explained by a characteristic set of relevant variables, ranging from soil type and dimension of the system, to nutrient and salinity concentration.
