F-Ratio Test and Hypothesis Weighting: A Methodology to Optimize Feature Vector Size
Figure 1
Outcome of an artificially generated signal with fixed effect (o) for our test statistics (testat0 (16) versus (15), logarithmic scale) compared to outcomes of the corresponding random effects (). The deviation from the expected value (solid line) of the latter is highly significant and below the 5% level (dash-dotted line) and even the 1% level (dotted line). The classical method according to Section 2.1 revealed the (insignificant) 13.95% level only. The proposed method recognizes the nonrandom effect correctly in this example while the classical approach does not.