Research Article

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.
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