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Selecting the counting condition as the more valid baseline measure, we obtained relatively stable lateralisation indices for the MCA with 1 of 10 measurements outside the 95% confidence interval.
In these cases, we adopted a policy penalty: in order to consider these unsuccessful participants, we doubled the respective measure we obtained (average value of the Euclidean distance) due to TTR 1.2 to be the one of jenny and IPO-TConfig.
When clustering with euclidean distance as the measure, we obtained three different clusters: one with all Bright images except B11 plus A23, A24; one with all All images except A21, A23 A25 and one with all Dim images plus A21, A25, B11.
Based on this ranking, for each outcome measure, we obtained a P-value for each individual patient.
Considering the median importance score over all homeodomains over all 2585 residues as a feature prioritization measure, we obtained the ranking of residues shown in Figure 3.
Replacing the shortest path to the closest source/end nodes by the average over all the shortest paths to all the source/end nodes, which would be a reasonable alternative measure, we obtained nearly identical results (data not shown).
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For this welfare measure we obtain the same qualitative results.
We would expect that the closer the source is to the receiver, the higher the power ratio measure we obtain.
Under the minimal martingale measure, we obtain a system of partial-differential-integral-equations satisfied by the European currency option prices.
Moreover, when μ is absolutely continuous with respect to the Lebesgue measure we obtain a result related to that in [[45], Theorem 4, p.101].
If (Omega= mathbb {Z}_) and μ is the counting measure, we obtain a simple sufficient condition for the Fatou inequality: Suppose that (Omega= mathbb {Z}_) and that μ is the counting measure.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com