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Because the three strains had distributions that did not differ in a statistically significant manner, samples were pooled to provide a more robust statistical population.
To prevent such behavior, more robust statistical methods are typically employed.
Sources were grouped by sub-region for a more robust statistical analysis.
Instead, we consider a more robust statistical approach based on multiple peaks in the CCF.
The need for a more robust statistical basis for models has prompted discussions on how model predictivity can be assessed [11, 12].
However, it is not clarified whether the heavy-tailed source distribution provides more robust statistical estimation for fewer time frames or not.
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Other techniques more robust to statistical inference could be used in the future as well.
This approach to topology comparison is more robust to statistical error than common ML procedures, and the analyses presented here were done using stepping stone integration, which is the most accurate method of estimating the marginal likelihoods of competing hypotheses currently available [ 24].
Then, in order to make more robust and unbiased statistical analysis, probes with a high proportion of missing values were removed from the dataset.
Furthermore, the greatly increased number of microarray chips used here (increased from 14 to 48) allowed for the use of a more robust ANOVA-based statistical analysis.
We are in the process of developing the random decoy structure model and deriving a more robust and reliable statistical model for the ligand-binding site search.
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