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The fitting of the experimental data to the two models is illustrated by Figs. 12 and 13.
In SVMs, the function that decides the classification of the data to the two classes is f ( x ) = sign ∑ i = 1 n a i y i ( ϕ ( x i ), ϕ ( x ) ) - b (14).
We compare the fit of the data to the two Gaussian models vs. the one Gaussian model to see if the distribution is bimodal.
To examine any temporal shift in the number of assaults we refitted the above models restricting the data to the two separate time periods of 10 p.m.–2.59 a.m. and 3 a.m.–6 a.m.
Nevertheless, to better understand the role of some genes included in the deleted segments, we compared our data to the two single previously reported patients with a molecular characterization of the ring chromosome 6.
Each model was evaluated for two criteria, each corresponding to a particular test statistic: (1) the relative fit of the simulated data to the two hypotheses of evolution in L. arthemis (figure 1) and (2) the absolute fit of the simulated data to the species tree topology being tested.
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The COA reduced the multidimensional microarray data to the three most informative components describing the dataset.
We compared our aligned data to the eight empirically-determined annotation tracks as previously mentioned.
Finally, our analysis was limited to the admission data from the hospitals that provide admission data to the three states examined.
Fitting the data to the zero truncated Poisson distribution for retrieving correlation coefficients were done by the R-package 'gamlss.tr' [ 59].
We used the textile data to test the two hypotheses described above.
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