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Figure 3: Likelihood contours in the (B0 μ+μ−) versus μ+μ−) plane.
Associated likelihood contours and one-dimensional likelihood scans are shown in Extended Data Fig. 6.
The SM branching fractions are assumed uncorrelated to each other, and their uncertainties are accounted for in the likelihood contours.
Likelihood contours for (B0 µ+µ−) versus are shown in Fig. 3. One-dimensional likelihood scans for both decay modes are displayed in the same figure.
Extended Data Fig. 6: Likelihood contours for the ratios of the branching fractions with respect to their SM prediction, in the versus plane.
Extended Data Figure 6: Likelihood contours for the ratios of the branching fractions with respect to their SM prediction, in the versus plane.
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Figure 1d shows the log-likelihood contours of the true speaker and the most competing speaker, their differences, and their difference accumulation that resulted from the speaker identification technique utilizing the conventional maximum likelihood (ML -based GML -based.
One of the reasons of this inexpedience can be the broadness of the likelihood surface contour with small block size.
The simple two-species maximum-likelihood analysis based on the simulation data indicated that if the alignment blocks are small, the likelihood surface contour plot becomes broad (supplementary fig. S3, Supplementary Material online).
To further compare gMOS with mgMOS we plotted the contours of the likelihood functions for the PM and MM values of the whole dataset for days 2 and 4 and found that mgMOS fitted the data better than gMOS (Fig. 2).
Figures 2(a)–(c) illustrate the contours of log-likelihood within certain ranges of the two model parameters.
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