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A key issue in large-scale proteomic analysis is the accuracy and precision of the changes measured.
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In addition, they are experimentally evaluated in terms of both the quality of the maintained SPL models and the precision of the impact change management.
The corresponding algorithm is based on iterative instantiations of weighted group Lasso, which is capable of enhancing the sparsity of the solution [33, 34], and thus improving the precision of the detected change points.
The precision of the fold change estimation varied according to the abundance of the transcripts, demonstrating increased variation in the observed values for lower concentrations of standards for both nanofluidic and standard real-time PCR approaches.
At this time, the accuracy and the precision measures of the change-point estimators are computed.
Then, the averages, the standard deviations, the mean square errors, and the precision performances of the change-point estimates in addition to the expected time when the control chart signals a change are summarized in Table 4.
Following a signal from the control chart, the averages, the standard deviations, the mean square errors, and the precision performances of the change-point estimates in 1,000 simulation runs are reported in Table 5.
Finally, Tables 5 and 6 contain the averages, the standard deviations, and the precision performances of the change-point estimates under a step shift in the error variance from (sigma_{0}^{2}) to (sigma_{1}^{2} = gamma sigma_{0}^{2}).
Then, the averages, the standard deviations, the mean square errors, and the precision performances of the change-point estimates for 1,000 simulation runs are reported in Tables 2 and 3 for δ < 1 and δ > 1, respectively.
The subgroup averages are plotted on the proposed control chart until a signal is generated, and at this time, the accuracy and the precision measures of the change-point estimators are computed.
In its role as a nemesis, heterogeneity can reduce the precision of estimates, change the shape of a population model, or reduce the generalizability of study results.
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