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The F1 measure is the harmonic mean of precision (P) and recall (R) (i.e. F1 = 2 PR/(P + R)) for the estimated graphs, and can be used to compare the performance of estimators in networks with different structures.
Thus the bin sizes of the estimated graphs are more than 10 µm.
To further investigate the effect of the truncating lasso penalty, it is helpful to examine the adjacency matrix of the estimated graphs.
Figure 11 shows the true graph and estimated graphs by three different models and Table 8 summarizes the true positive rate and false discovery rate by three models.
This distribution results from comparing two estimated graphs from two data sets which differ just by random fluctuations.
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Moreover, the flip ambiguity problem [15], defined as the phenomenon where the estimated graph of the network is locally translated, rotated, and/or reflected, can arise.
The sparsity of the estimated graph increases when ρ increases.
We then describe a classification algorithm that models the observed conditions using the already estimated graph structure.
Ĝ* T 100, where Ĝ* T T B is the estimated graph based on the B-th bootstrap sample.
However, there is a need to develop more rigorous methods for assessing the reliability of the estimated graph.
All meta-analyses risk estimates, graphs and plots were performed using STATA, version 12.1.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com