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Section 3 shows indices for ranking networks' switches.
Further, TOPSIS was found to be more precise than SAW in ranking networks.
In the future, he tells us, privacy will be dead and our blazingly public lives will be broadcast by transparent ranking networks (think Klout and Peer Index on steroids).
We propose a set of three steps, each of which is designed to resolve a significant challenge encountered in the construction of real-world ranking networks.
Finally, we briefly comment on the limits of the maximum likelihood estimate (MLE) approach and Bayesian analysis in constructing corporative ranking networks.
A method based on a corporative kingdom model, as presented here, is coherent with these observations, and is therefore a more realistic tool for the analysis of rhesus macaque ranking networks.
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A special case of a corporative ranking network is the kingdom ranking network, in which each group is identified by a common biological linkage, such as matriline or common genetic descent.
Based upon the optimal ranking network, we list in Table 2 the rank coordinates computed for the members of each matriline in the macaque enclosure (Cage 5).
The cost of the corresponding optimal ranking network, using relation (1), is computed to be 55.02.
This ranking network is common in human society, but has rarely been studied using social network analysis [10].
The third step derives confidence bounds for desired empirical features of the computed ranking network by accommodating heterogeneous measurement error.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com