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Figure 3 Distribution of the size of collaboration events.
In Figure 12 we report the size distribution of collaboration events for the different PACS number.
In the model, agents represent nodes in a collaboration network and links between nodes represent collaboration events.
For the simulations, we take the number of agents, N, and the total number of collaboration events, E, from the respective empirical networks.
Hence, to the purpose of comparing R&D and co-authorship networks, we do not consider single-author papers and the size of the collaboration events starts from 2 in all of our plots.
The time-aggregated data about these collaboration events can be conveniently represented by means of a complex network, where the nodes are the actors, or agents as we denote them in the following, and the links are the recorded collaborations.
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We report the distributions of partners per collaboration event for the two analyzed data sets.
Following these approaches, we argue that activity reflects the propensity of an agent to participate in a collaboration event.
To study these, we analyzed the distributions of partners per collaboration event, (P(m)), in both considered data sets.
In the SDC alliance data set, the size of a collaboration event is the number of firms per R&D alliance, while in the co-authorship data set it is the number of co-authors per paper.
The two input parameters, size of the collaboration event, (m_{i}), and agent activity, (a_{i}), are obtained by sampling from the above distributions, (P(m)) and (P a)).
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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