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Allow the model to add more randomness. Instead of setting the adoption rule to be deterministic, i.e. if exposure > threshold then adopt, it should be something like exposure > threshold + eps, where eps ~ F.
The text was updated successfully, but these errors were encountered:
I would like to apply your R package to predict a sequence of nodes that adopt a certain behavior. So at each time point I need only 1 new adopter. Which adopter that is depends on the diffusion from the node that adopted the behavior at t-1 towards the nodes at t and is probabilistic.
Will you add an option in the adoption rule in which one could sample a single new adopter based on a certain probability distribution?
That sounds like a nice option to add. In that case difussion would be a rather continuous process as described by a Poisson process. I believe that what you are describing may be available in the RSiena package, as the diffusion dynamics are described as a Poisson process.
Allow the model to add more randomness. Instead of setting the adoption rule to be deterministic, i.e. if exposure > threshold then adopt, it should be something like exposure > threshold + eps, where eps ~ F.
The text was updated successfully, but these errors were encountered: