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GrossSBM / missSBM

An R package for adjusting Stochastic Block Models from networks data sampled under various missing data conditions
http://grosssbm.github.io/missSBM
GNU General Public License v3.0
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Initial imputation in missSBM-fit is probably not adapted to cases with covariates #22

Closed jchiquet closed 5 years ago

jchiquet commented 5 years ago

Maybe related to #21, the following code for first estimation of pi in missSBM-fit is relevant for problem without covariates (when private$pi is indeed the mathematical matrix of connectivity between blocks)

https://github.com/jchiquet/missSBM/blob/18c3959d60ae4cf12039e37492987e89a8702253/R/missingSBM_fit.R#L32-L37

However, when private$pi represent gamma, as it is the case for the model with covariatess, we should adapt this first initialization and imputation. It has been show to be crucial in order to reproduce properly the resuts found with @TabouyT 's implementation.

So @TabouyT , comment initialises-tu les pi/gamma dans le modèles avec covariables ?

TabouyT commented 5 years ago

Je fais comme dans le SBM sans covariables, je mets des 0 à la place des NA, et j'utilise la classification initiale du spectral clustering pour calculer l'estimateur de pi. Puis, je dis que gamma c'est le logit de pi.

jchiquet commented 5 years ago

J'ai trouver un truc dégueux qui semble fonctionner (au moins aussi bien que ton code). On en reste là pour l'instant...