MAR case: perform optimization only on observed values

[jchiquet]

At this stage of the development, we perform imputation even in the MAR case to keep the same framework, whatever the underlying sampling process (MAR or NMAR).

Not only it would save some time to eprform the inference only on the observed part of the surrogate loglikelihood, but it would also be more correct in the LMAR case with covariates.

I will create a branch for that, as it changes a bit the interface with the C++ code and also the structure of the R6 object. A elegant solution would be to handle NA in the C++, by only looping over the no-NA value of the network adjacency matrix.