On 26.04.2018 15:29, Zahra Sheikhbahaee wrote:
In my network, beside to the information of which two nodes create an edge, I have the information of the time duration which an edge has lasted. I included this information as weight and used them as the covariate of the SBM. The results seems more reasonable compared to not considering any weights. However, the number of blocks changes slightly in each time I ran my script with the piece of code given before. So I was wondering if I must run minimize_nested_blockmodel_dl function by determining the higher number of MCMC iterations as argument, and then I would get more accurate results with highest confidence interval or I just need to repeat this function in a loop and then compute the mean number of blocks? I hope my question makes sense.
You should run the algorithm multiple times, and choose the result with the smallest description length. You get this value via the method state.entropy().