This function is useful to compute the likelihood for clusters obtained by different methods.
A MLVSBM object, the network data
A list of 2 vectors of integers of the same length as the number of node of each level.
A numeric, the log likelihood of the multilevel network for the given clustering.
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my_mlvsbm <- MLVSBM::mlvsbm_simulate_network( n = list(I = 40, O = 20), # Number of nodes for the lower level and the upper level Q = list(I = 2, O = 2), # Number of blocks for the lower level and the upper level pi = c(.3, .7), # Block proportion for the upper level, must sum to one gamma = matrix(c(.9, .2, # Block proportion for the lower level, .1, .8), # each column must sum to one nrow = 2, ncol = 2, byrow = TRUE), alpha = list(I = matrix(c(.8, .2, .2, .1), nrow = 2, ncol = 2, byrow = TRUE), # Connection matrix O = matrix(c(.99, .3, .3, .1), nrow = 2, ncol = 2, byrow = TRUE)),# between blocks directed = list(I = FALSE, O = FALSE), # Are the upper and lower level directed or not ? affiliation = "preferential") # How the affiliation matrix is generated mlvsbm_log_likelihood(mlv = my_mlvsbm, clustering = my_mlvsbm$memberships)
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