Summarizes a fitted normal-block model: model type, goodness-of-fit criteria, cluster sizes, and the density of the inferred network between blocks.
Usage
# S3 method for class 'NormalBlockBase'
summary(object, ...)Value
An object of class `summary.NormalBlockBase` (a list with the model's `who_am_I`, `criteria`, `cluster_sizes` and network `density`), printed with a dedicated [print.summary.NormalBlockBase()] method.
Examples
ex_data <- generate_normal_block_var_data(n = 50, p = 20, d = 1, q = 3)
data <- NormalBlockData$new(ex_data$Y, ex_data$X)
model <- normal_block(data, blocks = 3, control = NB_control(verbose = FALSE))
summary(model)
#> A diagonal normal-block-var model with 3 unknown blocks .
#> ===========================================================================
#> nb_param q n_edges sparsity loglik deviance BIC ICL EBIC niter
#> 48 3 3 0 -443.805 887.611 1075.388 809.619 1081.98 10
#> ===========================================================================
#> * Cluster sizes: 8, 9, 3
#> * Network: 3 edge(s), density = 1