# NOT RUN {
# dataset generation
base = mixture_generator(n = 150, p = 10, valid = 0, ratio = 0.4, tp1 = 1, tp2 = 1, tp3 = 1,
positive = 0.5, R2Y = 0.8, R2 = 0.9, scale = TRUE, max_compl = 3,
lambda = 1)
X_appr = base$X_appr # learning sample
density = density_estimation(X = X_appr, detailed = TRUE) # estimation of the marginal densities
density$BIC_vect # vector of the BIC (one per variable)
density$BIC # global value of the BIC (sum of the BICs)
density$nbclust # vector of the numbers of components.
density$details # matrices that describe each Gaussian Mixture (proportions, means and variances)
# }
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