Description Usage Arguments Value Examples
View source: R/density_estimation.R
Estimates the density of each covariates with gaussian mixture models and then gives the associated BIC.
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X |
the dataset (matrix) |
nbclustmax |
max number of clusters in the gaussian mixtures |
nbclustmin |
min number of clusters in the gaussian mixtures |
verbose |
verbose or not |
detailed |
boolean to give the details of the mixtures found |
max |
boolean. Use an heuristic to shrink nbclustmax according to the number of individuals in the dataset |
package |
package to use ("Rmixmod", "mclust") |
nbini |
number of initial points for Rmixmod |
matshape |
boolean to give the detail in matricial shape |
... |
additional parameters |
a list that contains:
BIC_vect |
vector of the BIC (one per variable) |
BIC |
global value of the BIC ( |
nbclust |
vector of the numbers of components |
details |
list of matrices that describe each Gaussian Mixture (proportions, means and variances) |
1 2 3 4 5 6 7 8 9 10 | # 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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