Description Usage Arguments Value Examples
Compute the BIC of a given structure
1 2 3 4 5 6 7 8 9 |
X |
the dataset |
Z |
binary adjacency matrix of the structure (size p) |
Bic_null_vect |
the BIC of the null hypothesis (used for independent variables) |
Bic_old |
BIC (vector) associated to Zold |
methode |
parameter for OLS (matrix inversion) methode_BIC parameter for OLS (matrix inversion) 1:householderQr, 2:colPivHouseholderQr |
Zold |
another structure with some common parts with Z (allows to compute only the differences, to be faster) |
star |
boolean defining wether classical BIC or BIC* (over-penalized by a hierarchical uniform assumption to avoid over-learning)is computed |
The vector of the BICs associated to each covariate (conditionnal distribution) according to the sub-regression structure.
1 2 3 4 5 6 7 | data = mixture_generator(n = 15, p = 5, valid = 0) # dataset generation
Z = data$Z # binary adjacency matrix that describes correlations within the dataset
X = data$X_appr
Bic_null_vect = density_estimation(X = X)$BIC_vect
# Computes the BIC associated to each covariate (optional, BicZ can do it if not given as an input)
# computes the BIC associated to the structure
res = BicZ(X = X, Z = Z, Bic_null_vect = Bic_null_vect)
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