# BicZ: Compute the BIC of a given structure In CorReg: Linear Regression Based on Linear Structure Between Variables

## Description

Compute the BIC of a given structure

## Usage

 ```1 2``` ```BicZ(X = X, Z = Z, Bic_null_vect = NULL, Bic_old = NULL, methode = 1, Zold = NULL, star = FALSE) ```

## Arguments

 `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

## Value

The vector of the BICs associated to each covariate (conditionnal distribution) according to the sub-regression structure.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ``` ## Not run: require(CorReg) 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) ## End(Not run) ```

CorReg documentation built on April 24, 2018, 1:03 a.m.