simuBlockGaussian

Simulate n samples from a gaussian multivariate law with 0 vector mean and block diagonal variance matrix with 
diagonal 1 and block of rho.

It implements a new procedure of variable selection in the context of redundancy between explanatory variables, which holds true with high dimensional data (Grimonprez et al. (2023) <doi:10.18637/jss.v106.i03>).

Quentin Grimonprez

MLGL

Multi-Layer Group-Lasso

Samuel Blanck

Alain Celisse

Guillemette Marot

Yi Yang

Hui Zou

simuBlockGaussian function

<dl><dt>n</dt>
<dd>number of samples to simulate</dd>
<dt>nBlock</dt>
<dd>number of blocks</dd>
<dt>sizeBlock</dt>
<dd>size of blocks</dd>
<dt>rho</dt>
<dd>correlation within each block</dd></dl>

Arguments

Author

Simulate multivariate Gaussian samples with block diagonal variance matrix — simuBlockGaussian

<dl>

<dt>n</dt>
<dd>number of samples to simulate</dd>


<dt>nBlock</dt>
<dd>number of blocks</dd>


<dt>sizeBlock</dt>
<dd>size of blocks</dd>


<dt>rho</dt>
<dd>correlation within each block</dd>

</dl>

simuBlockGaussian: Simulate multivariate Gaussian samples with block diagonal variance matrix

Description

Usage

Value

Arguments

Author

Examples