Description Usage Arguments Details Value See Also Examples
Dyadic algorithm using the Bolasso technique to order the variables
1  dyadiqueordre(data,Y,m,maxordre,var_nonselect,showtest,showordre,random)

data 
Input matrix of dimension n * p; each of the n rows is an observation vector of p variables. The intercept should be included in the first column as (1,...,1). If not, it is added. 
Y 
Response variable of length n. 
m 
Number of bootstrap iteration of the Lasso. Default is 
maxordre 
Number of variables to order. Default is min(n/21,p/21). 
var_nonselect 
Number of variables that don't undergo feature selection. They have to be in the first columns of data. Default is 1, the selection is not performed on the intercept. 
showtest 
Logical value. If TRUE, show the number of regularization parameters tested to show the steps of the algorithm. Default is FALSE. 
showordre 
Logical value. If TRUE, shows the ordered variables at each step of the algorithm. Default is TRUE. 
random 
optionnal parameter. Matrix of size n*m, the m bootstrap samples are constructed from the m columns. 
The algorithm starts from a large regularization parameter given by one run of Lasso. It proceeds by dyadic splitting until one variable is isolated; e.g one variable alone achieve a frequency of 1; it is the first ordered variable. And so on until maxordre
variables are ordered.
A 'bolasso' object is returned for which the method plot
is available.
data 
A list containing:

ordre 
The order obtained on the variables. 
mu 
Vector of the positive regularization sequence that was used in the algorithm. 
frequency 
Matrix of p rows. Appearance frequency of each variable for the regularization parameter in 
1 2 3 4 5 6 7 
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