Usage
searchZ_sparse(X = X, Zi = NULL, Zj = NULL, Si = NULL, Sj = NULL,
Bic_null_vect = NULL, candidates = 2, methode = 1, p1max = 5,
Maxiter = 1, plot = F, best = T, better = F, random = T,
verbose = 1, nb_opt_max = NULL)
Arguments
Zi
indices of the rows of the 1
Zj
indices of the columns of the 1
Bic_null_vect
the BIC of the null hypothesis (used for independent variables)
candidates
0:row and column,-1:column only, int>0:random int candidates, -2 : all (but the diag), -3 : non-zeros
methode
parameter for OLS (matrix inversion) 1:householderQr, 2:colPivHouseholderQr
p1max
maximum complexity for a regression
plot
TRUE: returns for each step the type of move, complexity and BIC
best
TRUE: systematically jumps to the best BIC seen ever when seen (it is stored even if best=FALSE)
better
TRUE: systematically jumps to the best candidate if better than stationnarity (random wheighted jump otherwise)
random
if FALSE:moves only to improve and only to the best
verbose
0:none, 1:BIC,step and complexity when best BIC found 2:BIC, step, complexity, nb candidates and best candidate when best BIC found
nb_opt_max
stop criterion defining how many times the chain can walk (or stay) on the max found