R/discardSimilarModels.R

   1 #' Discard models which have the same relevant variables - for EMGLLF
   2 #'
   3 #' @param B1 array of relevant coefficients (of size p*m*length(gridlambda))
   4 #' @param B2 array of irrelevant coefficients (of size p*m*length(gridlambda))
   5 #' @param glambda grid of regularization parameters (vector)
   6 #' @param rho covariance matrix (of size m*m*K*size(gridLambda))
   7 #' @param pi weight parameters (of size K*size(gridLambda))
   8 #'
   9 #' @return a list with update B1, B2, glambda, rho and pi, and ind the vector of indices
  10 #'  of selected models.
  11 #' @export
  12 discardSimilarModels_EMGLLF = function(B1,B2,glambda,rho,pi)
  13 {
  14     ind = c()
  15     for (j in 1:length(glambda))
  16     {
  17         for (ll in 1:(l-1))
  18         {
  19             if(B1[,,l] == B1[,,ll])
  20                 ind = c(ind, l)
  21         }
  22     }
  23     ind = unique(ind)
  24     B1 = B1[,,-ind]
  25     glambda = glambda[-ind]
  26     B2 = B2[,,-ind]
  27     rho = rho[,,,-ind]
  28     pi = pi[,-ind]
  29
  30     return (list("B1"=B1,"B2"=B2,"glambda"=glambda,"rho"=rho,"pi"=pi,"ind"=ind))
  31 }
  32
  33 #' Discard models which have the same relevant variables
  34 #'   - for Lasso-rank procedure (focus on columns)
  35 #'
  36 #' @param B1 array of relevant coefficients (of size p*m*length(gridlambda))
  37 #' @param rho covariance matrix
  38 #' @param pi weight parameters
  39 #'
  40 #' @return a list with B1, in, rho, pi
  41 #' @export
  42 discardSimilarModels_EMGrank = function(B1,rho,pi)
  43 {
  44     ind = c()
  45     dim_B1 = dim(B1)
  46     B2 = array(0,dim=c(dim_B1[1],dim_B1[2],dim_B1[3]))
  47     sizeLambda=dim_B1[3]
  48     glambda = rep(0,sizeLambda)
  49
  50     suppressmodel = discardSimilarModels_EMGLLF(B1,B2,glambda,rho,pi)
  51     return (list("B1" = suppressmodel$B1, "ind" = suppressmodel$ind,
  52         "rho" = suppressmodel$rho, "pi" = suppressmodel$pi))
  53 }