R/dantzig.R

In fastclime: A Fast Solver for Parameterized LP Problems, Constrained L1 Minimization Approach to Sparse Precision Matrix Estimation and Dantzig Selector

#-------------------------------------------------------------------------------#
# Package: fastclime                                                            #
# dantzig(): Dantzig Selector Function                                          #
# Authors: Haotian Pang, Di Qi, Han Liu and Robert Vanderbei                    #
# Emails: <hpang@princeton.edu>, <hanliu@princeton.edu> and <rvdb@princetonedu> #
# Date: April 22th 2016                                                           #
# Version: 1.4.1					                                            #
#-------------------------------------------------------------------------------#
dantzig <- function(X, y, lambda = 0.01, nlambda = 50)
{
    n0<-nrow(X)
    d0<-ncol(X)
    BETA0<-matrix(0,d0,nlambda)
    lambdalist<-matrix(0,nlambda,1)
    
    cat("compute X^TX and X^y \n")
    
    X2=t(X)%*%X
    Xy=t(X)%*%y
    
    cat("start recovering \n")
    
    # start.time <- Sys.time()
    str=.C("dantzig", as.double(X2), as.double(Xy), as.double(BETA0), 
        as.integer(d0), as.double(lambda), as.integer(nlambda), as.double(lambdalist), PACKAGE="fastclime")
    # end.time <- Sys.time()
    # t0 <- end.time - start.time

    # ptm <- proc.time()
    # cat("prepare the solution path \n")
    # proc.time() - ptm
    # print(ptm)

    rm(X2,Xy)
    BETA0<-matrix(unlist(str[3]),d0,nlambda)
    lambdalist<-unlist(str[7])

    validn<-sum(lambdalist>0)

    BETA0<-BETA0[,1:validn]

    final_lambda<-lambdalist[validn]
    cat("lambdamin is ", final_lambda,"\n")
    
    lambdalist<-lambdalist[1:validn]
    result<-list("X" = X, "y"=y, "BETA0"=BETA0, "n0"=n0, "d0"=d0, "validn"=validn, "lambdalist"=lambdalist)

    gc()
    class(result) = "dantzig"
    cat("Done! \n")
    
    return(result)
    
}