fitadapLASSO: Fits adaptive lasso

In Saptati-Datta/AdapLasso: Computes Adaptive Lasso Using Lars Algorithm

Description

Fits adaptive lasso

Usage

fitadaplasso(
  X,
  Y,
  tuning_seq = NULL,
  len_tuning = 60,
  gamma = 0.01,
  eps = 0.001
)

Arguments

X	n x p design matrix of inputs
Y	n x 1 vector of outputs
tuning_seq	(optional)sequence of tuning parameters
len_tuning	length of desired tuning parameter sequence
gamma	a scalar(>0) input used in the weight(user input)
eps	precision level for convergence assessment, default 0.001

Value

tuning_seq	the actual sequence of tuning parameters used
beta_lamb	p x length(tuning_seq) matrix of corresponding solutions at each lambda value (original data without center or scale)
intercept_vec

Unscaled vector of intercepts for a fixed gamma and for different lambda values

Examples

#EXAMPLE 1
X <- matrix(rnorm(500), 50, 10)
Y <- rnorm(50)
gamma <- 2
# Fits adaptive adaplasso
fit <- fitadaplasso(X , Y , gamma = gamma)
# EXAMPLE 2
X <- matrix(rchisq(500, 3), 50, 10)
Y <- rbinom(50)
tuning_seq <- runif(100, 1, 2)
#Fits adaptive adaplasso
fit2 <- fitadaplasso(X, Y, tuning_seq = tuning_seq, gamma = 0.1, eps = 0.002 )

Saptati-Datta/AdapLasso documentation built on Dec. 18, 2021, 12:57 p.m.