LassoNet (version 0.8.3)

betanew_lasso_cpp: C++ subroutine that updates \(\beta\) coefficients.

Description

This function updates \(\beta\) for given penalty parameters.

Usage

betanew_lasso_cpp(xx, xy, beta, M, y, Lambda1, Lambda2, iter, tol)

Arguments

xx

Bx matrix

xy

By vector

beta

initial value for \(\beta\); default - zero vector of size \(p \times 1\)

M

penalty matrix

y

response vector or size \(n \times 1\)

Lambda1

lasso penalty parameter

Lambda2

network penalty parameter

iter

maximum number of iterations for \(\beta\) step

tol

convergence tolerance level

Value

beta

updated \(\beta\) vector

steps

number of steps until convergence

Details

See beta.update.net

References

Weber, M., Striaukas, J., Schumacher, M., Binder, H. "Network-Constrained Covariate Coefficient and Connection Sign Estimation" (2018) <doi:10.2139/ssrn.3211163>

Examples

# NOT RUN {
p<-200
n<-100
beta.0=array(1,c(p,1))
x<-matrix(rnorm(n*p),n,p)
y<-rnorm(n,mean=0,sd=1)
lambda1<-1
lambda2<-1
M1<-diag(p)
updates<-beta.update.net(x, y, beta.0, lambda1, lambda2, M1)
# }