betanew_lasso_cpp {LassoNet}

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

Details

See beta.update.net

Value

beta

updated \beta vector

steps

number of steps until convergence

Author(s)

Maintainer: Jonas Striaukas <[e-mail]>

References

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

Examples

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)