slasso (version 1.0.1)

slasso-package: Smooth LASSO Estimator for the Function-on-Function Linear Regression Model

Description

Implements the smooth LASSO estimator for the function-on-function linear regression model described in Centofanti et al. (2022) tools:::Rd_expr_doi("10.1016/j.csda.2022.107556").

Author

Fabio Centofanti, Matteo Fontana, Antonio Lepore, Simone Vantini

Details

Package:	slasso
Type:	Package
Version:	1.0.1
Date:	2026-01-19
License:	GPL (>= 3)

References

Centofanti, F., Fontana, M., Lepore, A., & Vantini, S. (2022). Smooth lasso estimator for the function-on-function linear regression model. Computational Statistics & Data Analysis, 176, 107556.

See Also

slasso.fr, slasso.fr_cv

Examples

# \donttest{
library(slasso)
data<-simulate_data("Scenario II",n_obs=150)
X_fd=data$X_fd
Y_fd=data$Y_fd
domain=c(0,1)
n_basis_s<-30
n_basis_t<-30
breaks_s<-seq(0,1,length.out = (n_basis_s-2))
breaks_t<-seq(0,1,length.out = (n_basis_t-2))
basis_s <- fda::create.bspline.basis(domain,breaks=breaks_s)
basis_t <- fda::create.bspline.basis(domain,breaks=breaks_t)

mod_slasso_cv<-slasso.fr_cv(Y_fd = Y_fd,X_fd=X_fd,basis_s=basis_s,basis_t=basis_t,
lambda_L_vec = 10^seq(0,1,by=1),lambda_s_vec = 10^-9,lambda_t_vec = 10^-7,
B0=NULL,max_iterations=10,K=2,invisible=1,ncores=1)
mod_slasso<-slasso.fr(Y_fd = Y_fd,X_fd=X_fd,basis_s=basis_s,basis_t=basis_t,
lambda_L = 10^0.7,lambda_s =10^-5,lambda_t = 10^-6,B0 =NULL,invisible=1,max_iterations=10)

plot(mod_slasso_cv)
plot(mod_slasso)
# }