| simulate_data {slasso} | R Documentation |
Simulate data through the function-on-function linear regression model
Description
Generate synthetic data as in the simulation study of Centofanti et al. (2020).
Usage
simulate_data(scenario, n_obs = 3000, type_x = "Bspline")
Arguments
scenario |
A character strings indicating the scenario considered. It could be "Scenario I", "Scenario II", "Scenario III", and "Scenario IV". |
n_obs |
Number of observations. |
type_x |
Covariate generating mechanism, either Bspline or Brownian. |
Value
A list containing the following arguments:
X: Covariate matrix, where the rows correspond to argument values and columns to replications.
Y: Response matrix, where the rows correspond to argument values and columns to replications.
X_fd: Coavariate functions.
Y_fd: Response functions.
clus: True cluster membership vector.
References
Centofanti, F., Fontana, M., Lepore, A., & Vantini, S. (2020). Smooth LASSO Estimator for the Function-on-Function Linear Regression Model. arXiv preprint arXiv:2007.00529.
Examples
library(slasso)
data<-simulate_data("Scenario II",n_obs=150)