| simulate_data {adass} | 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)
Arguments
scenario |
A character strings indicating the scenario considered. It could be "Scenario HAT", "Scenario DAMP", or "Scenario RCHANGE". |
n_obs |
Number of observations. |
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.
Beta_vero_fd: The true coefficient function.
References
Centofanti, F., Lepore, A., Menafoglio, A., Palumbo, B., Vantini, S. (2023). Adaptive Smoothing Spline Estimator for the Function-on-Function Linear Regression Model. Computational Statistics 38(1), 191–216.
Examples
library(adass)
data<-simulate_data("Scenario HAT",n_obs=100)