adass (version 1.0.1)

simulate_data: 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)

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.

Arguments

scenario

A character strings indicating the scenario considered. It could be "Scenario HAT", "Scenario DAMP", or "Scenario RCHANGE".

n_obs

Number of observations.

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)