Use a function-on-function linear regression model for prediction
Predict new observations of the functional response variable and calculate the corresponding prediction error (and their standardized or studentized version) given new observations of functional covariates and a fitted function-on-function linear regression model.
predict_fof_pc(object, mfdobj_y_new, mfdobj_x_new)
object |
A list obtained as output from |
mfdobj_y_new |
An object of class |
mfdobj_x_new |
An object of class |
A list of mfd objects. It contains:
* pred_error: the prediction error of the
standardized functional response variable,
* pred_error_original_scale:
the prediction error of the functional
response variable on the original scale,
* y_hat_new: the prediction of the
functional response observations on the original scale,
* y_z_new: the standardized version of the
functional response observations provided in mfdobj_y_new,
* y_hat_z_new: the prediction of the
functional response observations on the standardized/studentized scale.
Centofanti F, Lepore A, Menafoglio A, Palumbo B, Vantini S. (2020) Functional Regression Control Chart. Technometrics. <doi:10.1080/00401706.2020.1753581>
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