Module scalar_on_function 

Scalar-on-function regression with mixed scalar/functional covariates.

Implements models of the form:

y = α + ∫β(t)X(t)dt + γᵀz + ε

where X(t) is a functional predictor, z is a vector of scalar covariates, β(t) is the functional coefficient, and γ is the vector of scalar coefficients.

Methods

• fregre_lm: FPC-based functional linear model with optional scalar covariates
• fregre_np_mixed: Nonparametric kernel regression with product kernels
• functional_logistic: Logistic regression for binary outcomes
• fregre_cv: Cross-validation for number of FPC components

Structs

FregreCvResult

Result of cross-validation for K selection.

FregreLmResult

Result of functional linear regression.

FregreNpResult

Result of nonparametric functional regression with mixed predictors.

FunctionalLogisticResult

Result of functional logistic regression.

Functions

fregre_cv

K-fold cross-validation for selecting the number of FPC components.

fregre_lm

Functional linear model with optional scalar covariates.

fregre_np_mixed

Nonparametric kernel regression with mixed functional and scalar predictors.

functional_logistic

Functional logistic regression for binary outcomes.

predict_fregre_lm

Predict new responses using a fitted functional linear model.

predict_fregre_np

Predict new responses using a fitted nonparametric model.