ffvd | R Documentation |
Auxiliary function used to define ffvd
terms within vd_fit
model formulae.
This term represents a functional predictor where each function is observed over a domain of varying length.
The formulation is \frac{1}{T_i} \int _1^{T_i} X_i(t)\beta(t,T_i)dt
, where X_i(t)
is a functional covariate of length T_i
, and \beta(t,T_i)
is an unknown bivariate functional coefficient.
The functional basis used to model this term is the B-spline basis.
ffvd(X, grid, nbasis = c(30, 50, 30), bdeg = c(3, 3, 3))
X |
variable domain functional covariate |
grid |
observation points of the variable domain functional covariate.
If not provided, it will be |
nbasis |
number of bspline basis to be used. |
bdeg |
degree of the bspline basis used. |
the function is interpreted in the formula of a VDPO
model.
list
containing the following elements:
An item named B
design matrix.
An item named X_hat
smoothed functional covariate.
An item named L_Phi
and B_T
1-dimensional marginal B-spline basis used for the functional coefficient.
An item named M
matrix object indicating the observed domain of the data.
An item named nbasis
number of basis used.
# Generate sample data
set.seed(123)
data <- data_generator_vd(beta_index = 1, use_x = FALSE, use_f = FALSE)
X <- data$X_se
# Specifying a custom grid
custom_grid <- seq(0, 1, length.out = ncol(X))
ffvd_term_custom_grid <- ffvd(X, grid = custom_grid, nbasis = c(10, 10, 10))
# Customizing the number of basis functions
ffvd_term_custom_basis <- ffvd(X, nbasis = c(10, 10, 10))
# Customizing both basis functions and degrees
ffvd_term_custom <- ffvd(X, nbasis = c(10, 10, 10), bdeg = c(3, 3, 3))
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