Functions for computing smoothing matrices and applying kernel smoothing
to functional data.
Nadaraya-Watson Kernel Smoother Matrix
Usage
S.NW(tt, h, Ker = "norm", w = NULL, cv = FALSE)
Arguments
- tt
Evaluation points (numeric vector).
- h
Bandwidth parameter.
- Ker
Kernel function or name. One of "norm", "epa", "tri", "quar",
"cos", "unif", or a custom function.
- w
Optional weights vector of length n.
- cv
Logical. If TRUE, compute leave-one-out cross-validation matrix
(diagonal is zero).
Value
An n x n smoother matrix S such that smooth(y) = S %*% y.
Details
Compute the Nadaraya-Watson kernel smoother matrix.
Examples
tt <- seq(0, 1, length.out = 50)
S <- S.NW(tt, h = 0.1)
dim(S) # 50 x 50
#> [1] 50 50