fdars (version 0.3.3)

S.NW: Smoothing Functions for Functional Data

Description

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)

Value

An n x n smoother matrix S such that smooth(y) = S %*% y.

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).

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