Select Optimal Bandwidth — select

Selects an optimal bandwidth using the specified method.

Usage

select_bandwidth(
  X,
  Y = NULL,
  method = "cv",
  kernel.fun = "normal",
  if_approx_kernel = TRUE,
  kernel.resol = 1000
)

Arguments

X: A numerical vector of sample data.
Y: Optional. A numerical vector of sample data for conditional expectation estimation.
method: A string specifying the bandwidth selection method. Options are "cv" for cross-validation and "silverman" for Silverman's rule of thumb. Defaults to "cv".
kernel.fun: A string specifying the kernel type. Options include "normal", "epanechnikov", "Schennach2004", and "sinc".
if_approx_kernel: Logical. If TRUE, uses approximations for the kernel function.
kernel.resol: The resolution for kernel function approximation.

Value

A scalar representing the optimal bandwidth.

Examples

# Generate sample data
X <- rnorm(100)
# Get optimal bandwidth using cross-validation with normal kernel
h_opt <- select_bandwidth(X, method = "cv", kernel.fun = "normal")
# Get optimal bandwidth using Silverman's rule with Schennach kernel
h_opt <- select_bandwidth(X, method = "silverman", kernel.fun = "Schennach2004")