rbbnp (version 0.3.0)

select_bandwidth: Select Optimal Bandwidth

Description

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
)

Value

A scalar representing the optimal bandwidth.

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.

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")