prior_alpha_beta: Determine Hyperparameters for Bayesian Wavelet Thresholding

In nelson16silva/wavdrcast: Wavelet-Based Direct Multistep Forecast

Description

The function prior_alpha_beta determines both the parameters alpha and beta that are used in bayesian wavelet thresholding of noisy data. Estimation is based on the avarage of the forecast error.

Usage

prior_alpha_beta(
  ...,
  par = c(0.5, 1),
  lower = c(0, 0),
  upper = c(3, 3),
  control = list()
)

Arguments

...	Parameters for function error. Argument wav = TRUE is automatically adjusted.
par	Initial values for the parameters to be optimized over.
lower	Bounds on the variables for the "L-BFGS-B" method. See stats::optim.
upper	Bounds on the variables for the "L-BFGS-B" method. See stats::optim.
control	A list of control parameters. See stats::optim.

Value

A double vector of length one.

Examples

prior_alpha_beta(df = inf[1],
lags = c(1, 1), .H = 2, .K = 2,
type = "hard", boundary = FALSE)

nelson16silva/wavdrcast documentation built on April 25, 2021, 7:03 a.m.