find_opt: Find optimal number of fourier variables

In boiwsa: Seasonal Adjustment of Weekly Data

Find optimal number of fourier variables

Description

Searches through the model space to identify the best number of trigonometric variables, with the lowest AIC, AICc or BIC value.

Usage

find_opt(
  x,
  dates,
  H = NULL,
  AO = NULL,
  method = "additive",
  l.max = 12,
  k.max = 42,
  by = 6
)

Arguments

x	Numeric vector. Time series to seasonally adjust
dates	a vector of class "Date", containing the data dates
H	(optional) Matrix with holiday and trading day variables
AO	(optional) Matrix with additive outlier variables
method	Decomposition method: "additive" or "multiplicative". By default uses the additive method
l.max	Maximal number of the monthly cycle variables to search for. By default is 12
k.max	Maximal number of the yearly cycle variables to search for. By default is 42
by	Step size in the search. By default is 6.

Value

list with the optimal number of (yearly and monthly) fourier variables according to AIC, AICc and BIC

Examples

data(gasoline.data)

res=find_opt(x=gasoline.data$y,dates=gasoline.data$date)
print(res)

boiwsa documentation built on April 4, 2025, 1:57 a.m.