find_outliers: Find additive outliers

In boiwsa: Seasonal Adjustment of Weekly Data

Find additive outliers

Description

Searches for additive outliers using the method described in Appendix C of Findley et al. (1998). If the number of trigonometric variables is not specified will search automatically through the model space to identify the best number of trigonometric variables, with the lowest AIC, AICc or BIC value.

Usage

find_outliers(
  x,
  dates,
  out.tolerance = 3.8,
  my.AO.list = NULL,
  H = NULL,
  my.k_l = NULL,
  method = "additive"
)

Arguments

x	Numeric vector. Time series to seasonally adjust
dates	a vector of class "Date", containing the data dates
out.tolerance	t-stat threshold for outliers (see Findley et al., 1998)
my.AO.list	(optional) Vector with user defined additive outlier variables
H	(optional) Matrix with holiday and trading day variables
my.k_l	(optional) Vector with the number of fourier terms to capture the yearly and monthly cycle. If NULL, would perform automatic search using AICc criterion
method	Decomposition method: "additive" or "multiplicative". By default uses the additive method

Value

my.k_l

ao list of AO dates

References

Findley, D.F., Monsell, B.C., Bell, W.R., Otto, M.C. and B.C Chen (1998). New capabilities and methods of the X-12-ARIMA seasonal-adjustment program. Journal of Business & Economic Statistics, 16(2), pp.127-152.

Examples

#Not run:
# Searching for additive outliers in Gasoline data
data(gasoline.data)
ao_list=find_outliers(x=gasoline.data$y,dates = gasoline.data$date)

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