decomp: Classical time series decomposition

In tsutils: Time Series Exploration, Modelling and Forecasting

Classical time series decomposition

Description

Perform classical time series decomposition.

Usage

decomp(
  y,
  m = NULL,
  s = NULL,
  trend = NULL,
  outplot = c(FALSE, TRUE),
  decomposition = c("multiplicative", "additive", "auto"),
  h = 0,
  type = c("mean", "median", "pure.seasonal"),
  w = NULL
)

Arguments

y	input time series. Can be ts object.
m	seasonal period. If y is a ts object then the default is its frequency.
s	starting period in the season. If y is a ts object then this is picked up from y.
trend	vector of the level/trend of y. Use NULL to estimate internally.
outplot	if TRUE, then provide a plot of the decomposed components.
decomposition	type of decomposition. This can be "multiplicative", "additive" or "auto". If y contains non-positive values then this is forced to "additive".
h	forecast horizon for seasonal component.
type	calculation for seasonal component: "mean": the mean of each seasonal period. "median": the median of each seasonal period. "pure.seasonal": estimate using a pure seasonal model.
w	percentage or number of observations to winsorise in the calculation of mean seasonal indices. If w>1 then it is the number of observations, otherwise it is a percentage. If type != "mean" then this is ignored.

Value

A list containing:

• trend: trend component.

• season: season component.

• irregular: irregular component.

• f.season: forecasted seasonal component if h>0.

• g: pure seasonal model parameters.

Author(s)

Nikolaos Kourentzes, [e-mail].

References

Ord K., Fildes R., Kourentzes N. (2017) Principles of Business Forecasting, 2e. Wessex Press Publishing Co., p.106-111.

Examples

decomp(referrals)

tsutils documentation built on Nov. 15, 2023, 1:08 a.m.