decompose {stats}R Documentation

Classical Seasonal Decomposition by Moving Averages

Description

Decompose a time series into seasonal, trend and irregular components using moving averages. Deals with additive or multiplicative seasonal component.

Usage

decompose(x, type = c("additive", "multiplicative"), filter = NULL)

Arguments

x A time series.
type The type of seasonal component.
filter A vector of filter coefficients in reverse time order (as for AR or MA coefficients), used for filtering out the seasonal component. If NULL, a moving average with symmetric window is performed.

Details

The additive model used is:

Y[t] = T[t] + S[t] + e[t]

The multiplicative model used is:

Y[t] = T[t] * S[t] + e[t]

Value

An object of class "decomposed.ts" with following components:

seasonal The seasonal component (i.e., the repeated seasonal figure)
figure The estimated seasonal figure only
trend The trend component
random The remainder part
type The value of type

Note

The function stl provides a much more sophisticated decomposition.

Author(s)

David Meyer David.Meyer@wu-wien.ac.at

See Also

stl

Examples

m <- decompose(co2)
m$figure
plot(m)

[Package stats version 2.1.0 Index]