# R: Classical Seasonal Decomposition by Moving Averages

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

    require(graphics)

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

[Package stats version 2.6.0 Index]