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 2.5.0

Index]