pastecs (version 1.0-2)

decaverage: Time series decomposition using a moving average

Description

Decompose a single regular time series with a moving average filtering. Return a 'tsd' object. To decompose several time series at once, use tsd() with the argument method="average"

Usage

decaverage(x, type="additive", order=1, times=1, sides=2, ends="fill",
        weights=NULL)

Arguments

x

a regular time series ('rts' under S+ and 'ts' under R)

type

the type of model, either type="additive" (by default), or type="multiplicative"

order

the order of the moving average (the window of the average being 2*order+1), centered around the current observation or at left of this observation depending upon the value of the sides argument. Weights are the same for all observations with

times

The number of times to apply the method (by default, once)

sides

If 2 (by default), the window is centered around the current observation. If 1, the window is at left of the current observation (including it)

ends

either "NAs" (fill first and last values that are not calculable with NAs), or "fill" (fill them with the average of observations before applying the filter, by default), or "circular" (use last values for estimating first ones and vice versa), or "period

weights

a vector indicating weight to give to all observations in the window. This argument has the priority over order

Value

• A 'tsd' object

Details

This function is a wrapper around the filter() function and returns a 'tsd' object. However, it offers more methods to handle ends.

References

Kendall, M., 1976. Time-series. Charles Griffin & Co Ltd. 197 pp. Laloire, J.C., 1972. M�thodes du traitement des chroniques. Dunod, Paris, 194 pp. Malinvaud, E., 1978. M�thodes statistiques de l'�conom�trie. Dunod, Paris. 846 pp. Philips, L. & R. Blomme, 1973. Analyse chronologique. Universit� Catholique de Louvain. Vander ed. 339 pp.

See Also

tsd, tseries, decdiff, decmedian, decevf, decreg, decloess

Examples

data(marbio)
ClausoB.ts <- ts(log(marbio$ClausocalanusB + 1))
ClausoB.dec <- decaverage(ClausoB.ts, order=2, times=10, sides=2, ends="fill")
plot(ClausoB.dec, col=c(1, 3, 2), xlab="stations")
# A stacked graph is more representative in this case
plot(ClausoB.dec, col=c(1, 3), xlab="stations", stack=FALSE, resid=FALSE,
        lpos=c(53, 4.3))