pastecs (version 1.4.2)

local.trend: Calculate local trends using cumsum

Description

A simple method using cumulated sums that allows to detect changes in the tendency in a time series

Usage

local.trend(x, k=mean(x), plotit=TRUE, type="l", cols=1:2, ltys=2:1,
    xlab="Time", ylab="cusum", ...)
# S3 method for local.trend
identify(x, ...)

Value

a 'local.trend' object is returned. It has the method identify()

Arguments

x

a regular time series (a 'ts' object) for local.trend() or a 'local.trend' object for identify()

k

the reference value to substract from cumulated sums. By default, it is the mean of all observations in the series

plotit

if plotit=TRUE (by default), a graph with the cumsum curve superposed to the original series is plotted

type

the type of plot (as usual notation for this argument)

cols

colors to use for original data and for the trend line

ltys

line types to use for original data and the trend line

xlab

label of the x-axis

ylab

label of the y-axis

...

additional arguments for the graph

Author

Frédéric Ibanez (), Philippe Grosjean ()

Details

With local.trend(), you can:

- detect changes in the mean value of a time series

- determine the date of occurence of such changes

- estimate the mean values on homogeneous intervals

References

Ibanez, F., J.M. Fromentin & J. Castel, 1993. Application de la méthode des sommes cumulées à l'analyse des séries chronologiques océanographiques. C. R. Acad. Sci. Paris, Life Sciences, 316:745-748.

See Also

trend.test, stat.slide, decmedian

Examples

data(bnr)
# Calculate and plot cumsum for the 8th series
bnr8.lt <- local.trend(bnr[,8])
# To identify local trends, use:
# identify(bnr8.lt)
# and click points between which you want to compute local linear trends...