# local.trend: Calculate local trends using cumsum In pastecs: Package for Analysis of Space-Time Ecological Series

## Description

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

## Usage

 ```1 2 3 4``` ```local.trend(x, k=mean(x), plotit=TRUE, type="l", cols=1:2, ltys=2:1, xlab="Time", ylab="cusum", ...) ## S3 method for class 'local.trend' identify(x, ...) ```

## 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

## 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

## Value

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

## Note

Once transitions are identified with this method, you can use `stat.slide()` to get more detailed information on each phase. A smoothing of the series using running medians (see `decmedian()`) allows also to detect various levels in a time series, but according to the median statistic. Under R, see also the 'strucchange' package for a more complete, but more complex, implementation of cumsum applied to time series.

## Author(s)

Frédéric Ibanez ([email protected]), Philippe Grosjean ([email protected])

## 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.

`trend.test`, `stat.slide`, `decmedian`

## Examples

 ```1 2 3 4 5 6``` ```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... ```

### Example output

```Loading required package: boot
```

pastecs documentation built on March 18, 2018, 2:30 p.m.