# lsar

##### Decomposition of Time Interval to Stationary Subintervals

Decompose time series to stationary subintervals and estimate local spectrum.

- Keywords
- ts

##### Usage

`lsar(y, max.arorder = 20, ns0, plot = TRUE, …)`

##### Arguments

- y
a univariate time series.

- max.arorder
highest order of AR model.

- ns0
basic local span.

- plot
logical. If

`TRUE`

(default), local spectra are plotted.- …
further arguments to be passed to

`plot.lsar`

.

##### Value

An object of class `"lsar"`

, which is a list with the following
elements:

1: pooled model is accepted. 2: switched model is accepted.

number of observations of local span.

start points and end points of local spans.

number of frequencies.

order of switched model.

innovation variance of switched model.

AIC of switched model.

order of pooled model.

innovation variance of pooled model.

AIC of pooled model.

local spectrum.

the name of the univariate time series `y`

.

##### References

Kitagawa, G. (2010)
*Introduction to Time Series Modeling*. Chapman & Hall/CRC.

##### Examples

```
# NOT RUN {
# seismic data
data(MYE1F)
lsar(MYE1F, max.arorder = 10, ns0 = 100)
# }
```

*Documentation reproduced from package TSSS, version 1.2.3, License: GPL (>= 2)*