# kpss.test

##### KPSS Test for Stationarity

Computes the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test for the
null hypothesis that `x`

is level or trend stationary.

- Keywords
- ts

##### Usage

`kpss.test(x, null = c("Level", "Trend"), lshort = TRUE)`

##### Arguments

- x
a numeric vector or univariate time series.

- null
indicates the null hypothesis and must be one of

`"Level"`

(default) or`"Trend"`

. You can specify just the initial letter.- lshort
a logical indicating whether the short or long version of the truncation lag parameter is used.

##### Details

To estimate `sigma^2`

the Newey-West estimator is used.
If `lshort`

is `TRUE`

, then the truncation lag parameter is
set to `trunc(4*(n/100)^0.25)`

, otherwise
`trunc(12*(n/100)^0.25)`

is used. The p-values are interpolated
from Table 1 of Kwiatkowski et al. (1992). If the computed statistic
is outside the table of critical values, then a warning message is
generated.

Missing values are not handled.

##### Value

A list with class `"htest"`

containing the following components:

the value of the test statistic.

the truncation lag parameter.

the p-value of the test.

a character string indicating what type of test was performed.

a character string giving the name of the data.

##### References

D. Kwiatkowski, P. C. B. Phillips, P. Schmidt, and Y. Shin (1992):
Testing the Null Hypothesis of Stationarity against the Alternative of
a Unit Root.
*Journal of Econometrics* **54**, 159--178.

##### See Also

##### Examples

```
# NOT RUN {
x <- rnorm(1000) # is level stationary
kpss.test(x)
y <- cumsum(x) # has unit root
kpss.test(y)
x <- 0.3*(1:1000)+rnorm(1000) # is trend stationary
kpss.test(x, null = "Trend")
# }
```

*Documentation reproduced from package tseries, version 0.10-47, License: GPL-2*