# stationary.test: Stationary Test for Univariate Time Series

## Description

Performs stationary test for a univariate time series.
## Usage

stationary.test(x, method = c("adf", "pp", "kpss"), nlag = NULL, type = c("Z_rho", "Z_tau"), lag.short = TRUE, output = TRUE)

## Arguments

x

a numeric vector or univariate time series.

method

a character indicating which test to use. The default is
`"adf"`

by Augmented Dickey-Fuller test.

nlag

the lag order to calculate the test statistic, only valid for
`method = "adf"`

. See `adf.test`

for more details. type

the test type, only valid for `method = "pp"`

.
See `pp.test`

for more details. lag.short

a logical value, only valid for `method = "pp"`

or `"kpss"`

.
See `pp.test`

and `kpss.test`

for more details. output

a logical value indicating to print the results in R console.
The default is `TRUE`

.

## Details

This function combines the existing functions `adf.test`

,
`pp.test`

and
`kpss.test`

for testing the stationarity of a univariate time series `x`

.
## Examples

x <- arima.sim(list(order = c(1,0,0),ar = 0.2),n = 100)
stationary.test(x) # same as adf.test(x)
stationary.test(x, method = "pp") # same as pp.test(x)
stationary.test(x, method = "kpss") # same as kpss.test(x)