Learn R Programming
aTSA (version 3.1.2.1)

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)

Value

The results are the same as one of the adf.test, pp.test, kpss.test, depending on which test are used.

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.

Author

Debin Qiu

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

Run this code
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)

Run the code above in your browser using DataLab