| adf.test(tseries) | R Documentation |
Computes the Augmented Dickey-Fuller test for the null that x has
a unit root. The general regression
equation which incorporates a constant and a linear trend is used and
the t-statistic for a first order autoregressive coefficient
equals one is computed. The number of lags used in the regression is
k. The default value of trunc((length(x)-1)^(1/3))
corresponds to the suggested upper bound on the rate at which the
number of lags, k, should be made to grow with the sample size
for the general ARMA(p,q) setup. Note that for k equals
zero the standard Dickey-Fuller test is computed. The p-values are
interpolated from Table 4.2, p. 103 of Banerjee et al. (1993).
Missing values are not allowed.
adf.test (x, k = trunc((length(x)-1)^(1/3)))
x |
a numeric vector or time series. |
k |
the lag order to calculate the test statistic. |
"htest" containing the following components:
statistic |
the value of the test statistic. |
parameter |
the lag order. |
p.value |
the p-value of the test. |
method |
a character string indicating what type of test was performed. |
data.name |
a character string giving the name of the data. |
A. Trapletti
A. Banerjee, J. J. Dolado, J. W. Galbraith, and D. F. Hendry (1993): Cointegration, Error Correction, and the Econometric Analysis of Non-Stationary Data, Oxford University Press, Oxford.
S. E. Said and D. A. Dickey (1984): Testing for Unit Roots in Autoregressive-Moving Average Models of Unknown Order. Biometrika 71, 599-607.
x <- rnorm (1000) # no unit-root adf.test (x) y <- diffinv (x) # contains a unit-root adf.test (y)