adf.test {tseries} | R Documentation |
Computes the Augmented Dickey-Fuller test for the null that x
has
a unit root.
adf.test(x, alternative = c("stationary", "explosive"), k = trunc((length(x)-1)^(1/3)))
x |
a numeric vector or time series. |
alternative |
indicates the alternative hypothesis and must be
one of "stationary" (default) or "explosive" . You can
specify just the initial letter. |
k |
the lag order to calculate the test statistic. |
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). If the computed statistic is outside the
table of critical values, then a warning message is generated.
Missing values are not allowed.
A list with class "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. |
alternative |
a character string describing the alternative hypothesis. |
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)