Augmented Dickey–Fuller Test
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 |
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)
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