| DickeyFullerPValues | R Documentation |
A collection and description of functions to compute the distribution and quantile function for the ADF unit root test statistics.
padf(q, N = Inf, trend = c("nc", "c", "ct"), statistic = c("t", "n"))
qadf(p, N = Inf, trend = c("nc", "c", "ct"), statistic = c("t", "n"))
adfTable(trend = c("nc", "c", "ct"), statistic = c("t", "n"),
includeInf = TRUE)
q |
vector of quantiles or test statistics. Missing values are allowed. |
p |
vector of probabilities. Missing values are allowed. |
N |
the number of observations in the sample from which the quantiles are to be computed. |
trend |
a character string describing the regression from which the
quantiles are to be computed. Valid choices are: |
statistic |
a character string describing the type of test statistic. Valid
choices are |
includeInf |
a logical flag. Should the asymptotic value be included into the table? |
padf computes cumulative probabilities for the ADF test.
qadf computes quantiles for the ADF test.
With sufficiently fine grid for the first argument, padf and
qadf compute, respectively, cumulative distribution functions
and quantile functions of ADF test statistics.
adfTable produces tables of p-values for ADF tests.
for padf and qadf, a named numeric vector with attribute
"control" holding N,
for adfTable, an object from class "gridData", which is
a list with the following components:
x |
the values of |
y |
quantiles for which the statistics are provided, |
Table |
a matrix with one row for each |
The "gridData" object contains also attribute "control"
with information about the requested test.
padf and qadf is based on the tables from A. Banerjee et
al. (1993). Interpolation is used For value of N not in the
tables. For small N (N < 25) the result is NA.
Diethelm Wuertz for the Rmetrics R-port.
Banerjee A., Dolado J.J., Galbraith J.W., Hendry D.F. (1993); Cointegration, Error Correction, and the Econometric Analysis of Non-Stationary Data, Oxford University Press, Oxford.
Dickey, D.A., Fuller, W.A. (1979); Distribution of the estimators for autoregressive time series with a unit root, Journal of the American Statistical Association 74, 427–431.
padf(q = -2:2, N = 25)
qadf(p = (1:9)/10, N = 25)
adfTable()
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