ur.df {urca} | R Documentation

## Augmented-Dickey-Fuller Unit Root Test

### Description

Performs the augmented Dickey-Fuller unit root test.

### Usage

    ur.df(y, type = c("none", "drift", "trend"), lags = 1,
          selectlags = c("Fixed", "AIC", "BIC"))

### Arguments

`y` | Vector to be tested for a unit root.
`type` | Test type, either `"none"`, `"drift"` or `"trend"`.
`lags` | Number of lags for endogenous variable to be included.
`selectlags` | Lag selection can be achieved according to the Akaike `"AIC"` or the Bayes `"BIC"` information criteria. The maximum number of lags considered is set by `lags`. The default is to use a `"fixed"` lag length set by `lags`.

### Details

The function `ur.df()` computes the augmented Dickey-Fuller test. If type is set to `"none"` neither an intercept nor a trend is included in the test regression. If it is set to `"drift"` an intercept is added and if it is set to `"trend"` both an intercept and a trend is added. The critical values are taken from Hamilton (1994) and Dickey and Fuller(1981).

### Value

An object of class `ur.df`.

### Author(s)

Bernhard Pfaff

### References

Dickey, D. A. and Fuller, W. A. (1979), Distributions of the Estimators For Autoregressive Time Series with a Unit Root, Journal of the American Statistical Association, 75, 427–431.

Dickey, D. A. and Fuller, W. A. (1981), Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root, Econometrica, 49, 1057–1072.

Hamilton (1994), Time Series Analysis, Princeton University Press.

### See Also

`ur.df-class`.

### Examples

    data(Raotbl3)
    attach(Raotbl3)
    lc.df <- ur.df(y=lc, lags=3, type='trend')
    summary(lc.df)

[Package urca version 1.2-3 Index]