Description Usage Arguments Details Value Author(s) References See Also Examples

Perform a unit root test to check stationarity in a linear stochastic process.

1 | ```
uroot.test(y,unit_root = c("adf","kpss","pp","box"),alpha = 0.05)
``` |

`y` |
a numeric vector or an object of the |

`unit_root` |
A character string naming the desired unit root test for checking stationarity.
Valid values are |

`alpha` |
Level of the test, possible values range from 0.01 to 0.1. By default |

Several different tests are available:
In the `kpss`

test, the null hypothesis that `y`

has a stationary root
against a unit-root alternative. In the two remaining tests, the null hypothesis
is that `y`

has a unit root against a stationary root alternative. By default,
`alpha = 0.05`

is used to select the more likely hypothesis.

a h.test class with the main results of unit root hypothesis test.

Asael Alonzo Matamoros and A. Trapletti

Dickey, D. & Fuller, W. (1979). Distribution of the Estimators for
Autoregressive Time Series with a Unit Root. *Journal of the American
Statistical Association*. 74, 427-431.

Kwiatkowski, D., Phillips, P., Schmidt, P. & Shin, Y. (1992). Testing the Null
Hypothesis of Stationarity against the Alternative of a Unit Root,
*Journal of Econometrics*. 54, 159-178.

Phillips, P. & Perron, P. (1988). Testing for a unit root in time series regression,
*Biometrika*. 72(2), 335-346.

Ljung, G. M. & Box, G. E. P. (1978). On a measure of lack of fit in time series models.
*Biometrika*. 65, 297-303.

1 2 3 4 5 6 7 | ```
# stationary ar process
y = arima.sim(100,model = list(ar = 0.3))
uroot.test(y)
# a random walk process
y = cumsum(y)
uroot.test(y,unit_root = "pp")
``` |

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