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

This function estimates the location where the investigated time series exhibits a break in persistence. It requires knowledge of the direction of the break, i.e. an increase or decrease in persistence. This needs to be determined beforehand using one of the various persistence change tests provided in this package.

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`x` |
the univariate numeric vector to be investigated. Missing values are not allowed. |

`trend` |
whether the time series exhibits a trend, |

`tau` |
the function searches in the interval |

`type` |
which type of break point estimator should be used, |

`direction` |
direction of the change in persistence, |

`d_estim` |
which estimator should be used to determine the order of integration in the two regimes, |

`d_bw` |
bandwidth used for estimating the order of integration d. Default is |

`m` |
Number of covariances used for the estimation of the long run variance when considering the LKT estimator. Default is |

`serial` |
boolean, indicating whether to account for serial correlation of the errors when considering the MR estimator. Default is |

The estimators BT and LKSN are only consistent for changes from I(0) to I(1) or vice versa, the LKT estimator is consistent for changes from stationary to nonstationary memory or vice versa (cf. also Sibbertsen and Kruse (2009)), and the MR estimator is consistent for changes in d in general.

Returns a list that contains break point, estimate of the order of integration in the two regimes (the memory parameter d) and standard deviation of this estimate.

Janis Becker

Leybourne, S., Kim, T., Smith, V., and Newbold, P. (2003): Tests for a change in persistence against the null of difference-stationarity. Econometrics Journal, 6, pp. 291-311.

Busetti, F. and Taylor, R. (2004): Tests of stationarity against a change in persistence. Journal of Econometrics, 123, pp. 33-66.

Leybourne, S., Kim, T., and Taylor, R. (2007): Cusum of squares-based tests for a change in persistence. Journal of Time Series Analysis, 28, pp. 408-433.

Martins, L.. and Rodrigues, P. (2014): Testing for persistence change in fractionally integrated models: An application to world inflation rates Cusum of squares-based tests for a change in persistence. Computational Statistics and Data Analysis, 76, pp. 502-522.

`cusum_test`

, `LKSN_test`

, `MR_test`

, `ratio_test`

.

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