Description Usage Arguments Details References Examples

Multivariate local Whittle Score type test for the null hypothesis of true long memory against the alternative of spurious long memory suggested by Sibbertsen, Leschinski and Holzhausen (2015).

1 2 3 4 |

`X` |
data matrix |

`m` |
bandwith parameter specifying the number of Fourier frequencies used
for the estimation usually |

`epsilon` |
trimming parameter |

`coint.elements` |
Vector specifying which elements in the vector series are in a cointegrating relationship. By default |

`B` |
cointegrating matrix, if known. Default is |

`prewhite` |
specifies the form of pre-whitening applied. One of |

`eta` |
vector of weights. Default is |

`rep` |
if |

`approx` |
if |

`split` |
if |

`T_limdist` |
number of increments used in simulation if limit distribution.
Only relevant for component-wise version of the test. Default is |

`M_limdist` |
number of replications for simulation of the limit distribution.
Default is |

add details here

Sibbertsen, P., Leschinski, C. H., Holzhausen, M., (2015): A Multivariate Test Against Spurious Long Memory. Hannover Economic Paper.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
T<-500
m<-floor(1+T^0.75)
series<-FI.sim(T=T,q=2,rho=0.7,d=c(0.4,0.2))
ts.plot(series, col=1:2)
MLWS(X=series, m=m, epsilon=0.05)
shift.series<-series+ARRLS.sim(T=T, phi=0, sig.shift=2, prob=5/T)
ts.plot(shift.series, col=1:2)
MLWS(X=shift.series, m=m, epsilon=0.05)
T<-500
m<-floor(T^0.75)
series<-FI.sim(T=T,q=2,rho=0,d=c(0.1,0.4), B=rbind(c(1,-1),c(0,1)))
ts.plot(series, col=1:2)
MLWS(series, m=m)
MLWS(series, m=m, coint.elements=c(1,2))
``` |

FunWithR/LongMemoryTS documentation built on June 9, 2018, 12:22 a.m.

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