pred(x, sp = uncor.spec(x), h = 1, p = 5, kernel = "normal", g = 30)

Predicts time series **x**.

Takes:

x |
The time series to be predicted, as a vector of observations. Its length t does not have to be a power of two. |

sp |
The uncorrected Haar spectrum
of x. To obtain the spectrum, use
uncor.spec. |

h |
Prediction lag. |

p |
Number of rows and columns in the Yule-Walker matrix. |

kernel |
The kernel to be used for smoothing the local autocovariance. Like in ksmooth, can be set to "box", "triangle", "parzen" or "normal". Also see help(ksmooth) in S-Plus. |

g |
The value of the bandwidth for kernel smoothing. |

Returns:

p |
The unchanged value of
p. |

mean |
The predicted value. |

std.err |
The standard prediction error. |