Estimates confidence intervals for an unknown process mean of a time seeries well modeled by a stochastic fractal process.

1 2 | ```
lmConfidence(x, model, conf.level=0.95,
parm.known=FALSE, n.rep=100000)
``` |

`x` |
a vector containing a uniformly-sampled real-valued time series or an
object of class |

`model` |
an object of class |

`conf.level` |
confidence interval probability on the interval (0,1). Default: |

`n.rep` |
number of repititions in a Monte Carlo study. Default: |

`parm.known` |
a logical value. Default: |

an two-element vector defining the low and high limits of the estimated confidence interval.

D. Percival and A. Walden (2000),
*Wavelet Methods for Time Series Analysis*,
Cambridge University Press, Chapter 7.

1 2 | ```
model <- lmModel("ppl",alpha=-0.9)
lmConfidence(lmSimulate(model), model)
``` |

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