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

Applies the taut string method to one-dimensional data.

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`y` |
observed values (ordered by value of independent variable) |

`thr.const` |
smoothing parameter for the multiresolution criterion (should be approximately 2.3) |

`verbose` |
logical, if T progress (for each iteration) is illustrated grahically |

`extrema.nr` |
if set to a positive integer an approximation with the specified number of local extreme values is calculated |

`bandwidth` |
if set to a positive value the specified bandwidth is used instead of the multiresolution criterion. |

`sigma` |
if set to a positive value sigma the standard deviation is set to sigma and not estimated from the data |

`localsqueezing` |
logical, if TRUE (default) the bandwidth is changed locally. |

`squeezing.factor` |
The amount of decrement applied to the bandwidthes |

`tolerance` |
Accuracy used for the determination of the bandwidth when extrema.nr is greater than 0. |

`extrema.mean` |
logical, if TRUE (default) the value of the taut string approximation at local extreme values is set to the mean of the observations on the interval where the extremum is taken. |

`DYADIC` |
If TRUE the multiresolution constraints are only checked on dyadic intervals. |

`dyad.factor` |
If the multiresolution constraints are checked on dyadic intervals, dyad.factor determines the ratio between the lengths of two subsequent level (default is 1.1). |

`POSTISO` |
If TRUE (default) any bias caused by local squeezing is removed by applying isotonic and isotonic regression between each two local extreme values. |

A list with components

`y` |
The approximation of the given data |

`sigma` |
Standard deviation used |

`widthes` |
Bandwidth used |

`nmax` |
Number of local extreme values |

`knotsind` |
Indices of knot points |

`knotsy` |
y-koordinates of knots of the taut string |

Arne Kovac A.Kovac@bristol.ac.uk

Davies, P. L. and Kovac, A. (2001) Local Extremes, Runs, Strings and Multiresolution (with discussion) Annals of Statistics. 29. p1-65

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```
[1] "sigma is " "0.419006170602322"
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[1] 28
```

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