model.thresh {breakfast} | R Documentation |

## Estimating change-points in the piecewise-constant or piecewise-linear mean of a noisy data sequence via thresholding

### Description

This function estimates the number and locations of change-points in the piecewise-constant or piecewise-linear mean of a noisy data sequence via thresholding.

### Usage

```
model.thresh(cptpath.object, sigma = NULL, th.const = NULL)
```

### Arguments

`cptpath.object` |
A solution-path object, returned by a |

`sigma` |
An estimate of the standard deviation of the noise in the data |

`th.const` |
A positive real number used to define the threshold for the detection process. The default used in the piecewise-constant model is 1.15, while in the piecewise-linear model, the value is taken equal to 1.4. |

### Value

An S3 object of class `cptmodel`

, which contains the following fields:

`solution.path` |
The solution path method used to obtain |

`type` |
The model type used, inherited from the given |

`model.selection` |
The model selection method used to return the final change-point estimators object, here its value is |

`no.of.cpt` |
The number of estimated change-points |

`cpts` |
The locations of estimated change-points |

`est` |
An estimate of the mean of the vector |

### See Also

`sol.idetect`

, `sol.idetect_seq`

, `sol.not`

, `sol.tguh`

, `sol.wbs`

, `sol.wbs2`

, `breakfast`

### Examples

```
f <- rep(rep(c(0, 1), each = 50), 10)
x <- f + rnorm(length(f))
model.thresh(sol.idetect_seq(x))
```

*breakfast*version 2.4 Index]