Estimate the least squares model for a noisy signal. We use the cghseg package, which implements the pruned dynamic programming method of Rigaill (2010) to find, for all k=1,...,maxSegments: argmin_x has k segments ||Y-x||^2_2.

1 | ```
run.cghseg(Y, base = seq_along(Y), maxSegments = 20)
``` |

`Y` |
Numeric vector of the noisy signal to segment. |

`base` |
Integer vector of bases where Y is sampled. |

`maxSegments` |
Maximum number of segments to consider. |

List containing the solutions. The "segments" element is a data.frame that describes the segmentation model, with 1 line for each segment.

Guillem Rigaill, Toby Dylan Hocking

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