findSegments {tilingArray} | R Documentation

## Fit a piecewise constant curve to a sequence of numbers – OBSOLETE, please use function segment instead.

### Description

This function is only here for backward compatibility - please use `segment`.

The function fits a piecewise constant curve to a sequence of numbers using a simple least squares cost function and the dynamic programming algorithm described by Picard et al. (see reference).

### Usage

    findSegments(x, maxcp, maxk, verbose=TRUE)

### Arguments

`x` | Numeric (real) vector.
`maxcp` | Integer (length 1): maximum number of segments (= 1 + maximum number of change points).
`maxk` | Integer (length 1): maximum length of a segment.
`verbose` | Logical: if this parameter has a positive value, various diagnostic output is printed.

### Details

The complexity of the algorithm is `length(x)*maxk` in memory and `length(x)*maxk*maxcp` in time.

### Value

An object of class `"segmentation"` A list with elements

`J` | likelihood criterion
`th` | matrix of segment start points
`dat` | the data used for the segmentation
`call` | the function call

.
See the vignette, and the paper cited below for details.

### Note

This function is depracated and replaced by function `segment`, but still included for backward compability.

### Author(s)

W. Huber huber@ebi.ac.uk, Joern Toedling toedling@ebi.ac.uk

### References

A statistical approach for CGH microarray data analysis. Franck Picard, Stephane Robin, Marc Lavielle, Christian Vaisse, Gilles Celeux, Jean-Jacques Daudin, Rapport de recherche No. 5139, Mars 2004, Institut National de Recherche en Informatique et en Automatique (INRIA), ISSN 0249-6399. The code of this function is based on the Matlab implementation presented at http://www.inapg.fr/ens_rech/mathinfo/recherche/mathematique/outil.html, but it has evolved.

### Examples

     x = rep( sin((0:4)/2*pi), each=3) + rnorm(3*5, sd=0.1)
     res = findSegments(x, maxcp=6, maxk=15)

[Package tilingArray version 1.14.0 Index]