R: Kernel Change Point Analysis

kcpa {ecp} | R Documentation

## Kernel Change Point Analysis

### Description

An algorithm for multiple change point analysis that uses the 'kernel trick' and dynamic programming.

### Usage

    kcpa(X, L, C)

### Arguments

`X` | A T x d matrix containing the length T time series with d-dimensional observations.
`L` | The maximum number of change points.
`C` | The constant used to penalize the inclusion of additional change points in the fitted model.

### Details

Segments are found through the use of dynamic programming and the kernel trick.

### Value

If the algorithm determines that the best fit is obtained through using k change points then the returned value is an array of length k, containing the change point locations.

### Author(s)

Nicholas A. James

### References

Harchaoui Z., Moulines E., Francis R.B (2009). Kernel Change-point Analysis. Advances in Neural Information Processing Systems.

[Package ecp version 3.1.2 Index]