kcpa {ecp} | R Documentation |
An algorithm for multiple change point analysis that uses the 'kernel trick' and dynamic programming.
kcpa(X, L, C)
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. |
Segments are found through the use of dynamic programming and the kernel trick.
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.
Nicholas A. James
Harchaoui Z., Moulines E., Francis R.B (2009). Kernel Change-point Analysis. Advances in Neural Information Processing Systems.