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
Arlot S., Celisse A., Harchaoui Z. (2019). A Kernel Multiple Change-point Algorithm via Model Selection. J. Mach. Learn. Res., 20, 162:1-162:56.
[Package ecp version 3.1.5 Index]