Multiple changes

In general, a time series can have any number of changes. There are two use cases:

1. Interest is in the most recent change

2. All change points are interesting to study

The most recent change point

mcplast calls mcpoint repeatedly on the most recent segment until no more changes are found and returns the starting index of that segment. If there are no change points, 0 is returned.

using ChangePointMean

ts = [1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 8, 8, 8, 8, 3, 3, 3, 3]
mcplast(ts)

15

All change points

mcpall calls mcpoint repeatedly on all segments recursively until no more changes can be found. It returns a vector of starting indices, if no changes are found, an empty vector is returned.

mcpall(ts)

3-element Vector{Int64}:
  6
 11
 15