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new 70f2178 Fix typo in MATH documentation (#158)
70f2178 is described below
commit 70f2178337b4dbe476af758888f05a3e0f50cd42
Author: Arpit Jain <[email protected]>
AuthorDate: Wed May 13 07:34:41 2026 +0900
Fix typo in MATH documentation (#158)
---
docs/MATH.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/docs/MATH.md b/docs/MATH.md
index e8bea50..3b64812 100644
--- a/docs/MATH.md
+++ b/docs/MATH.md
@@ -50,7 +50,7 @@ Figure 2. On the **left subfigure**, there is a time-series
$Z=\\{ Z_0, \cdots Z
There are a couple of additional nuances and notes that we want to mention:
- According to the provided definition, the change point is the first point of
the *second* subsequence, and, because both subsequences must be non-empty, the
change point cannot be the first point of the whole sequence $Z$, i.e., point
$Z_0$.
- There exists an alternative way of defining the change point (as the last
point of the first subsequence - in that case, the last point $Z_{T-1}$ cannot
be the change point). And, in fact, some of the papers cited here are using
that other definition. However, Apache Otava uses the term "change point" as
defined above, i.e., the change point is the first commit at which metrics
change.
-- In the example in Figure 2 we effectivelly used distance between means as a
distance between the distributions. It's an oversimplification for illustrative
purposes, and in reality we actually use a divergence measure between
multivariate distributions. See **[Original Work](#original-work)** section for
more details.
+- In the example in Figure 2 we effectively used distance between means as a
distance between the distributions. It's an oversimplification for illustrative
purposes, and in reality we actually use a divergence measure between
multivariate distributions. See **[Original Work](#original-work)** section for
more details.
- In the example in Figure 2, we compared only two pairs of the values
$(\hat{\tau}_1, \hat{\kappa}_1)$, namely $(6, 12)$ and $(6, 22)$. The algorithm
actually checks for all valid values before choosing the best one. See Figure 3.
