12 months average (R) and single year (X) temperature of a city. |

The picture shows clearly that we have had a colder winter in 2013 (X) but still we can't say if this is an anomaly or not, because we need to have a margin of tolerance, which may be different in each month, if X tolerate in the margin then it is normal behaviour.

But now let us look at this time series in another way. Why not consider R or X each as a vector in a 12-dimension euclidean space? Exactly like what we talked about in the previous post. If we think this way, we can find the distance between points R and X (which is the length of the R-X) with the formula we talked about before in the previous post. Now if the distance is acceptable the point X is not anomaly otherwise, it is.

(Download: TIME SERIES ANOMALY DETECTION)

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