# Automatic test measuring dissimilarity between two time series

I have two time series, series1 and series2. My aim is to find how much Series2 is different from Series1, automatically/quantitatively.
Image can be seen in its original size by clicking here.

Series1 is the expected result. Series2 is the test/incoming series.

I am providing a histogram plot, where Series2 is represented in dark brown colour. You can also note in the x-axis between 221 and 353 there is a significant variation. ie Series2 is less than Series1. I am coding using C++.

I think, crosscorrelation will help, but produces a value based on similarity rather than dissimilarity. I see people talk about Kolmogorov-Smirnov Test. Is this the test which i should be performing?

UPDATE 1: I am trying to perform a template matching. I have divided my template image in to 8x8 blocks as well as my incoming test image. I am trying to compare one block in template image with the same block(based on the spatial pixel positions) in the test image. I calculate the intensity sum within each block. I obtain series1 for the Template image and have Series2 for the test image.

• I would suggest you to work on clarity of the question; this helps in getting answers. – user88 Oct 21 '10 at 10:56
• @mbq, i have updated to my post – Raj Oct 21 '10 at 11:15

You can look at the mean square error. In R, you can see the algorithm for time series in Rob Hyndman's ftsa package (see the error function).