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I need to detect plateaus in time series data online. The data I am working with represents the magnitude of acceleration of a tri-axis accelerometer. I want to find a reference time window that I can use for calibration purposes. Because of that, the system must not move and hence only gravity should influence the system.

How can I find such plateaus or is there even a more principled approach that I can take?

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  • $\begingroup$ It would be good if you uploaded the data used to generate the plot, e.g. to github or sharecsv.com $\endgroup$
    – Emre
    Mar 22 '16 at 22:39
  • $\begingroup$ Please don't cross post. $\endgroup$
    – Emre
    Mar 23 '16 at 17:38
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Why don't you use a Shewhart Control Chart (more modernly referred to as 6-sigma) with a moving variable length window to understand the process that you have.

As you find your process variability decreases markedly, by having too many results within $±1σ$ then you have a "process change" and that might be defined as a plateau. You will need to decide how many observations you require to establish a plateau.

The as you find your variability increases and your $±3σ$, you know you again have a process change and need to recalculate your limits.

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  • $\begingroup$ Why would you want to use the number of results within $\pm 1\sigma$ instead of the $\sigma$ of the moving window directly? $\endgroup$ Mar 22 '16 at 17:06
  • $\begingroup$ Inherent in Shewhart control techniques is the probability of various events happening. e.g. 68.3% of the population is contained within 1 standard deviation from the mean, so the probably of 8 points within +/i 1 std dev is 4.7% and so it is likely that a process change has occurred. $\endgroup$
    – Marcus D
    Mar 22 '16 at 19:15
  • $\begingroup$ I agree that violating a Shewhart rule is evidence that there's a process change. What's not clear to me is that this is better evidence of the plateau than a direct test on the level of $\sigma$. (Edit: This is the sort of thing we'd want to test by, say, looking at the graph of number of points outside of $\pm 1\sigma$ in a window vs. the graph of $\sigma$ over that window to see how they compare for this dataset.) $\endgroup$ Mar 22 '16 at 20:14
  • $\begingroup$ I'm sure there are better tests for plateau @MatthewGraves. $\endgroup$
    – Marcus D
    Mar 23 '16 at 11:29
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I found a good solution for my problem here: https://stats.stackexchange.com/a/201315/101744

Thanks to everyone!

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