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How do you estimate the magnitude of seasonality in time-series data?

Here's one solution I've tried for estimating the peak-to-low ratio. My main problem was that the month variable in the Poisson model had an arbitrary reference month (eg. January) and you might not ...
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How to forecast a time series which is generated by accumulating data of every five minutes and reset to 0 by the end of the day

Another, more heuristic approach here is to try to model the changes in y1, rather than the actual values, e.g. ...
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How to forecast a time series which is generated by accumulating data of every five minutes and reset to 0 by the end of the day

First off, your data is seasonal: you have $24\times 12=288$ buckets per day, and your data repeats essentially daily, so you need to specify a season length attribute (AKA frequency) of 288. Then ...
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Find "seasonality" in a categorical time series in python

For every different letter, obtain its position in the series (1st, 2nd, ...). Take the ordered set of positions and second-difference it. If the resultant time series contains only zeros, you have ...
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