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What is an appropriate way to calculate the MASE accuracy measure (Link) for a time series with multiple seasonalities?

For example: daily data with a strong weekly pattern and annual pattern.

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The naive seasonal forecast used to scale the error is only allowing one seasonal pattern m.

Using m = 365: we are not considering the weekly pattern anymore (365 is not a multiple of 7). Using m = 7: we are not considering the annual pattern anymore.

m = 364 considers the weekly pattern and most of the annual pattern. Is that thought right?

Any other idea how to calculate the MASE for multiple seasonalities?

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I ended up using m=7 based on a recommendation by Rob J Hyndman in the comments of this post link.

I suggest you pick the shortest of the seasonal periods and use it with a seasonal naive scaling factor.

Thanks again Rob for your advice!

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