# Calculate MASE for time series with multiple seasonalities

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.

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?

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