Hello Udo, Thank you for your response. Unfortunately, my data is proprietary so I cannot share it. However, I have found the following. My time series data is based on daily data. When seasonality=365, the size of the holdout sample has a large impact on how long the process takes. When seasonality=7, this no longer occurs. Why I had originally set seasonality =365 is because my data has this interesting pattern where every year there is an almost clockwork-like increase of values from the previous years. In other words, the pattern of data within a year are almost perfectly replicated the following year, but their absolute values are all higher relative to the previous year. I found that by setting seasonality=365, I was able to forecast this yearly step-wise function. With seasonality=7, it doesn't work. Do you have any suggestions for how I could model seasonality=7 and still get the yearly jumps? I've tried adding a year regressor, but this doesn't seem to be doing the trick. Best, Juan Manuel
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