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I have a daily time series, with weekly seasonality, but it starts and ends in the middle of the week (Wed/Thu, during the season peak).

I have two questions:

  1. Should I drop the first and last partial weeks from the data before modelling?

  2. When splitting into training and test sets, should I also make sure to include only whole seasons in each set?

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  1. No, it is probably better to use and keep all data. Repeated-measures methods as implemented in functions like lmer from R package lme4, and gam and s from mgcv do not require higher-level units to have the same number of lower-level units.

  2. Yes. Cross-validated accuracy measures are likely less optimistic when you sample at the higher than at the lower level.

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  • $\begingroup$ Thank you @Marjolein. $\endgroup$
    – Kazumi
    Feb 28, 2021 at 0:27
  • $\begingroup$ @Kazumi You are welcome $\endgroup$ Feb 28, 2021 at 9:34

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