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Add vignette on modelling temporally aggregated data (i.e., obs_opts(na = "accumulate") ) #772

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jamesmbaazam opened this issue Sep 15, 2024 · 3 comments

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@jamesmbaazam
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Thanks a lot all - I've tested it out and it's working well now! I've included the updated figure below on the same data for reference, in case helpful!

@jamesmbaazam regarding extra documentation, I think that at some point it could be useful to add a short, dedicated section on applying to weekly data. The current documentation mentions the rw estimator for weekly, but I think having a section with an example as you do for daily could be beneficial to others as we work a lot with weekly aggregated data. The other thing would probably be then to be able to visualize on weekly scale too, but as it's possible for end users to extract the estimates and create visuals I don't think it's really necessary.

Thanks again for your help and for a great package!

weekly_est_epinow

Originally posted by @martinamcm in #767 (comment)

@jamesmbaazam
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By "surface", I mean we need a vignette walkthrough. My argument for this need is here #774 (comment).

@seabbs
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seabbs commented Sep 16, 2024

Agree. Perhaps edit the title and add a plan/outline?

@jamesmbaazam jamesmbaazam changed the title Surface feature for working with temporally aggregated data (i.e., obs_opts(na = "accumulate") ) Add vignette on modelling temporally aggregated data (i.e., obs_opts(na = "accumulate") ) Sep 16, 2024
@jamesmbaazam
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Outline of vignette

  • Discuss how EpiNow2 treats/prepares input data (into complete daily data)
  • Motivate for data being reported at different types of intervals;
    • daily,
    • irregular intervals (every few days), and
    • regular but at an aggregated scale (weekly, monthly)
  • Walk-throughs of how EpiNow2 supports observations reported at non-daily intervals:
    • Treating missing dates as explicitly missing (obs_opts(na = "missing"))
    • Treating missing dates as accumulated (obs_opts(na = "accumulate"))

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