Comments (3)
Probably a good idea to explain what is meant by day of reference vs report in this document too.
Agree. We need to keep it concise though to maintain this as a quick start vs a longer intro to the package.
What is (1 | day)? Is this the random walk?
Its a random intercept by day,
"Rather than using the methods supplied for epinowcast directly, package functions can also be used to extract nowcast posterior samples, summarise them, and then plot them" Is this sentence missing something? I'm confused what "package functions" are referring to. It sounds like you might be referring to a different package? Not sure why functions vs methods are different here...
This is complete but might need an edit. The distinction this is drawing is that there are user facing S3 methods for the output for epinowcast
(i.e. methods) and then normal functions that underlie these methods that more advanced users can use if they wish.
Am curious why there is a consistent underestimation. Would be useful to give some information (e.g., what things you can try, what to read) for readers who want to learn more (but don't have to show how to actually do more complicated things)...
Yes, this is a good point and I like the idea of pointing users towards other resources for learning more/ideas of things to try. Some of the obvious things to try (which are tried in the german vignette are time-varying reporting delay distributions and day-of-the-week effects for the reporting delay as well as for the date of report. Once we have them implemented non-parametric model specifications will likely do well here. Lastly, there is a clear day of the week signal in the final reported counts this could be included in the expectation model as a random effect on the day_of_week
. A more mechanistic expectation model might also help (i.e one with some kind of growth rate vs a random walk on the log scale).
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Fancy making some of these changes @parksw3 (or any others for the comments in the related issues).
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This seems like we should address it for 0.2.1
. Currently no one is assigned but ideally we would be aiming for a release candidate tomorrow. If anyone can turn it around that quick it would be great but if not I will address tomorrow morning and then ping @parksw3 to see if it has covered his comments.,
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Related Issues (20)
- Comments on `germany-age-stratified-nowcasting.Rmd` HOT 3
- Schematic for `model.Rmd` HOT 5
- Check documentation of supported input types and standardise
- Check documentation of outputs
- Split `model.Rmd` vignette into separate vignettes
- Switch to using cmdstanr to expose Stan functions to R HOT 2
- README equation rendering HOT 8
- README citation rendering
- Model initialisation issues due to a cmdstan update
- Model compilation failing on Windows in CI HOT 2
- Improve documentation of discrete distributions HOT 3
- Improve documentation for enw_preprocess_data HOT 2
- epinowcast error when multiple time series are used: Mismatch in dimension declared and found in context; HOT 3
- Add support for a gamma Poisson mixture observation model
- Add support for a normal observation model
- Add support for using NA to indicate skipping a term from the likelihood HOT 1
- Explore the use of the stan transformation functions HOT 1
- Improve discretisation
- Getting help with stan vignette
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