Open mloning opened 4 years ago
Not at the moment, but it would be a good blog post!
The main points (some of which I've written about in vignettes/blogs) would be:
ts
and the need for tsibble
(sub-daily data, multiple series, leveraging existing user skills)tidy()
, glance()
, components()
, fitted()
, etc.)Do you have something similar for sktime?
Hi @mitchelloharawild, thanks, looks good, where can I find the vignettes/blog posts you mention?
For sktime, we've got a preprint and a more extensive design proposal in our wiki, but a lot of it is still work in progress.
I want to include a reference to fable, what's the best way to cite fable?
We'll be writing a paper about fable and its design but we haven't started on this yet.
The fable introduction blog gives an overview of the fable interface: https://www.mitchelloharawild.com/blog/fable/
The fpp3 textbook also details a workflow for forecasting: https://otexts.com/fpp3/a-tidy-forecasting-workflow.html
My comparisons between ts and tsibble must have been scraped, I recall writing about it in the fable introduction blog but likely removed it for straying too far from the topic.
The current best reference for fable is:
citation("fable")
#>
#> To cite package 'fable' in publications use:
#>
#> Mitchell O'Hara-Wild, Rob Hyndman and Earo Wang (2020). fable:
#> Forecasting Models for Tidy Time Series. R package version 0.1.2.
#> https://CRAN.R-project.org/package=fable
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Manual{,
#> title = {fable: Forecasting Models for Tidy Time Series},
#> author = {Mitchell O'Hara-Wild and Rob Hyndman and Earo Wang},
#> year = {2020},
#> note = {R package version 0.1.2},
#> url = {https://CRAN.R-project.org/package=fable},
#> }
Created on 2020-06-22 by the reprex package (v0.3.0)
Do you have any documentation on the new API design and lessons from the forecast package?