* Add example of dask distributed parameter tuning to notebook diagnostics
* Rearrange description blocks and correct typos
* Add more informative explanations and tips in docs for tuning examples
* increase output df column width to see results
* add instructions for multiprocess and threaded
* reset index of hyperparameter tuning results df
* fix typos
* remove blank code cell
* grammar correction
* Add subsection
* Split different parameter optimsiation examples
I'm not sure why a data frame ends up with names and a tibble does not, but it doesn't seem like an important enough problem to investigate in detail, and this is a simple fix.
+ cleans up Stan model compilation by switching over to the rstantools-based workflow (see https://mc-stan.org/rstantools/articles/minimal-rstan-package.html for more info)
+ minor documentation change: {devtools} -> {remotes}, which is better for end-users
+ adds RStudio project file which makes it easier for community to get started with contributing to the package
* Add functions for serializing to/from JSON
* Fix list vs. series type issue, track version
* Avoid DateTimeIndex
* bugfix
* another fix
* Fix copy test
* Fix issue with pre-epoch dates
* Handle empty datetime series
* modified cross_validation to allow custom cutoffs
* moved set period, initials and identify larg. seas
* modified the diagnostics and added the test
* reverted cv default value tests and added a new custom cutoff test
* reorganized to raise the seasonality period warning message even if cutoffs are manually specified
* moved the initials vs. seasonality check
* changed assertCountEqual to assertItemsEqual in cv
* modified to test lengths instread of cutoff values
Co-authored-by: Fusi Marco <Marco.Fusi@valuelab.it>
* sampling iters arg name, logic changes
* Bump cmdstanpy version in requirements to 0.9.5
* Change Model to CmdStanModel
Co-authored-by: Ben Letham <bletham@gmail.com>
* Add multiprocessing Pool and create function for single cutoff forecast
* add params to single forecast function
* Add iterable for input params for pool
* Add docstring for single cutoff forecast func
* Add check for multiprocessing in test_cross_validation
* check ofr is None and is True and add better description for multiprocess in docstring
* Raise error if wrong args chosen and add test
* fix conflicts
* Change arg to True/False, model.kwargs
* docstring units and few more fixes
* change to iterator and add back tqdm to for loop
* add option in diagnosics notebook about multiprocessing option
* add extra test for checking calls to single forecast func
* tqdm
* Added progress bar to the crossvalidation
In order to improve the user experiance a progress bar is added to the crossvalidation loop.
* Update requirements.txt
* Update python/fbprophet/diagnostics.py
* updated further
* Update requirements.txt
* changes
* added actual tests for fit method
* precision
* syntax
* sampling not working
* sampling seems to work
* sampling not working again
* sampling works, tests to be removed
* replaced data with rmse
* replace pystan with cmdstanpy
* cleanup
* cleanup
* test for newton
* added support for multiple backends
* minor fixes
* fixed comment
* added support for --test-slow flag
* fixed import
* reverted style change
* specify backend based on env variable
* fixes
* PR fixes
