from fbprophet.serialize import model_to_json, model_from_json
with open("serialized_model.json", "r") as fin:
    fb_model = model_from_json(json.load(fin))

df_cv = cross_validation(fb_model, ............)

It produces this error,

File "C:\Users\XXXXX\.conda\envs\fbprophet7\lib\site-packages\fbprophet\diagnostics.py", line 295, in prophet_copy
    stan_backend=m.st

Describe the solution you'd like
Translate code from the R implementation into Python.

Describe alternatives you've considered
Consider implementing it as part of statsmodels rather than sktime and then interface it in sktime.

Description

• currently we have DEFAULT_SEASONALITIES = {"H": 24, "D": 1, "W": 1, "M": 12, "B": 5}
• however, having a seasonality of 1 has no real benefit to my knowledge (please correct me if I'm mistaken)
  • I base my knowledge on NBEATSEstimator and Naive2Predictor
• therefore I suggest seasonality of 7 for Daily data "D"
  • to me this makes sense since this would capture the se

Is your feature request related to a current problem? Please describe.
In order to create an outlier detection with Prophet, i need the full dataframe that's return Prophet

Describe proposed solution
Remove the hardcoded ["yhat"] from Prophet.predict add a variable asking to return just yhat or all the predictions: 'yhat_lower', 'yhat_upper', etc..
https://unit8co.github.io/d

Is your feature request related to a problem? Please describe.
While sales forecasting, it is necessary that the model is given the input about the promotions, special events that are taken care of in the prophet model as the holiday effect. Does orbit support this feature?