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

Is your feature request related to a problem? Please describe.
Plotting confidence intervalls with the current plot function from sktime.utils.plotting import plot_series is not well suitable in case all lines are very close, see picture.

**Describe the solution you'd

Description

We currently only check for the underlying prediction net to have the same parameters. This can create issues when constructing a Predictor using the correct prediction net but other parameters, like freq or transformation.

Maybe we can add proper checks the other inputs as well.

References

[this note](https://github.com/awslabs/gluon-ts/blob/726f52e720f6afc72c86e

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?