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.
I am wondering if there is a Random Grid Search equivalent of ForecastingGridSearchCV similar to how we have [RandomizedSearchCV](https://scikit-learn.org/stable/modul

Description

(A clear and concise description of what the feature is.)

• util.cumsum implementation https://github.com/awslabs/gluon-ts/blob/master/src/gluonts/mx/util.py#L326 does not scale under mx.ndarray
• cumsum is 2-5 times slower than nd.cumsum under both mx.sym and mx.ndarray, and even fails for large 4-dim input

Sample test

Code

# import ...
def test_

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?