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 issue linked to the documentation

Our documentation is a bit patchy in some places, filling in the missing information would be a great help! Thanks to @chrisholder for creating the list!

| File | Comments

Description

Currently, DistributionOutput classes produce a TransformedDistribution when the distribution method is invoked with loc and scale. However, we cannot get mean and variance out of such object:

import mxnet as mx
from gluonts.mx.distribution import GaussianOutput

distr_output = GaussianOutput()

args = mx.nd.array([0.0]), mx.nd.array([1.0])
loc = mx.

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?