Maybe I'm missing a setting, but there currently seems to be no inbuilt in way to enable legends for the plot functions. Would it be possible to add this feature? Many thanks.

Functions for forecasting intermittent demand time series.

Conventional methods for modeling(like ARIMA) are not suited for time series which is Intermittent in nature.
We need specialized methods to model such Demands/Time Series

Methods like Croston's can be used to model such series
A rough sketch of the API

croston=Croston(...)
cro

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_

similar to scikit model.get_params

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

There is a new warning about using torch.range with respect to the Dilateloss

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?