forecasting

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.

Is your feature request related to a problem? Please describe.
EnsembleForecaster does not currently accept weights. With #1136 and #1139 being worked on it would be nice to optionally allow users to pass weights to EnsembleForecaster.

This would give users an out-of-the-box way to use ainverse error based weighting strategy in forecasting ensembles. Users could also supply other types

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

Dear team,

I am in stuck when convert very large numpy array to your TSDatasets.
These are what I have tried to fix my issue:

• when building time-series, I used tensorflow.keras.preprocessing.timeseries_dataset_from_array. After this step, the memory is still fine
• I concatenate all batch data into numpy array, this step produces problem so I use numpy memmap to avoi

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?

1. The README.md does not mention or link to ReadTheDocs documentation. It would be great if it did.

2. The Getting Started page does mention ReadTheDocs documentation but does not link to it. We should add this [link](https://flow-forecast.readthedocs.io/en/la