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forecasting

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sameermahajan
sameermahajan commented Nov 15, 2021

make_future_dataframe doesn't support regressors currently. So code like:

m = Prophet()
m.add_regressor('var')
m.fit(df)
forecasts = m.predict(m.make_future_dataframe(periods=7))

gives an error like:

ValueError: Regressor 'var' missing from dataframe when attempting to generate forecasts

I know prophet may not know what exact values to put for var in each of the rows a

sktime
fkiraly
fkiraly commented Feb 5, 2022

scipy 1.8.0 is just 2 minutes old and already breaks our CI/CD.

The issue seems to be with the import of _boxcox_conf_interval in BoxCoxtransformer which has changed.

Generally, it is a bad habit to interface private methods, we should not do this.

Also, it does not seem that the output of _boxcox_conf_interval is really used in the transformer? The easy way to address this is pro

gluon-ts

Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

  • Updated Feb 6, 2022
  • Jupyter Notebook
pmdarima
nicolaschapados
nicolaschapados commented Nov 14, 2021

Is your feature request related to a problem? Please describe.

It would be nice to directly support simulating from a fitted ARIMA model, e.g. to have a simulate method to call that would delegate to statsmodels.tsa.arima.model.ARIMA.simulate. Right now, the only way I found is to use arima_res_ member of the fitted object.

Describe the solution you'd like

Class `pmdarima.arima.ar

flow-forecast
julia-shenshina
julia-shenshina commented Jan 20, 2022

🐛 Bug Report

I ran code from How To Reproduce and got strange results: fold_info column in backtest's forecasts was not added to ts[:, segment] block but concatenated separately from other segment's columns.

Expected behavior

I expected smth like

|segment |     segment_0      |     segment_1      |      segment_2     |
------------------------------------------------------

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