Nixtla/statsforecast
View on GitHub ↗ ★ 4,958 Python
Lightning ⚡️ fast forecasting with statistical and econometric models.
15 mentions on Hacker News by 6 people: 10 stories, 5 comments · first 2021-12-06 · latest 2025-03-20
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…They are currently the most mature timeseries packages. [0] https://unit8co.github.io/darts/ [1] https://github.com/Nixtla/statsforecast
comment by EricLeer · 2023-09-27 · in Prophet: Automatic Forecasting Procedure -
…to test the model against simpler models (ETS in this case) using the StatsForecast library ( https://github.com/Nixtla/statsforecast/ ).
comment by fedegr · 2022-08-17 · in Exponential Smoothing: faster and more accurate than NeuralProphet -
…of events created on Facebook). We can conclude from the results comparing AutoARIMA vs. Prophet ( https://github.com/Nixtla/statsforecast/tree/main/experiment... , using the same datasets as in the ETS vs. NeuralProphet experiment) that…
comment by fedegr · 2022-08-17 · in Exponential Smoothing: faster and more accurate than NeuralProphet -
…developed. About benchmarking using statistical models, we highly recommend using statsforecast ( https://github.com/Nixtla/statsforecast ) that we created. It is designed to be highly efficient in fitting statistical models on millions of…
comment by fedegr · 2021-12-06 · in Automated Time Series Processing and Forecasting