statsforecast

Lightning ⚡️ fast forecasting with statistical and econometric models.

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Nixtla

Nixtla • individual

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363

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0/100

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Created

Nov 24, 2021

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README Summary

StatsForecast is a Python library that provides lightning-fast implementations of statistical and econometric forecasting models. It offers optimized versions of classic time series forecasting methods like ARIMA, ETS, and seasonal naive models with significant speed improvements over traditional implementations.

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Tags

Time Series ForecastingStatistical ModelingEconometric AnalysisARIMA ModelingExponential SmoothingSeasonal DecompositionCross-validation for Time SeriesForecast Evaluation MetricsHierarchical ForecastingProbabilistic ForecastingServerlessFinancial Time Series AnalysisRetailSelf-hostedStatistical Feature EngineeringHealthcare AnalyticsFast Statistical ComputingBudget ForecastingTime SeriesClassical Statistical MethodsTabularResource Capacity PlanningSupply ChainClassical ML RenaissanceEnergyFinTechOn-premiseEconomic Indicator PredictionCloud APISales PredictionDemand PlanningDemand ForecastingManufacturingInterpretable AISeasonal Trend AnalysisInventory PlanningPython

Recent Activity

Updated 24 days ago

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Quality

production

Quality: high
Maturity: production

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Languages

Python100.0%

Timeline

Project created: Nov 24, 2021
Forked: Mar 22, 2026
Your last push: 24 days ago
Upstream last push: 7 days ago
Tracked since: Mar 21, 2026

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