StatsForecast Files

Fast forecasting with statistical and econometric models

This is an exact mirror of the StatsForecast project, hosted at https://github.com/Nixtla/statsforecast. SourceForge is not affiliated with StatsForecast. For more information, see the SourceForge Open Source Mirror Directory.

The interactive file manager requires Javascript. Please enable it or use sftp or scp.
You may still browse the files here.

Name	Modified	Size	InfoDownloads / Week
Parent folder
README.md	2024-11-26	438 Bytes	0
v2.0.0 source code.tar.gz	2024-11-26	52.2 MB	0
v2.0.0 source code.zip	2024-11-26	52.3 MB	0
Totals: 3 Items		104.4 MB	0

Breaking Change

breaking: remove deprecated behavior @jmoralez (#946)
breaking: allowmean and allowdrift True by default in AutoARIMA @V-nguard (#918)

Bug Fixes

C++ ARIMA fixes and refactoring @filipcacky (#939)
fix: seasonal naive confidence interval bug @andrewscottm (#932)
fix: auto arima xreg rank deficient test @andrewscottm (#931)

Documentation

Update broken yahoo query @paullabonne (#925)

Source: README.md, updated 2024-11-26

Other Useful Business Software

Gen AI apps are built with MongoDB Atlas

The database for AI-powered applications.

MongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.

Start Free

Keep company data safe with Chrome Enterprise

Protect your business with AI policies and data loss prevention in the browser

Make AI work your way with Chrome Enterprise. Block unapproved sites and set custom data controls that align with your company's policies.

Download Chrome

Recommended Projects

Darts
A python library for easy manipulation and forecasting of time series
Deep learning time series forecasting
Deep learning PyTorch library for time series forecasting
OpenForecast
OpenForecast is a package of general purpose, forecasting models written in Java that can be applied to any data series. No knowledge of forecasting is required. Using this package, the most appropriate algorithm for your data will be selected.
Prophet
Tool for producing high quality forecasts for time series data
IRIS Toolbox Project
I Rest, IRIS Solves

StatsForecast Files

Fast forecasting with statistical and econometric models

Get an email when there's a new version of StatsForecast

Breaking Change

Bug Fixes

Documentation