tylerJPike/OOS
Out-Of-Sample Time Series Forecasting: OOS introduces a comprehensive framework for time series forecasting with traditional econometric and modern machine learning techniques.
Forecasting future trends in economic or business data is a critical task for many professionals. This tool helps you accurately predict future values by taking historical time-series data and applying various forecasting models. It then outputs detailed forecasts, allowing you to analyze and visualize the predictions to inform your decisions. This is ideal for economists, financial analysts, operations managers, or anyone relying on robust future predictions.
No commits in the last 6 months.
Use this if you need a reliable way to generate, combine, and rigorously evaluate out-of-sample forecasts for time-series data, ensuring no look-ahead bias.
Not ideal if your primary goal is to analyze relationships within historical data rather than predict future values, or if you only need a single, one-time forecast.
Stars
11
Forks
2
Language
R
License
GPL-3.0
Category
Last pushed
Mar 30, 2021
Commits (30d)
0
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