From e561a9efd9076b66ad65a657160e082f9c4d145c Mon Sep 17 00:00:00 2001 From: cesare panzeri Date: Wed, 25 Mar 2026 09:55:49 +0100 Subject: [PATCH] Fix OmniOracle description: lagged MI, not Granger (#293) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * Add OmniOracle — automatic statistical discovery engine Co-Authored-By: Claude Opus 4.6 (1M context) * fix: correct OmniOracle description (lagged MI, not Granger causality) --------- Co-authored-by: Claude Opus 4.6 (1M context) --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 6ea55f9..fd13c30 100644 --- a/README.md +++ b/README.md @@ -222,7 +222,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [tsmoothie](https://github.com/cerlymarco/tsmoothie) - A python library for time-series smoothing and outlier detection in a vectorized way. - [pmdarima](https://github.com/alkaline-ml/pmdarima) - A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function. - [gluon-ts](https://github.com/awslabs/gluon-ts) - vProbabilistic time series modeling in Python. -- [OmniOracle](https://github.com/cesabici-bit/omni-oracle) - Automatic discovery of non-trivial statistical relationships across 500+ time series from FRED, World Bank, EIA, and NOAA using mutual information screening, Granger causality, and FDR correction. +- [OmniOracle](https://github.com/cesabici-bit/omni-oracle) - Automatic discovery of non-trivial statistical relationships across 500+ time series from FRED, World Bank, EIA, and NOAA using mutual information screening, lagged MI directional testing, and FDR correction. - [functime](https://github.com/functime-org/functime) - Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data. ### Calendars