ProcessMiner/nlcor

nlcor is a niche statistical tool that has failed to gain significant traction since its inception over seven years ago. With only 20 stars and virtually no recent activity (Velocity: 0.0/hr), it represents a stagnant research artifact rather than a living project. The approach—using local linear approximations to estimate global nonlinear correlation—is a standard heuristic in exploratory data analysis but faces stiff competition from more mathematically robust or widely adopted metrics such as Maximal Information Coefficient (MIC), Distance Correlation (dCor), and Mutual Information (MI). While frontier labs are unlikely to specifically 'target' this tool due to its niche nature, the project is effectively displaced by standard features in major data science libraries like scikit-learn (Python) or the 'energy' and 'minerva' packages in R. There is no technical or community moat; the code is easily reproducible and the underlying statistical concept is commodity knowledge.