Fortran Statistics and Machine Learning Library
A modern Fortran statistical library.
Statistical evaluation framework for AI agents
AI Firewall and guardrails for LLM-based Elixir applications
Significant Network Interval Mining
High-performance statistical testing and regression for Polars DataFrames, powered by Rust.
Quantitative research tool analyzing stock performance around US Thanksgiving. 354 stocks, 8,293 observations (2000-2024). Statistical significance testing included.
Statistical tests in Rust
Customer base analysis is concerned with using the observed past purchase behavior of customers to understand their current and likely future purchase patterns. More specifically, as developed in Schmittlein et al. (1987), customer base analysis uses data on the frequency, timing, and dollar value of each customer's past purchases
From idea to statistically validated trade setup. VARRD is more than a back tester you can query with natural language — it's your home for safely researching market edges without the invisible statistical mistakes that invalidate most backtests. Let your agent autonomously discover edges with peace of mind.
This repository is a fork of a repository originally created by Lucas Descause. It is the codebase used for my Master's dissertation "Reinforcement Learning with Function Approximation in Continuing Tasks: Discounted Return or Average Reward?" which was also an extension of Luca's work.
Yeast TMT data - 3 different carbon sources (from Gygi lab) analyzed with PAW pipeline and MaxQuant
Zero-error LLM execution via SPRT voting. Rust library and MCP server implementing the MAKER algorithm for mathematically-grounded error correction in long-horizon AI agent tasks. Research experiment based on arXiv:2511.09030
MATLAB functions for Beta distribution test
Multivariate analysis (MVA) of high dimensional heterogeneous data
Analysis of 2.2 million Realtor.com listings using Python and machine learning to uncover U.S. real estate market patterns. The project identifies market segments, predicts property prices, and reveals regional trends, providing data-driven insights for real estate professionals and investors.
Analytical workflow for Superstore Business Insights: identifies key profitability drivers via statistical tests and quantile regression. Includes data cleaning, hypothesis testing, model checks, and actionable recommendations from SampleSuperstoreClean.csv.
Fairness and bias detection library for Elixir AI/ML systems
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