BAyesian Model-Building Interface (Bambi) in Python.
Fast Bayesian Inference in Python. 50+ conjugate models with vectorized updates, sufficient statistic helpers, built-in plotting, and SciPy integration.
The official implementation of "Joint Modeling of Image and Label Statistics for Enhancing Model Generalizability of Medical Image Segmentation" via Pytorch
A professional, research-grade comparison of Gaussian Copula and Variational Autoencoder (VAE) methods for synthetic tabular data generation. Includes full evaluation pipeline with distribution overlap, correlation analysis, PCA projections, pairplots, metrics, and automated visual reports.
An open-source toolkit for comparing and conflating Points of Interest (POIs) across major geospatial datasets.
A collection of scripts used for modeling global daily maximum surges
Implementation is to use gradient descent to find the optimal values of θ that minimize the cost function.
Fitness estimates of SARS-CoV-2 variants
Python package for conducting power analysis for experiments using regression and/or clustered data.
Pure-Python library of heavy-tailed probability distributions (Pareto, Burr, LogNormal, etc.) built from first principles.
Open-source Life Cycle Assessment engine that scores any consumer product's environmental footprint using activity-based emission factors, Monte Carlo simulation, and machine learning. Includes FastAPI backend, Streamlit dashboard, and Jupyter notebooks.
A 15-year longitudinal study evaluating climate covariates in national-scale dengue forecasting. Contrasts SARIMA and Random Forest models under strict rolling-origin validation.
🧑🎨 Generate and compare synthetic tabular data using Gaussian Copula and Variational Autoencoders for enhanced analytics and model prototyping.
Data science projects created using actual data, using Python and R.
RNS-Seq Count Model Explorer
Predict Fantasy Premier League (FPL) points using two models: a Random Forest regression (ML_xP.py) and a custom statistical model (xP_FPL.py). This project explores different approaches to predicting player performance, with a detailed comparison for Gameweek 5 of the 2024/25 EPL season.
A/B testing framework for two-sided marketplaces designed to mitigate estimation bias caused by marketplace interference.
Entity prioritization and escalation detection using GLMM statistical models
Research-grade backtester for sports-betting strategies on 1X2 markets. Walk-forward evaluation, bootstrap CIs, Betfair-style commission.
A Machine Learning modeling pipeline that predicts customer churn of an organization based on customer historical behavior
Add a description, image, and links to the statistical-modeling topic page so that developers can more easily learn about it.
To associate your repository with the statistical-modeling topic, visit your repo's landing page and select "manage topics."