bayesian-regression

Global Horizontal Irradiance Analysis using Support Vector Regression and Bayesian Ridge Regression

This is the implementation of the five regression methods Least Square (LS), Regularized Least Square (RLS), LASSO, Robust Regression (RR) and Bayesian Regression (BR).

The project analyses the impact of different marketing tactics on the sales of items. The problem is a multivariate-modeling problem as there are 3 different tactics of marketing. Since, the impact of marketing medium cannot be negative we will be using Bayesian model for regression.

Predicting Bitcoin Price Variations using Bayesian Regression

Bayesian Regression of Latent Source Modelling for Predicting Price Variation of Bitcoin

A machine learning pipeline for predicting Bitcoin closing prices using time series data. Includes four models, grid search, and neural network using Keras. Prints predictions and best parameters/scores.

This repository focuses on building linear regression algorithms from scratch using only Numpy for faster array processing.

code for performing Bayesian ARD regression, where covariates have groups

Which areas of England & Wales got healthier from 2011 to 2021, and why? Census pipeline, Bayesian regression and a linked map dashboard.

Electoral forecasting laboratory modeling constrained voter-transition flows via Bayesian regression, constructing synthetic controls, and projecting correlated Monte Carlo seat distributions.

Bayesian calibration of predictive intervals for rat-to-human oral toxicity translation using 289 compound pairs, with reproducible analysis scripts, diagnostic evaluations, and figures to assess cross-species and cross-endpoint uncertainty.

A modular Bayesian inference platform built from scratch using NumPy, implementing MCMC (Metropolis-Hastings) for A/B testing, regression, and probabilistic modeling with YAML-driven experiments, step-level logging, and decision-focused outputs.

Modular Gaussian Process regression framework implementing non-parametric Bayesian inference with customizable kernels, posterior prediction, and calibrated uncertainty estimation.

Research project