Implementing MCMC sampling from scratch in R for various Bayesian models

🚫 ↩️ A document that introduces Bayesian data analysis.

machine learning

Latent Dirichlet Allocation

Bayesian Statistics MOOC by Coursera - Solutions in Python

A Python library designed to swiftly and effortlessly obtain the UNIFAC-like groups from molecules by their names and subsequently integrate them into inputs for thermodynamic libraries. UNIFAC, PSRK, and Joback models are implemented.

R implementation of the Thermodynamic Equation Of Seawater - 2010 (TEOS-10)

Bayesian Analysis, No Gibbs

Rate Stabilizing Tool R Package: Gibbs Samplers for Bayesian Spatiotemporal CAR Models

Package to do Bayesian inference with Gibbs sampler

This repo contains the codes in R and Cpp to replicate the original proposal of Linkletter for Bayesian Spatial Process Models for Social Network Analysis and our proposal using an estimation of the likelihood function.

The iterated block Gibbs sampler algorithm

Julia implementation of TEOS-10 GSW based on wrappers of GSW-C

Here is the simulation data for Variable selection in high dimension via Gibbs sampler

Gibbs Sampling & EM Algorithm Implementation / R Programming Language / on Iris Dataset

Gibbs 3.2 formerly located at http://ccmbweb.ccv.brown.edu/gibbs/gibbs.html

Notebook for implementing Monte Carlo techniques (Metropolis-Hastings and Augmented Gibbs) to solve a Bayesian Probit regression.

Rapport pour l'enseignement de Mathématiques appliquées suivi à l'UTC