Implementing MCMC sampling from scratch in R for various Bayesian models
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Updated
Dec 7, 2023 - HTML
Implementing MCMC sampling from scratch in R for various Bayesian models
🚫 ↩️ A document that introduces Bayesian data analysis.
machine learning
Bayesian Statistics MOOC by Coursera - Solutions in Python
A Python library designed to swiftly and effortlessly obtain the UNIFAC groups from molecules by their names and subsequently integrate them into inputs for thermodynamic libraries.
R implementation of the Thermodynamic Equation Of Seawater - 2010 (TEOS-10)
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.
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Notebook for implementing Monte Carlo techniques (Metropolis-Hastings and Augmented Gibbs) to solve a Bayesian Probit regression.
Gibbs 3.2 formerly located at http://ccmbweb.ccv.brown.edu/gibbs/gibbs.html
Implementing a Skill-based rating system using probabilistic modelling and Gibbs sampling
Rapport pour l'enseignement de Mathématiques appliquées suivi à l'UTC
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