Datasets and code for CS226 (Machine Learning) Research Project (December 2016). The endproduct is a reversible jump Markov Chain Monte Carlo algorithm to define the appropriate clusters of genetic ancestry with a sample of human genomes.

Homework done in R

Applied analysis on the Bayesian student-t "Robust" regression model with Jeffrey's prior. Compared its model performance and robustness of posterior distributions with the Gaussian model when outliers are present.

⏪ R package for: Reconstructing Etiology with Binary Decomposition

Statistical models and proofs done for my Bayesian Statistics and Markov Chain/Monte Carlo class at Yale. Original problem statements and prompts available upon request!

Applies Bayesian techniques for analysing various factors that can influence a UK university's graduate prospects rating from the HESA SFR247 and Complete University Guide table.

Metropolis and Nested Sampling in R

This repository contains code for the paper `Sequential Monte Carlo algorithms for agent-based models of disease transmission' by Nianqiao (Phyllis) Ju, Jeremy Heng and Pierre Jacob.

Markov Chain Monte Carlo Simulation for COVID-19 Incidence.

Stochastic Approximation Cut Algorithm for Inference in Modularised Bayesian Models

A stokhazesthai (stochastic) process, also called a random process, is one in which outcomes are uncertain (MAT 455, ISU).

Simulation of COVID-19 cases arising from high-risk contacts

Efficient MCMC Algorithm for Fitting the Semi-Markov Stochastic SIR Model to Incidence Counts.

A lightweight R-language implementation of the affine-invariant sampling method of Goodman & Weare (2010)

Simulation of markov chain.

Bayesian analysis of children's height data from Galton's experiment. Finished 2022

Radial neighbors GP

Reconstruction of Transmission Chains from Surveillance Data

A friendly MCMC framework

Bayesian Methods for State Space Models