Ecological forecasting using Dynamic Generalized Additive Models with R 📦's {mvgam} and {brms}

Bayesian modelling of DNA methylation heterogeneity at single-cell resolution

Core Functionality for Simulating Quantities of Interest from Generalised Linear Models

R scripts and data sets to reproduce the results in the paper "Accounting for shared covariates in semi-parametric Bayesian additive regression trees". The Annals of Applied Statistics (to appear).

Norm Constrained Generalised Linear Model using numpy, numba and scipy.

The project can be split into different sub-projects (easy-medium difficulty: meta-analysis of COVID vaccines; medium-high difficulty: estimating excess mortality due to COVID). Requires skills in R and will require some learning on Bayesian modelling.

R package hosted on CRAN: Generalised linear models calculated by splitting data into smaller chunks (Author: Thomas Lumley)

Experiments for Binarsity: a penalization for one-hot encoded features

The project can be split into different sub-projects (easy difficulty: replication of the published meta-analysis for evidence of gender bias in hiring decisions; medium for newer modelling). Requires skills in R and will require some learning on Bayesian modelling.

Data analysis of Air BnB data in Barcelona and London using a subset of data investigated by Gyódi, K., & Nawaro, Ł. Generalised Linear Models have been fitted to examine weekend price differences and how price changes between the two cities.

Data and R code accompanying article 10.3354/meps14261 in Marine Ecology Progress Series.

my second year poster for the Graduate School Poster Day 2016

Modeling Mortgage Customer Retention with Binary Logistic Regression

All of my R code from the Advanced Statistical Modelling III module at Durham University

PGR generalised linear modelling course

Some solutions to Wood's Generalised Additive Models book.