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 that can be used to reproduce the results presented in the paper "Accounting for shared covariates in semi-parametric Bayesian additive regression trees".

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

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

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.

Modeling Mortgage Customer Retention with Binary Logistic Regression

PGR generalised linear modelling course

Some solutions to Wood's Generalised Additive Models book.

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.