Ecological forecasting using Dynamic Generalized Additive Models with R 📦's {mvgam} and {brms}
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Updated
Jun 11, 2024 - HTML
Ecological forecasting using Dynamic Generalized Additive Models with R 📦's {mvgam} and {brms}
Core Functionality for Simulating Quantities of Interest from Generalised Linear Models
Bayesian modelling of DNA methylation heterogeneity at single-cell resolution
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.
PGR generalised linear modelling course
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
R package hosted on CRAN: Generalised linear models calculated by splitting data into smaller chunks (Author: Thomas Lumley)
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
Experiments for Binarsity: a penalization for one-hot encoded features
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.
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.
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