{mvgam} R 📦 to fit Dynamic Bayesian Generalized Additive Models for time series analysis and forecasting

Functions for using GAMs to model time series

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

This repository contains data, code and outputs related to the paper titled "A Bayesian approach to integrate and impute South American migration flows using residence permit data".

This is the repository used to make the project titled 'Grass Pollen in Cape Town: A Comparison of Generalised Additive Models and Random Forests' by Sky Cope and Chloë Stipinovich.

Forecasting Oil Prices with Time Series & Generalized Additive Models for Location, Scale and Shape

Some solutions to Wood's Generalised Additive Models book.

Prediction of the adjusted electricity sales using simple machine learning algorithms like linear regression, GAMs, MARS and Random Forests

This report uncovers Youtube identifiers for a viral video using the application of statistical methodologies and text analysis

This study utilised a 20-year dataset of seal counts from the Solent region of southeast England. Generalised additive models (GAMs) were used to examine yearly and seasonal trends in seal counts. This repository contains the raw data and code for analysis.

Shiny App to visualise and fit a GAM