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}
Applied Time Series Analysis - course website repository.
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.
A Graphical User Interface-Based R Package for Species Distribution Modeling
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