Ecological forecasting using Dynamic Generalized Additive Models with R 📦's {mvgam} and {brms}
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Updated
May 30, 2024 - HTML
Ecological forecasting using Dynamic Generalized Additive Models with R 📦's {mvgam} and {brms}
R package to run Bayesian MMRMs using {brms}
Work on Bayesian growth mixture models including hidden Markov chains and softmax regressions for representing latent class memberships.
Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
Estimate Realtime Case Counts and Time-varying Epidemiological Parameters
Pre-compiled CmdStan models in R packages
An R package and Bayesian generative model to estimate effective reproduction numbers from wastewater concentration measurements over time.
Repository for the "Bayesian Statistics" course, MSc degree in Data Science & AI (University of Trieste)
{mvgam} R 📦 to fit Dynamic Bayesian Generalized Additive Models for time series analysis and forecasting
brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
Bayesian Inference of Complex Panel Data
A sklearn style interface to Stan regression models
This repository holds slides and code for a full Bayesian statistics graduate course.
RStan, the R interface to Stan
Translate System Dynamics models (Stella, Vensim) into R
The Stan Math Library is a C++ template library for automatic differentiation of any order using forward, reverse, and mixed modes. It includes a range of built-in functions for probabilistic modeling, linear algebra, and equation solving.
CmdStanR: the R interface to CmdStan
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