dynamite: An R Package for Dynamic Multivariate Panel Models

TL;DR

dynamite is an R package that facilitates Bayesian inference for complex multivariate panel data, supporting flexible modeling, efficient computation, and comprehensive diagnostics.

Contribution

It introduces a user-friendly R package that enables flexible Bayesian modeling of multivariate panel data with advanced features and efficient MCMC estimation.

Findings

Supports joint modeling of multiple responses

Provides efficient MCMC-based inference

Includes tools for visualization and diagnostics

Abstract

dynamite is an R package for Bayesian inference of intensive panel (time series) data comprising multiple measurements per multiple individuals measured in time. The package supports joint modeling of multiple response variables, time-varying and time-invariant effects, a wide range of discrete and continuous distributions, group-specific random effects, latent factors, and customization of prior distributions of the model parameters. Models in the package are defined via a user-friendly formula interface, and estimation of the posterior distribution of the model parameters takes advantage of state-of-the-art Markov chain Monte Carlo methods. The package enables efficient computation of both individual-level and aggregated predictions and offers a comprehensive suite of tools for visualization and model diagnostics.