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.
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