Bayesian Modeling and Causal Inference for Multivariate Longitudinal Data
Compute Lagging Values of an Imputed Response
Compute Leading Values of an Imputed Response
Return the Number of Posterior Draws of a dynamitefit Object
Extract the Number of Observations Used to Fit a Dynamite Model
Plots for dynamitefit Objects
Extract Samples From a dynamitefit Object as a Data Frame
Extract Samples From a dynamitefit Object as a Data Table
Convert dynamite Output to draws_df Format
Extract Regression Coefficients of a Dynamite Model
Credible Intervals for Dynamite Model Parameters
Estimate a Bayesian Dynamic Multivariate Panel Model With Multiple Imp...
Deprecated Functions in the dynamite Package
Diagnostic Values of a Dynamite Model
The dynamite package.
Estimate a Bayesian Dynamic Multivariate Panel Model
Model formula for dynamite
Extract Fitted Values of a Dynamite Model
Extract the Stan Code of the Dynamite Model
Extract the Model Data of the Dynamite Model
Get Parameter Dimensions of the Dynamite Model
Get Parameter Names of the Dynamite Model
Get Parameter Types of the Dynamite Model
Get Prior Definitions of a Dynamite Model
HMC Diagnostics for a Dynamite Model
Add Lagged Responses as Predictors to Each Channel of a Dynamite Model
Define a Common Latent Factor for the Dynamite Model.
Approximate Leave-Future-Out (LFO) Cross-validation
Approximate Leave-One-Out (LOO) Cross-validation
Plot the Model Structure as a Directed Acyclic Graph (DAG)
Diagnostic Plot for Pareto k Values from LFO
Predict Method for a Dynamite Model
Print the results from the LFO
Additional Specifications for the Group-level Random Effects of the DM...
Define the B-splines Used for the Time-varying Coefficients of the Mod...
Update a Dynamite Model
Easy-to-use and efficient interface for Bayesian inference of complex panel (time series) data using dynamic multivariate panel models by Helske and Tikka (2024) <doi:10.1016/j.alcr.2024.100617>. The package supports joint modeling of multiple measurements per individual, time-varying and time-invariant effects, and a wide range of discrete and continuous distributions. Estimation of these dynamic multivariate panel models is carried out via 'Stan'. For an in-depth tutorial of the package, see (Tikka and Helske, 2024) <doi:10.48550/arXiv.2302.01607>.
Useful links