% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/BayesRTMB_package.R
\docType{package}
\name{BayesRTMB-package}
\alias{BayesRTMB}
\alias{BayesRTMB-package}
\title{BayesRTMB: Bayesian Modeling with RTMB}
\description{
The `BayesRTMB` package provides an intuitive, R-based Bayesian modeling
environment using the `RTMB` package as its computational backend.
It allows users to perform Maximum A Posteriori (MAP) estimation,
Markov Chain Monte Carlo (MCMC) sampling, and Automatic Differentiation
Variational Inference (ADVI) for hierarchical and complex non-linear models
through a unified and user-friendly interface.
}
\details{
The standard workflow of the package consists of three main steps:

1. **Model Definition**: Use [rtmb_code()] to define the model structure
   (likelihood, prior distributions, transformations, etc.) using standard R syntax.
2. **Model Instantiation**: Pass the data and the generated model code to
   [rtmb_model()] to create an `RTMB_Model` R6 object.
3. **Estimation**: Call the appropriate method on the model object:
   * `$optimize()`: For MAP estimation and Laplace approximation.
   * `$sample()`: For MCMC sampling using the No-U-Turn Sampler (NUTS).
   * `$variational()`: For approximate Bayesian inference using ADVI.

For more detailed examples and tutorials, please refer to the package vignettes.
}
\seealso{
Useful links:
* [https://github.com/norimune/BayesRTMB](https://github.com/norimune/BayesRTMB)
* Report bugs at [https://github.com/norimune/BayesRTMB/issues](https://github.com/norimune/BayesRTMB/issues)
}
\author{
\strong{Maintainer}: Hiroshi Shimizu \email{simizu706@gmail.com}

}
\keyword{internal}
