Implementation of the 'bisque' strategy for approximate Bayesian posterior inference. See Hewitt and Hoeting (2019) <arXiv:1904.07270> for complete details. 'bisque' combines conditioning with sparse grid quadrature rules to approximate marginal posterior quantities of hierarchical Bayesian models. The resulting approximations are computationally efficient for many hierarchical Bayesian models. The 'bisque' package allows approximate posterior inference for custom models; users only need to specify the conditional densities required for the approximation.
Package details 


Author  Joshua Hewitt 
Maintainer  Joshua Hewitt <[email protected]> 
License  GPL3 
Version  1.0.1 
Package repository  View on CRAN 
Installation 
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