Package: bisque
Type: Package
Title: Approximate Bayesian Inference via Sparse Grid Quadrature
        Evaluation (BISQuE) for Hierarchical Models
Version: 1.0.2
Date: 2020-02-03
Author: Joshua Hewitt
Maintainer: Joshua Hewitt <joshua.hewitt@duke.edu>
Description: 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.
License: GPL-3
RoxygenNote: 7.0.2
Suggests: testthat, fields
Depends: R (>= 3.0.2)
Imports: mvQuad, Rcpp, foreach, itertools
LinkingTo: Rcpp (>= 0.12.4), RcppArmadillo, RcppEigen (>= 0.3.3.3.1)
SystemRequirements: A system with a recent-enough C++11 compiler (such
        as g++-4.8 or later).
NeedsCompilation: yes
Encoding: UTF-8
Packaged: 2020-02-04 21:19:26 UTC; pointdex
Repository: CRAN
Date/Publication: 2020-02-06 00:40:03 UTC
Built: R 4.4.0; aarch64-apple-darwin20; 2024-04-05 23:27:25 UTC; unix
Archs: bisque.so.dSYM
