HBglm: Hierarchical Bayesian Regression for GLMs

Convenient and efficient functions for performing 2-level hierarchical Bayesian regression analysis for multi-group data. The lowest level may belong to the generalized linear model (GLM) family while the prior level, which effects pooling, allows for linear regression on lower level covariates. Constraints on all or part of the parameter set maybe specified with ease. A rich set of methods is included to visualize and analyze results.

Install the latest version of this package by entering the following in R:
AuthorAsad Hasan, Alireza S. Mahani
Date of publication2015-07-14 15:59:53
MaintainerAsad Hasan <asad.hasan@sentrana.com>
LicenseGPL (>= 2)

View on CRAN


coef.hbglm Man page
hbglm Man page
HBglm Man page
hbglm.model.control Man page
hbglm.sampler.control Man page
linear_list Man page
predict.hbglm Man page
print.hbglm Man page
print.summary.hbglm Man page
summary.hbglm Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

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