Title: An Empirical Bayes Method for Chi-Squared Data
Description: We provide the main R functions to compute the posterior interval for the noncentrality parameter of the chi-squared distribution. The skewness estimate of the posterior distribution is also available to improve the coverage rate of posterior intervals. Details can be found in Du and Hu (2020) <doi:10.1080/01621459.2020.1777137>.

Author: Anhui Huang; Shizhong Xu; Xiaodong Cai
Description: Empirical Bayesian Elastic Net algorithms.

Description: Provides the Empirical Bayesian Elastic Net for handling multicollinearity in generalized linear regression models.  As a special case of the 'EBglmnet'
package (also available on CRAN), this package encourages a grouping effects to select relevant variables and estimate the corresponding non-zero effects.

Author: Michael D. Ward and Jacob M. Montgomery
Description: Ensemble BMA for logistic regression
Depends: separationplot, ensembleBMA, plyr, methods, Hmisc
Packaged: 2012-06-14 03:15:42 UTC; jacobmontgomery

Author: Jacob M. Montgomery, Florian Hollenbach, and Michael D. Ward
Description: Ensemble BMA for social science data
Depends: separationplot, ensembleBMA, plyr, methods, Hmisc, abind
Packaged: 2012-08-21 01:24:21 UTC; jacobmontgomery

Packaged: 2012-08-22 17:32:54 UTC; jmontgomery

Packaged: 2013-02-25 04:10:10 UTC; jmontgomery

Author: Jacob M. Montgomery, Florian M. Hollenbach, and Michael D. Ward
Maintainer: Florian M. Hollenbach <fhollenbach@tamu.edu>
Description: Ensemble BMA for social science data.
Depends: stats, graphics, separationplot, plyr, methods, Hmisc, abind
Packaged: 2016-02-09 21:35:15 UTC; florianhollenbach

Title: Estimate Ensemble Bayesian Model Averaging Forecasts using Gibbs
Authors@R: c(person("Florian M.", "Hollenbach", email = "fhollenbach@tamu.edu",
person("Jacob M.", "Montgomery", role = c("aut")),
person("Michael D.", "Ward", role = c("aut")))
Description: Create forecasts from multiple predictions using ensemble Bayesian model averaging (EBMA). EBMA models can be estimated using an expectation maximization (EM) algorithm or as fully Bayesian models via Gibbs sampling.
Imports: Rcpp (>= 1.0.2), plyr, graphics, separationplot, Hmisc, abind,
Packaged: 2020-05-20 11:01:56 UTC; florianhollenbach
Author: Florian M. Hollenbach [aut, cre]