Package: sparsereg
Type: Package
Title: Sparse Bayesian Models for Regression, Subgroup Analysis, and
        Panel Data
Version: 1.2
Date: 2016-03-01
Author: Marc Ratkovic and Dustin Tingley
Maintainer: Marc Ratkovic <ratkovic@princeton.edu>
Description: Sparse modeling provides a mean selecting a small number of non-zero effects from a large possible number of candidate effects.  This package includes a suite of methods for sparse modeling: estimation via EM or MCMC, approximate confidence intervals with nominal coverage, and diagnostic and summary plots.  The method can implement sparse linear regression and sparse probit regression.  Beyond regression analyses, applications include subgroup analysis, particularly for conjoint experiments, and panel data. Future versions will include extensions to  models with truncated outcomes, propensity score, and instrumental variable analysis.
License: GPL (>= 2)
Depends: R (>= 3.0.2), MASS, ggplot2
Imports: Rcpp (>= 0.11.0), msm, VGAM, MCMCpack, coda, glmnet,
        gridExtra, grid, GIGrvg
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2016-03-02 17:11:07 UTC; ratkovic
Repository: CRAN
Date/Publication: 2016-03-10 23:32:18
Built: R 4.4.3; x86_64-w64-mingw32; 2025-10-21 13:49:01 UTC; windows
Archs: x64
