Installation
About
Implements a Bayesian-like approach to the high-dimensional sparse linear regression problem based on an empirical or data-dependent prior distribution, which can be used for estimation/inference on the model parameters, variable selection, and prediction of a future response. The method was first presented in Martin, Ryan and Mess, Raymond and Walker, Stephen G (2017) doi:10.3150/15-BEJ797. More details focused on the prediction problem are given in Martin, Ryan and Tang, Yiqi (2019)
Key Metrics
Downloads
Yesterday | 9 0% |
Last 7 days | 71 +78% |
Last 30 days | 224 +8% |
Last 90 days | 582 +11% |
Last 365 days | 2.311 -10% |
Maintainer
Maintainer | Yiqi Tang |