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VsusP: Variable Selection using Shrinkage Priors
Bayesian variable selection using shrinkage priors to identify significant variables in high-dimensional datasets. The package includes methods for determining the number of significant variables through innovative clustering techniques of posterior distributions, specifically utilizing the 2-Means and Sequential 2-Means (S2M) approaches. The package aims to simplify the variable selection process with minimal tuning required in statistical analysis.
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Package details |
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| Author | Nilson Chapagain [aut, cre] (<https://orcid.org/0000-0003-2962-2949>), Debdeep Pati [aut] |
| Maintainer | Nilson Chapagain <nilson.chapagain@gmail.com> |
| License | GPL (>= 3) |
| Version | 1.0.0 |
| URL | https://github.com/nilson01/VsusP-variable-selection-using-shrinkage-priors |
| Package repository | View on CRAN |
| Installation |
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