Papageorgiou, Georgios (2018) BNSP: an R Package for fitting Bayesian semiparametric regression models and variable selection. The R Journal 10 (2), pp. 526-548. ISSN 2073-4859.
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Abstract
The R package BNSP provides a unified framework for semiparametric location-scale regression and stochastic search variable selection. The statistical methodology that the package is built upon utilizes basis function expansions to represent semiparametric covariate effects in the mean and variance functions, and spike-slab priors to perform selection and regularization of the estimated effects. In addition to the main function that performs posterior sampling, the package includes functions for assessing convergence of the sampler, summarizing model fits, visualizing covariate effects and obtaining predictions for new responses or their means given feature/covariate vectors.
Metadata
| Item Type: | Article |
|---|---|
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
| Depositing User: | Georgios Papageorgiou |
| Date Deposited: | 15 Oct 2018 07:07 |
| Last Modified: | 09 Aug 2023 12:45 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/24480 |
Available Versions of this Item
- BNSP: an R Package for fitting Bayesian semiparametric regression models and variable selection. (deposited 15 Oct 2018 07:07) [Currently Displayed]
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