BKP: Beta Kernel Process Modeling
Implements the Beta Kernel Process (BKP) for nonparametric modeling of spatially varying binomial probabilities, together with its extension, the Dirichlet Kernel Process (DKP), for categorical or multinomial data. The package provides functions for model fitting, predictive inference with uncertainty quantification, posterior simulation, and visualization in one-and two-dimensional input spaces. Multiple kernel functions (Gaussian, Matern 5/2, and Matern 3/2) are supported, with hyperparameters optimized through multi-start gradient-based search. For more details, see Zhao, Qing, and Xu (2025) <doi:10.48550/arXiv.2508.10447>.
| Version: | 0.2.3 |
| Depends: | R (≥ 3.5.0) |
| Imports: | dirmult,gridExtra,lattice,optimx,tgp |
| Suggests: | knitr,mlbench,testthat (≥ 3.0.0) |
| Published: | 2025-09-22 |
| DOI: | 10.32614/CRAN.package.BKP |
| Author: | Jiangyan Zhao [cre, aut], Kunhai Qing [aut], Jin Xu [aut] |
| Maintainer: | Jiangyan Zhao <zhaojy2017 at 126.com> |
| BugReports: | https://github.com/Jiangyan-Zhao/BKP/issues |
| License: | GPL (≥ 3) |
| URL: | https://github.com/Jiangyan-Zhao/BKP |
| NeedsCompilation: | no |
| Citation: | BKP citation info |
| Materials: | README,NEWS |
| CRAN checks: | BKP results |
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