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BKP: Beta Kernel Process Modeling

Implements the Beta Kernel Process (BKP) for nonparametric modeling of covariate-dependent binomial probabilities, and the Dirichlet Kernel Process (DKP) for categorical or multinomial response data. Scalable global-local approximations are provided through TwinBKP and TwinDKP, using twinning-selected global subsets and local nearest-neighbour updates. Functions are included for model fitting, predictive inference with uncertainty quantification, posterior simulation, and visualization in one- and two-dimensional input spaces. Gaussian, Matern 5/2, Matern 3/2, and Wendland kernels are supported, with hyperparameters selected by multi-start derivative-free optimization. For more details, see Zhao, Qing, and Xu (2025) <doi:10.48550/arXiv.2508.10447>.

Version: 0.3.1
Depends: R (≥ 3.5.0)
Imports: dirmult, ggplot2, gridExtra, lattice, nloptr, rlang, Rcpp, tgp
LinkingTo: Rcpp, RcppArmadillo, nloptr
Suggests: knitr, mlbench, testthat (≥ 3.0.0)
Published: 2026-07-13
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)
Copyright: See inst/COPYRIGHTS
BKP copyright details
URL: https://github.com/Jiangyan-Zhao/BKP, https://github.com/Jiangyan-Zhao/BKP-paper
NeedsCompilation: yes
Citation: BKP citation info
Materials: README, NEWS
CRAN checks: BKP results

Documentation:

Reference manual: BKP.html , BKP.pdf

Downloads:

Package source: BKP_0.3.1.tar.gz
Windows binaries: r-devel: BKP_0.3.1.zip, r-release: BKP_0.3.1.zip, r-oldrel: BKP_0.3.1.zip
macOS binaries: r-release (arm64): BKP_0.3.1.tgz, r-oldrel (arm64): BKP_0.3.1.tgz, r-release (x86_64): BKP_0.3.1.tgz, r-oldrel (x86_64): BKP_0.3.1.tgz
Old sources: BKP archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=BKP to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.