Package: BKP 0.2.3.9000

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>.

Authors:Jiangyan Zhao [cre, aut], Kunhai Qing [aut], Jin Xu [aut]

BKP_0.2.3.9000.tar.gz
BKP_0.2.3.9000.zip(r-4.7)BKP_0.2.3.9000.zip(r-4.6)BKP_0.2.3.9000.zip(r-4.5)
BKP_0.2.3.9000.tgz(r-4.6-x86_64)BKP_0.2.3.9000.tgz(r-4.6-arm64)BKP_0.2.3.9000.tgz(r-4.5-x86_64)BKP_0.2.3.9000.tgz(r-4.5-arm64)
BKP_0.2.3.9000.tar.gz(r-4.7-arm64)BKP_0.2.3.9000.tar.gz(r-4.7-x86_64)BKP_0.2.3.9000.tar.gz(r-4.6-arm64)BKP_0.2.3.9000.tar.gz(r-4.6-x86_64)
BKP_0.2.3.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
BKP/json (API)
NEWS

# Install 'BKP' in R:
install.packages('BKP', repos = c('https://jiangyan-zhao.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jiangyan-zhao/bkp/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

bayesian-nonparametric-modelsbeta-binomialbeta-kernel-processbeta-processdirichlet-kernel-processdirichlet-multinomialdirichlet-processkernel-methodsopenblascppopenmp

4.20 score 1 stars 1 scripts 204 downloads 8 exports 30 dependencies

Last updated from:dbc49e5058. Checks:12 OK, 1 ERROR. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK203
linux-devel-x86_64OK210
source / vignettesOK220
linux-release-arm64OK217
linux-release-x86_64OK203
macos-release-arm64ERROR134
macos-release-x86_64OK498
macos-oldrel-arm64OK179
macos-oldrel-x86_64OK278
windows-develOK200
windows-releaseOK243
windows-oldrelOK216
wasm-releaseOK148

Exports:fit_BKPfit_DKPfit_TwinBKPfit_TwinDKPget_priorkernel_matrixloss_funparameter

Dependencies:cliclustercpp11dirmultfarverggplot2gluegridExtragtableisobandlabelinglatticelifecyclemaptreenloptrnumDerivoptimxpracmaR6RColorBrewerRcppRcppArmadillorlangrpartS7scalestgpvctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Beta Kernel Process ModelingBKP-package
Fit a Beta Kernel Process (BKP) Modelfit_BKP
Fit a Dirichlet Kernel Process (DKP) Modelfit_DKP
Fit a Twin Beta Kernel Process (TwinBKP) Modelfit_TwinBKP
Fit a Twin Dirichlet Kernel Process (TwinDKP) Modelfit_TwinDKP
Extract BKP or DKP Model Fitted Valuesfitted fitted.BKP fitted.DKP fitted.TwinBKP fitted.TwinDKP
Construct Prior Parameters for BKP/DKP Modelsget_prior
Compute Kernel Matrix Between Input Locationskernel_matrix
Loss Function for BKP and DKP Modelsloss_fun
Extract Model Parameters from a Fitted BKP or DKP Modelparameter parameter.BKP parameter.DKP
Plot Fitted BKP or DKP Modelsplot plot.BKP plot.DKP plot.TwinBKP plot.TwinDKP
Posterior Prediction for BKP or DKP Modelspredict predict.BKP predict.DKP
Predict from a Fitted TwinBKP Modelpredict.TwinBKP
Predict from a Fitted TwinDKP Modelpredict.TwinDKP
Print Methods for BKP and DKP Objectsprint print.BKP print.DKP print.predict_BKP print.predict_DKP print.predict_TwinDKP print.simulate_BKP print.simulate_DKP print.simulate_TwinBKP print.simulate_TwinDKP print.summary_BKP print.summary_DKP print.summary_TwinBKP print.summary_TwinDKP print.TwinBKP print.TwinDKP
Posterior Quantiles from a Fitted BKP or DKP Modelquantile quantile.BKP quantile.DKP quantile.TwinBKP quantile.TwinDKP
Simulate from a Fitted BKP or DKP Modelsimulate simulate.BKP simulate.DKP simulate.TwinBKP simulate.TwinDKP
Summary of a Fitted BKP or DKP Modelsummary summary.BKP summary.DKP summary.TwinBKP summary.TwinDKP