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binaryGP

0.2Package record

Fit and Predict a Gaussian Process Model with (Time-Series) Binary Response

0packages depend
6.7Kdownloads / year
–test coverage
11/13flavors OK

Overview

About

Allows the estimation and prediction for binary Gaussian process model. The mean function can be assumed to have time-series structure. The estimation methods for the unknown parameters are based on penalized quasi-likelihood/penalized quasi-partial likelihood and restricted maximum likelihood. The predicted probability and its confidence interval are computed by Metropolis-Hastings algorithm. More details can be seen in Sung et al (2017) arXiv:1705.02511.

Install

Health

CRAN checks
2NOTE11OK
Check messages
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Chih-Li Sung <iamdfchile@gmail.com>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: person(given = "Chih-Li",
                    family = "Sung",
                    role = c("aut", "cre"),
                    email = "iamdfchile@gmail.com")
as necessary.

The Description field contains
  can be seen in Sung et al (2017) <arXiv:1705.02511>.
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.

CRAN check page ↗

Slowest check: 3.0 min · r-devel-windows-x86_64
Status changes
  • NOTE11 OK, 2 NOTENow
  • NOTE9 OK, 5 NOTE2026-04-22
  • ERROR8 OK, 5 NOTE, 1 ERROR2026-04-18
  • NOTE9 OK, 5 NOTE2026-03-10
Advisories

none known

Documentation

In release 0.2
READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
4
Examples that run
100%4 run in a plain check
Exported functions with examples
100%
Documented parameters
82%
Return-value docs
100%
Help pages citing references
0%

Downloads

6.7K
CRAN downloads in the past year
Rank #7,662 · ~18/day · ~556/mo
Daily download trend is not available in this view yet.
36230 days
1.2K90 days
6.7K1 year
Compare downloads with other packages →
Also on371 r2u50 autocran

Dependencies

Declared dependencies
7 external dependencies (excludes base and recommended)

Installing binaryGP adds 6 packages (4 with compiled code, 5.3 MB of source tarballs). Heaviest: nloptr 2.1 MB, Rcpp 1.8 MB, RcppArmadillo 1.0 MB.

Depends (1)
R >= 2.14.1
Imports (9)
RcpplhslogitnormnloptrGPfitstatsgraphicsutilsmethods
LinkingTo (2)
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (from the free-text Author field) (1)

Maintainer since 0.2 (2017)

Releases (1)
  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • R
    R 3.5.0 released · 2018-04-23
  • 0.2Latest
    2017-09-19 · current release
  • R
    R 3.4.0 released · 2017-04-21

Package metadata

First published
2017-09-19
Total releases
1 / 9 yrs
License
GPL-2 | GPL-3 OSI
Minimum R
≥ 2.14.1
Download size
14 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("binaryGP")

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for binaryGP version 0.2 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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