binaryGP
0.2Fit and Predict a Gaussian Process Model with (Time-Series) Binary Response
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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.
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- NOTE r-devel-linux-x86_64-debian-clang
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Slowest check: 2.3 min · r-oldrel-windows-x86_64
Code health
None
Tests · ratio 0.00
not tracked
Coverage
100%
Documentation · exports
9
Dependencies · direct
Check history
- NOTE2026-04-229 OK · 5 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-188 OK · 5 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-03-109 OK · 5 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
Documentation
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- Examples that run
- 100%
- Documented parameters
- 82%
- Return-value docs
- 100%
- References docs
- 0%
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Also on405 r2u20 autocran
Dependencies
Declared dependencies
7 external dependencies (excludes base and recommended)
Depends (1)
R >= 2.14.1
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none
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none
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Listed in earlier versions (1)
no longer listed · 0.2
Package Timeline
1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.2Latest2026-03-10 · current release
- RR 4.5.0 released · 2025-04-11
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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
- Installed size
- not tracked yet
- With dependencies
- not tracked yet