GPBayes
0.1.0-6Tools for Gaussian Process Modeling in Uncertainty Quantification
Overview
Gaussian processes ('GPs') have been widely used to model spatial data, 'spatio'-temporal data, and computer experiments in diverse areas of statistics including spatial statistics, 'spatio'-temporal statistics, uncertainty quantification, and machine learning. This package creates basic tools for fitting and prediction based on 'GPs' with spatial data, 'spatio'-temporal data, and computer experiments. Key characteristics for this GP tool include: (1) the comprehensive implementation of various covariance functions including the 'Matérn' family and the Confluent 'Hypergeometric' family with isotropic form, tensor form, and automatic relevance determination form, where the isotropic form is widely used in spatial statistics, the tensor form is widely used in design and analysis of computer experiments and uncertainty quantification, and the automatic relevance determination form is widely used in machine learning; (2) implementations via Markov chain Monte Carlo ('MCMC') algorithms and optimization algorithms for GP models with all the implemented covariance functions. The methods for fitting and prediction are mainly implemented in a Bayesian framework; (3) model evaluation via Fisher information and predictive metrics such as predictive scores; (4) built-in functionality for simulating 'GPs' with all the implemented covariance functions; (5) unified implementation to allow easy specification of various 'GPs'.
Install
Health
- OK2026-04-2512 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-04-2212 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-1811 OK · 2 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-04-1012 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-0911 OK · 2 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
Show 1 earlier snapshots
- NOTE2026-03-1012 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 97%
- Return-value docs
- 100%
- References docs
- 8%
Downloads
Repository
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Repository practices
Checks run against github.com/pulongma/gpbayes on 2026-07-19.
No development-tooling practices detected in the upstream repository.
Dependencies
Code & Tests
People & History
7 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- 0.1.0-6Latest
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 0.1.0-5.12023-02-01 · diff ↗
- unarchivedReturned to CRAN2023-02-01
- archivedRemoved from CRAN2023-01-26configure issues were not corrected in time
- 0.1.0-52023-01-12 · diff ↗
- 0.1.0-42022-08-06 · diff ↗
- RR 4.2.0 released · 2022-04-22
- 0.1.0-32021-12-03 · diff ↗
- 0.1.0-2.12021-10-08 · diff ↗
- 0.1.0-22021-09-13
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2021-09-13
- Total releases
- 7 / 5 yrs
- License
- GPL (>= 2) OSI
- Download size
- 119 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet