magi: MAnifold-Constrained Gaussian Process Inference

Provides fast and accurate inference for the parameter estimation problem in Ordinary Differential Equations, including the case when there are unobserved system components. Implements the MAGI method (MAnifold-constrained Gaussian process Inference) of Yang, Wong, and Kou (2021) <doi:10.1073/pnas.2020397118>. A user guide is provided by the accompanying software paper Wong, Yang, and Kou (2024) <doi:10.18637/jss.v109.i04>.

Version: 1.2.4
Depends: R (≥ 3.6.0)
Imports: Rcpp (≥ 1.0.6), gridExtra, gridBase, grid, methods, deSolve
LinkingTo: Rcpp, RcppArmadillo, BH, roptim
Suggests: testthat, mvtnorm, covr, knitr, MASS, rmarkdown, markdown
Published: 2024-06-22
DOI: 10.32614/CRAN.package.magi
Author: Shihao Yang ORCID iD [aut, cre], Samuel W.K. Wong ORCID iD [aut], S.C. Kou [ctb, cph] (Contributor of MAGI method development)
Maintainer: Shihao Yang <shihao.yang at>
License: MIT + file LICENSE
NeedsCompilation: yes
Citation: magi citation info
Materials: README
In views: DifferentialEquations
CRAN checks: magi results


Reference manual: magi.pdf
Vignettes: magi-vignette


Package source: magi_1.2.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): magi_1.2.4.tgz, r-oldrel (arm64): magi_1.2.4.tgz, r-release (x86_64): magi_1.2.4.tgz, r-oldrel (x86_64): magi_1.2.3.tgz
Old sources: magi archive


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