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>.

Version: 1.2.0
Depends: R (≥ 3.5.0)
Imports: Rcpp (≥ 1.0.6), gridExtra, gridBase, grid, methods, deSolve
LinkingTo: Rcpp, RcppArmadillo, BH, roptim
Suggests: testthat, mvtnorm, covr, knitr, MASS, rmarkdown, markdown
Published: 2022-08-29
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 isye.gatech.edu>
License: MIT + file LICENSE
URL: https://arxiv.org/abs/2203.06066
NeedsCompilation: yes
Materials: README
CRAN checks: magi results

Documentation:

Reference manual: magi.pdf
Vignettes: magi-vignette

Downloads:

Package source: magi_1.2.0.tar.gz
Windows binaries: r-devel: magi_1.2.0.zip, r-release: magi_1.2.0.zip, r-oldrel: magi_1.2.0.zip
macOS binaries: r-release (arm64): magi_1.2.0.tgz, r-oldrel (arm64): magi_1.2.0.tgz, r-release (x86_64): magi_1.2.0.tgz, r-oldrel (x86_64): magi_1.2.0.tgz
Old sources: magi archive

Linking:

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