Package: magi 1.2.4

Shihao Yang

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>.

Authors:Shihao Yang [aut, cre], Samuel W.K. Wong [aut], S.C. Kou [ctb, cph]

magi_1.2.4.tar.gz
magi_1.2.4.tar.gz(r-4.5-noble)magi_1.2.4.tar.gz(r-4.4-noble)
magi_1.2.4.tgz(r-4.4-emscripten)magi_1.2.4.tgz(r-4.3-emscripten)
magi.pdf |magi.html✨
magi/json (API)

# Install 'magi' in R:
install.packages('magi', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • FNdat - Dataset of noisy observations from the FitzHugh-Nagumo (FN) equations

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.67 score 47 scripts 252 downloads 23 exports 12 dependencies

Last updated 5 months agofrom:137fd1f7ba. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 22 2024
R-4.5-linux-x86_64OKNov 22 2024

Exports:calCovfnmodelDthetafnmodelDxfnmodelODEgpcovgpmeangpsmoothinggpsmoothllikhes1logmodelDthetahes1logmodelDxhes1logmodelODEhes1modelDthetahes1modelDxhes1modelODEis.magioutputmagioutputMagiPosteriorMagiSolverptransmodelDthetaptransmodelDxptransmodelODEsetDiscretizationtestDynamicalModel

Dependencies:BHclideSolvegluegridBasegridExtragtablelifecycleRcppRcppArmadillorlangroptim

magi-vignette

Rendered frommagi-vignette.Rmdusingknitr::rmarkdownon Nov 22 2024.

Last update: 2024-05-06
Started: 2021-07-27