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AIUQ: Ab Initio Uncertainty Quantification

Uncertainty quantification and inverse estimation by probabilistic generative models from the beginning of the data analysis. An example is a Fourier basis method for inverse estimation in scattering analysis of microscopy videos. It does not require specifying a certain range of Fourier bases and it substantially reduces computational cost via the generalized Schur algorithm. See the reference: Mengyang Gu, Yue He, Xubo Liu and Yimin Luo (2023), <doi:10.48550/arXiv.2309.02468>.

Version:0.5.3
Imports:fftwtools (≥ 0.9.11),SuperGauss (≥ 2.0.3), methods,plot3D (≥ 1.4)
Suggests:knitr,rmarkdown
Published:2024-07-02
DOI:10.32614/CRAN.package.AIUQ
Author:Yue He [aut], Xubo Liu [aut], Mengyang Gu [aut, cre]
Maintainer:Mengyang Gu <mengyang at pstat.ucsb.edu>
License:GPL (≥ 3)
NeedsCompilation:no
Materials:ChangeLog
CRAN checks:AIUQ results

Documentation:

Reference manual:AIUQ.html ,AIUQ.pdf
Vignettes:AIUQ tutorial (source,R code)

Downloads:

Package source: AIUQ_0.5.3.tar.gz
Windows binaries: r-devel:AIUQ_0.5.3.zip, r-release:AIUQ_0.5.3.zip, r-oldrel:AIUQ_0.5.3.zip
macOS binaries: r-release (arm64):AIUQ_0.5.3.tgz, r-oldrel (arm64):AIUQ_0.5.3.tgz, r-release (x86_64):AIUQ_0.5.3.tgz, r-oldrel (x86_64):AIUQ_0.5.3.tgz
Old sources: AIUQ archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=AIUQto link to this page.


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