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.pdf
Vignettes: AIUQ tutorial

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:

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