Package: dacc 0.0-5

dacc: Detection and Attribution Analysis of Climate Change

Conduct detection and attribution of climate change using methods including optimal fingerprinting via generalized total least squares or estimating equation approach from Ma et al. (2023) <doi:10.1175/JCLI-D-22-0681.1>. Provide shrinkage estimators for covariance matrix from Ledoit and Wolf (2004) <doi:10.1016/S0047-259X(03)00096-4>, and Ledoit and Wolf (2017) <doi:10.2139/ssrn.2383361>.

Authors:Yan Li [aut, cre], Kun Chen [aut], Jun Yan [aut]

dacc_0.0-5.tar.gz
dacc_0.0-5.zip(r-4.5)dacc_0.0-5.zip(r-4.4)dacc_0.0-5.zip(r-4.3)
dacc_0.0-5.tgz(r-4.4-any)dacc_0.0-5.tgz(r-4.3-any)
dacc_0.0-5.tar.gz(r-4.5-noble)dacc_0.0-5.tar.gz(r-4.4-noble)
dacc_0.0-5.tgz(r-4.4-emscripten)dacc_0.0-5.tgz(r-4.3-emscripten)
dacc.pdf |dacc.html
dacc/json (API)

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

Peer review:

Bug tracker:https://github.com/liyanstat/dacc/issues

Datasets:
  • globalDat - Sample Dataset Used in Numerical Studies of "Detection and Attribution Analysis of Temperature Changes with Estimating Equations".
  • simDat - Sample Dataset in Simulation Studies of "Regularized Fingerprinting in Detection and Attribution of Climate Change with Weight Matrix Optimizing the Efficiency in Scaling Factor Estimation".

On CRAN:

3 exports 12 stars 2.06 score 33 dependencies 221 downloads

Last updated 23 days agofrom:cc4ac75fd7. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 25 2024
R-4.5-winOKAug 25 2024
R-4.5-linuxOKAug 25 2024
R-4.4-winOKAug 25 2024
R-4.4-macOKAug 25 2024
R-4.3-winOKAug 25 2024
R-4.3-macOKAug 25 2024

Exports:CovestfingerprintfpPrep

Dependencies:CFtimeclicpp11dplyrfansigenericsgluehmsIsojanitorlatticelifecyclelubridatemagrittrMASSncdf4pillarpkgconfigpracmapurrrR6rlangsnakecasespstringistringrtibbletidyrtidyselecttimechangeutf8vctrswithr