Package: dacc 0.0-8

dacc: Detection and Attribution Analysis of Climate Change

Detection and attribution of climate change using methods including optimal fingerprinting via generalized total least squares or an estimating equation approach (Li et al., 2025, <doi:10.1175/JCLI-D-24-0193.1>; Ma et al., 2023, <doi:10.1175/JCLI-D-22-0681.1>). Provides shrinkage estimators for the covariance matrix following 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_0.0-8.tar.gz
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dacc_0.0-8.tgz(r-4.6-any)dacc_0.0-8.tgz(r-4.5-any)
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dacc_0.0-8.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
dacc/json (API)

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

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:

Conda:

4.30 score 20 stars 412 downloads 3 exports 32 dependencies

Last updated from:fe34fe725b. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK140
source / vignettesOK161
linux-releaseOK150
macos-releaseOK187
macos-oldrelOK172
windows-develOK87
windows-releaseOK93
windows-oldrelOK75
wasm-releaseOK103

Exports:CovestfingerprintfpPrep

Dependencies:CFtimeclicpp11dplyrgenericsgluehmsIsojanitorlatticelifecyclelubridatemagrittrMASSncdf4pillarpkgconfigpracmapurrrR6rlangsnakecasespstringistringrtibbletidyrtidyselecttimechangeutf8vctrswithr