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]

# Install 'dacc' in R:

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

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:

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

Target	Result	Time
linux-devel-x86_64	OK	171
source / vignettes	OK	159
linux-release-x86_64	OK	149
macos-release-arm64	OK	137
macos-oldrel-arm64	OK	229
windows-devel	OK	92
windows-release	OK	78
windows-oldrel	OK	90
wasm-release	OK	108

Help page	Topics
Regularized estimators for covariance matrix.	Covest
Optimal Fingerprinting via total least square regression.	fingerprint
Process netCDF4 Gridded Data into Format of the fingerprint() Function	fpPrep
Sample Dataset Used in Numerical Studies of "Detection and Attribution Analysis of Temperature Changes with Estimating Equations".	globalDat
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".	simDat