dacc: Detection and Attribution Analysis of Climate Change
Detection and attribution analysis of climate change using errors-in-variables
regression. Implements the polynomial shrinkage framework under variance
heterogeneity proposed by Li and Li (2026)
<doi:10.48550/arXiv.2608.12496> and the latent factor framework proposed
by Li and Li (2026) <doi:10.48550/arXiv.2609.13488>. Estimates forcing
scaling factors and variance inflation coefficients for
forced simulations and control runs relative to observations. Selects
polynomial covariance weights or bias-corrected spiked precision weights by
minimizing estimated total asymptotic scaling factor variance, and provides
asymptotic confidence intervals and residual diagnostics. Also retains
earlier total least squares and estimating equation procedures
(Li et al., 2025, <doi:10.1175/JCLI-D-24-0193.1>;
Ma et al., 2023, <doi:10.1175/JCLI-D-22-0681.1>) for comparison and
reproducibility, together with covariance shrinkage estimators.
| Version: |
0.1.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
MASS, stats, graphics, utils, Iso, pracma, janitor, magrittr, sp, CFtime, ncdf4 |
| Suggests: |
RMTstat |
| Published: |
2026-11-09 |
| DOI: |
10.32614/CRAN.package.dacc |
| Author: |
Haoran Li [aut],
Yan Li [aut, cre],
Kun Chen [aut],
Jun Yan [aut] |
| Maintainer: |
Yan Li <yan.4.li at uconn.edu> |
| BugReports: |
https://github.com/LiYanStat/dacc/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/LiYanStat/dacc |
| NeedsCompilation: |
no |
| CRAN checks: |
dacc results |
Documentation:
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