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We provide a list of functions for replicating the results of the Monte Carlo simulations and empirical application of Jiang et al. (2022). In particular, we provide corresponding functions for generating the three types of random data described in this paper, as well as all the estimation strategies. Detailed information about the data generation process and estimation strategy can be found in Jiang et al. (2022) <doi:10.48550/arXiv.2201.13004>.
Version: | 1.2.0 |
Depends: | R (≥ 2.10) |
Imports: | pracma, MASS, stringr, splus2R, glmnet, stats, purrr |
Suggests: | knitr, rmarkdown |
Published: | 2023-06-12 |
DOI: | 10.32614/CRAN.package.drcarlate |
Author: | Liang Jiang [aut, cph], Oliver B. Linton [aut, cph], Haihan Tang [aut, cph], Yichong Zhang [aut, cph], Mingxin Zhang [cre] |
Maintainer: | Mingxin Zhang <21110680035 at m.fudan.edu.cn> |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | drcarlate results |
Reference manual: | drcarlate.pdf |
Vignettes: |
Introduction to drcarlate |
Package source: | drcarlate_1.2.0.tar.gz |
Windows binaries: | r-devel: drcarlate_1.2.0.zip, r-release: drcarlate_1.2.0.zip, r-oldrel: drcarlate_1.2.0.zip |
macOS binaries: | r-release (arm64): drcarlate_1.2.0.tgz, r-oldrel (arm64): drcarlate_1.2.0.tgz, r-release (x86_64): drcarlate_1.2.0.tgz, r-oldrel (x86_64): drcarlate_1.2.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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