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Fits the Expectile Regression for Fixed Effect (ERFE) estimator. The ERFE model extends the within-transformation strategy to solve the incidental parameter problem within the expectile regression framework. The ERFE model estimates the regressor effects on the expectiles of the response distribution. The ERFE estimate corresponds to the classical fixed-effect within-estimator when the asymmetric point is 0.5. The paper by Barry, Oualkacha, and Charpentier (2021, <doi:10.48550/arXiv.2108.04737>) gives more details about the ERFE model.
Version: | 0.0.1 |
Depends: | R (≥ 2.10) |
Imports: | Matrix, mvtnorm, stats |
Suggests: | covr, testthat (≥ 3.0.0) |
Published: | 2022-12-16 |
DOI: | 10.32614/CRAN.package.erfe |
Author: | Amadou Barry [cre, aut] |
Maintainer: | Amadou Barry <barryhafia at gmail.com> |
BugReports: | https://github.com/amadoudiogobarry/erfe/issues |
License: | GPL-3 |
URL: | https://arxiv.org/abs/2108.04737 |
NeedsCompilation: | no |
Language: | en-US |
Materials: | README NEWS |
CRAN checks: | erfe results [issues need fixing before 2024-11-28] |
Reference manual: | erfe.pdf |
Package source: | erfe_0.0.1.tar.gz |
Windows binaries: | r-devel: erfe_0.0.1.zip, r-release: erfe_0.0.1.zip, r-oldrel: erfe_0.0.1.zip |
macOS binaries: | r-release (arm64): erfe_0.0.1.tgz, r-oldrel (arm64): erfe_0.0.1.tgz, r-release (x86_64): erfe_0.0.1.tgz, r-oldrel (x86_64): erfe_0.0.1.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.