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Estimates models that extend the standard GLM to take misclassification into account. The models require side information from a secondary data set on the misclassification process, i.e. some sort of misclassification probabilities conditional on some common covariates. A detailed description of the algorithm can be found in Dlugosz, Mammen and Wilke (2015) <https://www.zew.de/publikationen/generalised-partially-linear-regression-with-misclassified-data-and-an-application-to-labour-market-transitions>.
| Version: | 0.3.5 |
| Depends: | R (≥ 3.0.0) |
| Imports: | stats, Matrix, MASS, ucminf, numDeriv, foreach, mlogit |
| Suggests: | parallel |
| Published: | 2023-11-19 |
| DOI: | 10.32614/CRAN.package.misclassGLM |
| Author: | Stephan Dlugosz |
| Maintainer: | Stephan Dlugosz <stephan.dlugosz at googlemail.com> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | misclassGLM results |
| Reference manual: | misclassGLM.pdf |
| Package source: | misclassGLM_0.3.5.tar.gz |
| Windows binaries: | r-devel: misclassGLM_0.3.5.zip, r-release: misclassGLM_0.3.5.zip, r-oldrel: misclassGLM_0.3.5.zip |
| macOS binaries: | r-release (arm64): misclassGLM_0.3.5.tgz, r-oldrel (arm64): misclassGLM_0.3.5.tgz, r-release (x86_64): misclassGLM_0.3.5.tgz, r-oldrel (x86_64): misclassGLM_0.3.5.tgz |
| Old sources: | misclassGLM archive |
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