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Fits generalized linear models (GLMs) when there is missing data in both the response and categorical covariates. The functions implement likelihood-based methods using the Expectation and Maximization (EM) algorithm and optionally apply Firth’s bias correction for improved inference. See Pradhan, Nychka, and Bandyopadhyay (2025) <https:>, Maiti and Pradhan (2009) <doi:10.1111/j.1541-0420.2008.01186.x>, Maity, Pradhan, and Das (2019) <doi:10.1080/00031305.2017.1407359> for further methodological details.
| Version: | 2.1.0 |
| Depends: | R (≥ 4.0.0) |
| Imports: | data.table (≥ 1.12.8), dplyr (≥ 1.0.0), abind (≥ 1.4-5), MASS (≥ 7.3-53), brglm2 (≥ 0.7.1) |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2025-04-22 |
| DOI: | 10.32614/CRAN.package.glmfitmiss |
| Author: | Vivek Pradhan [aut, cre], Douglas Nychka [aut], Soutir Bandyopadhyay [aut] |
| Maintainer: | Vivek Pradhan <vpradhan2009 at gmail.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| CRAN checks: | glmfitmiss results |
| Reference manual: | glmfitmiss.pdf |
| Package source: | glmfitmiss_2.1.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: glmfitmiss_2.1.0.zip, r-oldrel: glmfitmiss_2.1.0.zip |
| macOS binaries: | r-release (arm64): glmfitmiss_2.1.0.tgz, r-oldrel (arm64): glmfitmiss_2.1.0.tgz, r-release (x86_64): glmfitmiss_2.1.0.tgz, r-oldrel (x86_64): glmfitmiss_2.1.0.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.