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Provides functions for isotonic regression and classification when there are multiple independent variables. The functions solve the optimization problem using a projective Bayes approach with recursive sequential update algorithms, and are useful for situations with a relatively large number of covariates. Supports binary outcomes via a Beta-Binomial conjugate model ('miso', 'PBclassifier') and continuous outcomes via a Normal-Inverse-Chi-Squared conjugate model ('misoN'). Parallel computing wrappers ('mcmiso', 'mcPBclassifier', 'mcmisoN') are provided that run the down-up and up-down algorithms simultaneously and return whichever finishes first. The estimation method follows the projective Bayes solution described in Cheung and Diaz (2023) <doi:10.1093/jrsssb/qkad014>.
| Version: | 0.2.0 |
| Depends: | R (≥ 4.0.0) |
| Imports: | stats, utils |
| Suggests: | future (≥ 1.33.0) |
| Published: | 2026-04-03 |
| DOI: | 10.32614/CRAN.package.McMiso |
| Author: | Cheung Ken [aut, cre] |
| Maintainer: | Cheung Ken <yc632 at cumc.columbia.edu> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | McMiso results |
| Reference manual: | McMiso.html , McMiso.pdf |
| Package source: | McMiso_0.2.0.tar.gz |
| Windows binaries: | r-devel: McMiso_0.2.0.zip, r-release: McMiso_0.1.2.zip, r-oldrel: McMiso_0.1.2.zip |
| macOS binaries: | r-release (arm64): McMiso_0.2.0.tgz, r-oldrel (arm64): McMiso_0.1.2.tgz, r-release (x86_64): McMiso_0.2.0.tgz, r-oldrel (x86_64): McMiso_0.2.0.tgz |
| Old sources: | McMiso archive |
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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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