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Starting from a given object representing a fitted model (within a certain set of model classes) whose (non-)linear predictor includes some ordered factor(s) among the explanatory variables, a new model is constructed and fitted where each named factor is replaced by a single numeric score, suitably chosen so that the new variable produces a fit comparable with the standard methodology based on a set of polynomial contrasts. Two variants of the present approach have been developed, one in each of the next references: Azzalini (2023) <doi:10.1002/sta4.624>, (2024) <doi:10.48550/arXiv.2406.15933>.
Version: | 1.2.1 |
Depends: | R (≥ 4.0.0) |
Imports: | stats, methods |
Suggests: | ggplot2, survival |
Published: | 2024-10-30 |
DOI: | 10.32614/CRAN.package.smof |
Author: | Adelchi Azzalini [aut, cre] |
Maintainer: | Adelchi Azzalini <adelchi.azzalini at unipd.it> |
License: | GPL-2 | GPL-3 |
NeedsCompilation: | no |
Citation: | smof citation info |
Materials: | NEWS |
CRAN checks: | smof results |
Reference manual: | smof.pdf |
Package source: | smof_1.2.1.tar.gz |
Windows binaries: | r-devel: smof_1.2.1.zip, r-release: smof_1.2.1.zip, r-oldrel: smof_1.2.1.zip |
macOS binaries: | r-release (arm64): smof_1.2.1.tgz, r-oldrel (arm64): smof_1.2.1.tgz, r-release (x86_64): smof_1.2.1.tgz, r-oldrel (x86_64): smof_1.2.1.tgz |
Old sources: | smof 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.