Package: smof 1.2.2
Adelchi Azzalini
smof: Scoring Methodology for Ordered Factors
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>.
Authors:
smof_1.2.2.tar.gz
smof_1.2.2.tar.gz(r-4.5-noble)smof_1.2.2.tar.gz(r-4.4-noble)
smof_1.2.2.tgz(r-4.4-emscripten)smof_1.2.2.tgz(r-4.3-emscripten)
smof.pdf |smof.html✨
smof/json (API)
NEWS
| # Install 'smof' in R: |
| install.packages('smof', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 15 days agofrom:6f96d8d750. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 10 2024 |
| R-4.5-linux | OK | Dec 10 2024 |
Exports:anova.smofplot.smofpredict.smofprint.smofprint.summary.smofsmofsmof_refitsummary.smof
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Scoring Methodology for Ordered Factors | smof-package |
| Scoring Methodology for Ordered Factors | smof |
| Re-fitting an existing 'smof' model for improved optimization | smof_refit |
| Methods for 'smof' objects | anova.smof coef.smof plot.smof predict.smof print.smof print.summary.smof summary.smof |