sure: Surrogate Residuals for Ordinal and General Regression Models
An implementation of the surrogate approach to residuals and
diagnostics for ordinal and general regression models; for details, see Liu
and Zhang (2018) <doi:10.1080/01621459.2017.1292915> and Greenwell et al.
(2018) <doi:10.32614/RJ-2018-004>. These residuals can be used to construct
standard residual plots for model diagnostics (e.g., residual-vs-fitted
value plots, residual-vs-covariate plots, Q-Q plots, etc.). The package also
provides 'plot' methods for producing standard diagnostic plots using
lightweight base R graphics (via 'tinyplot'). The package currently
supports cumulative link models from packages 'MASS', 'ordinal', 'rms', and
'VGAM', binary and other generalized linear models fit with 'glm', and
multinomial models or general classifiers via a matrix of predicted class
probabilities.
| Version: |
0.3.1 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
stats |
| Suggests: |
goftest, knitr, MASS, ordinal, PResiduals, rmarkdown, rms, tinyplot, tinytest, VGAM |
| Published: |
2026-10-24 |
| DOI: |
10.32614/CRAN.package.sure |
| Author: |
Brandon Greenwell [aut, cre],
Andrew McCarthy [aut],
Bradley Boehmke [aut],
Liz Glaser [ctb] |
| Maintainer: |
Brandon Greenwell <greenwell.brandon at gmail.com> |
| BugReports: |
https://github.com/bgreenwell/sure/issues |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
https://github.com/bgreenwell/sure,
https://bgreenwell.github.io/sure/,
https://bgreenwell.r-universe.dev/sure |
| NeedsCompilation: |
no |
| Citation: |
sure citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
sure results |
Documentation:
Downloads:
Reverse dependencies:
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