clis: Conformal Local Influence Screening for Bounded-Response
Regression
Provides fast, statistically calibrated influence diagnostics
for zero-or-one inflated beta (BIc) regression models with variable
dispersion. The core idea is to use the conformal normal curvature of
Poon and Poon (1999) <doi:10.1111/1467-9868.00162> as a non-conformity
score within a split-conformal testing procedure, yielding per-observation
conformal p-values whose Benjamini-Hochberg adjustment controls the false
discovery rate at a user-specified level (Bates and others, 2023)
<doi:10.1214/22-AOS2244>. Unlike classical local influence diagnostics,
which rely on visual inspection of index plots and do not scale beyond a
few hundred observations, 'clis' provides a finite-sample error guarantee
and runs in linear time per observation after a single model fit. Methods
for four perturbation schemes, block decomposition of influence into the
inflation-probability and conditional-mean/precision components, penalised
additive (semiparametric) submodels, and a full suite of diagnostic plots
are included.
| Version: |
0.3.6 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
gamlss (≥ 5.4.0), gamlss.dist (≥ 6.0.0), stats, graphics, grDevices, utils |
| Suggests: |
testthat (≥ 3.0.0), knitr, rmarkdown, ggplot2, betareg, gamlss.data |
| Published: |
2026-09-29 |
| DOI: |
10.32614/CRAN.package.clis |
| Author: |
Raydonal Ospina 
[aut, cre] |
| Maintainer: |
Raydonal Ospina <raydonal at de.ufpe.br> |
| BugReports: |
https://github.com/Raydonal/clis/issues |
| License: |
GPL-3 |
| URL: |
https://github.com/Raydonal/clis, https://raydonal.github.io/clis/ |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
clis results |
Documentation:
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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.