Conformal Local Influence Screening for Bounded-Response Regression R package clis version 0.3.6 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. Software 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 Raydonal Ospina <raydonal@de.ufpe.br> Comprehensive R Archive Network (CRAN) Raydonal Ospina [aut, cre] (ORCID: <https://orcid.org/0000-0002-9884-9090>) GPL-3 2026-09-29 application/tgz https://CRAN.R-project.org/package=clis doi:10.32614/CRAN.package.clis