Package: smsncut
Type: Package
Title: Optimal Diagnostic Cutoff Selection under Scale Mixtures of
        Skew-Normal Distributions
Version: 0.1.0
Authors@R: c(
    person("Renato", "de Paula",
           email = "rrpaula@ciencias.ulisboa.pt",
           role = c("aut", "cre"),
           comment = c(ORCID = "0000-0002-5835-5918")),
    person("Helena", "Mouriño",
           role = "aut"),
    person("Tiago", "Dias Domingues",
           role = "aut"))
Description: Implements a parametric decision-theoretic framework for optimal
    diagnostic cutoff selection under the family of scale mixtures of skew-normal
    (SMSN) distributions, including the skew-normal (SN) and skew-t (ST) models
    as special cases. The optimal cutoff is defined by minimising a weighted
    misclassification risk that incorporates disease prevalence and asymmetric
    costs, leading to a likelihood-ratio equation that generalises the Youden
    criterion. Under a monotone likelihood ratio condition, existence, uniqueness,
    and global optimality of the cutoff are established. Asymptotic normality and
    a closed-form plug-in variance estimator are provided via the implicit function
    theorem and the multivariate delta method. Tools for model fitting, cutoff
    estimation, confidence intervals, the local identifiability diagnostic, and
    Monte Carlo simulation are included. The methodology is described in
    de Paula, Mouriño, and Dias Domingues (2026)
    <doi:10.48550/arXiv.2605.07829>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: sn (>= 2.0.0), numDeriv (>= 2016.8-1)
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-14 14:09:32 UTC; renato
Author: Renato de Paula [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-5835-5918>),
  Helena Mouriño [aut],
  Tiago Dias Domingues [aut]
Maintainer: Renato de Paula <rrpaula@ciencias.ulisboa.pt>
Config/roxygen2/version: 8.0.0
Repository: CRAN
Date/Publication: 2026-05-19 08:50:02 UTC
Built: R 4.5.3; ; 2026-05-19 23:51:26 UTC; windows
