Package: GsymPoint 1.1.2

Mónica López-Ratón

GsymPoint: Estimation of the Generalized Symmetry Point, an Optimal Cutpoint in Continuous Diagnostic Tests

Estimation of the cutpoint defined by the Generalized Symmetry point in a binary classification setting based on a continuous diagnostic test or marker. Two methods have been implemented to construct confidence intervals for this optimal cutpoint, one based on the Generalized Pivotal Quantity and the other based on Empirical Likelihood. Numerical and graphical outputs for these two methods are easily obtained.

Authors:Mónica López-Ratón [aut, cre], Carmen Cadarso-Suárez [aut], Elisa M. Molanes-López [aut], Emilio Letón [aut]

GsymPoint_1.1.2.tar.gz
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GsymPoint.pdf |GsymPoint.html✨
GsymPoint/json (API)
NEWS

# Install 'GsymPoint' in R:
install.packages('GsymPoint', repos = 'https://cloud.r-project.org')
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 216 downloads 5 exports 8 dependencies

Last updated 1 years agofrom:158c572b69. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 24 2025
R-4.5-linuxOKMar 24 2025
R-4.4-linuxOKMar 24 2025

Exports:control.gsym.pointgsym.pointplot.gsym.pointprint.gsym.pointsummary.gsym.point

Dependencies:bitopscaToolsgplotsgtoolsKernSmoothROCRRsolnptruncnorm

Citation

To cite GsymPoint in publications use:

López-Ratón M., Molanes-López E.M., Letón E. and Cadarso Suárez C. (2017). GsymPoint: An R Package to Estimate the Generalized Symmetry Point, an Optimal Cut-off Point for Binary Classification in Continuous Diagnostic Tests. The R Journal 9(1):262-283.

Corresponding BibTeX entry: 

  @Article{,
    title = {{GsymPoint}: An {R} Package to Estimate the Generalized
      Symmetry Point, an Optimal Cut-off Point for Binary
      Classification in Continuous Diagnostic Tests},
    author = {L{\'o}pez-Rat{\'o}n M. and Molanes-L{\'o}pez E.M. and
      Let{\'o}n E. and Cadarso Su{\'a}rez C.},
    journal = {The R Journal},
    year = {2017},
    volume = {9},
    number = {1},
    pages = {262-283},
    url = {https://doi.org/10.32614/RJ-2017-015},
  }