Package: MNLR 0.1.0

MNLR: Interactive Shiny Presentation for Working with Multinomial Logistic Regression

An interactive presentation on the topic of Multinomial Logistic Regression. It is helpful to those who want to learn Multinomial Logistic Regression quickly and get a hands on experience. The presentation has a template for solving problems on Multinomial Logistic Regression. Runtime examples are provided in the package function as well as at <https://jarvisatharva.shinyapps.io/MultinomPresentation>.

Authors:Kartikeya Bolar

MNLR_0.1.0.tar.gz
MNLR_0.1.0.zip(r-4.5)MNLR_0.1.0.zip(r-4.4)MNLR_0.1.0.zip(r-4.3)
MNLR_0.1.0.tgz(r-4.5-any)MNLR_0.1.0.tgz(r-4.4-any)MNLR_0.1.0.tgz(r-4.3-any)
MNLR_0.1.0.tar.gz(r-4.5-noble)MNLR_0.1.0.tar.gz(r-4.4-noble)
MNLR_0.1.0.tgz(r-4.4-emscripten)MNLR_0.1.0.tgz(r-4.3-emscripten)
MNLR.pdf |MNLR.html✨
MNLR/json (API)

# Install 'MNLR' in R:
install.packages('MNLR', repos = c('https://kartikeyabolar.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

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

1.78 score 1 scripts 133 downloads 6 mentions 1 exports 103 dependencies

Last updated 6 years agofrom:10ceaecedc. Checks:1 OK, 7 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 27 2025
R-4.5-winNOTEJan 27 2025
R-4.5-macNOTEJan 27 2025
R-4.5-linuxNOTEJan 27 2025
R-4.4-winNOTEJan 27 2025
R-4.4-macNOTEJan 27 2025
R-4.3-winNOTEJan 27 2025
R-4.3-macNOTEJan 27 2025

Exports:MNLR

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