NominalLogisticBiplot: Biplot representations of categorical data

Analysis of a matrix of polytomous items using Nominal Logistic Biplots (NLB) according to Hernandez-Sanchez and Vicente-Villardon (2013). The NLB procedure extends the binary logistic biplot to nominal (polytomous) data. The individuals are represented as points on a plane and the variables are represented as convex prediction regions rather than vectors as in a classical or binary biplot. Using the methods from Computational Geometry, the set of prediction regions is converted to a set of points in such a way that the prediction for each individual is established by its closest "category point". Then interpretation is based on distances rather than on projections. In this package we implement the geometry of such a representation and construct computational algorithms for the estimation of parameters and the calculation of prediction regions.

Install the latest version of this package by entering the following in R:
install.packages("NominalLogisticBiplot")
AuthorJulio Cesar Hernandez Sanchez, Jose Luis Vicente-Villardon
Date of publication2014-05-02 07:13:20
MaintainerJulio Cesar Hernandez Sanchez <juliocesar_avila@usal.es>
LicenseGPL (>= 2)
Version0.2

View on CRAN

Functions

afc Man page
Env Man page
Generators Man page
HairColor Man page
hermquad Man page
multiquad Man page
Nominal2Binary Man page
NominalDistances Man page
NominalLogBiplotEM Man page
NominalLogisticBiplot Man page
NominalLogisticBiplot-package Man page
NominalMatrix2Binary Man page
PCoA Man page
PhD_nomCyL Man page
plotNominalFittedVariable Man page
plot.nominal.logistic.biplot Man page
plotNominalVariable Man page
polylogist Man page
RidgeMultinomialRegression Man page
summary.nominal.logistic.biplot Man page

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