Paired Comparison Data Analysis

Description

Different tools for describing and analysing paired comparison data are presented. Main methods are estimation of products scores according Bradley Terry Luce model. A segmentation of the individual could be conducted on the basis of a mixture distribution approach. The number of classes can be tested by the use of Monte Carlo simulations. This package deals also with multi-criteria paired comparison data.

Details

Package: CompR
Type: Package
Version: 1.0
Date: 2015-07-01
License: GPL-2
Depends: methods, MASS, stats, graphics, utils

Function to estimate products configurations (Bradley's scores) and weights of the
classes is EstimBradley().

Function to perform a test concerning the number of classes is ResSimulLvrRatio().

Function to obtain a graphical representation of Bradley's scores is Piplot().

Author(s)

Michel Semenou

Maintainer: <michel.semenou@oniris-nantes.fr>

See Also

EstimBradley, ResSimulLvrRatio, Piplot

Examples

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data(Cocktail)
show(Cocktail)
ResCock1<-EstimBradley(Cocktail,Constraint=0,Tcla=1,eps=0.001,eps1=0.001,TestPi=TRUE)
show(ResCock1)
Res_LvrRatio1<-ResSimulLvrRatio(Cocktail,ResCock1,0,3,level=0.05,eps=0.001,eps1=0.001)
getSimu(Res_LvrRatio1)
getTest(Res_LvrRatio1)

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