caMaxUtility: Function caMaxUtility estimates participation (market share)...

In conjoint: An Implementation of Conjoint Analysis Method

Description

Function caMaxUtility estimates participation of simulation profiles using model of maximum utility ("first position"). Function returns vector of percentage participations. The sum of participation should be 100%.

Usage

caMaxUtility(sym, y, x)

Arguments

sym	matrix of simulation profiles
y	matrix of preferences
x	matrix of profiles

Author(s)

Andrzej Bak [e-mail],

Tomasz Bartlomowicz [e-mail]

Department of Econometrics and Computer Science, Wroclaw University of Economics, Poland http://keii.ue.wroc.pl/conjoint

References

Bak A., Bartlomowicz T. (2012), Conjoint analysis method and its implementation in conjoint R package, [In:] Pociecha J., Decker R. (Eds.), Data analysis methods and its applications, C.H.Beck, Warszawa, p.239-248.

Bak A. (2009), Analiza Conjoint [Conjoint Analysis], [In:] Walesiak M., Gatnar E. (Eds.), Statystyczna analiza danych z wykorzystaniem programu R [Statistical Data Analysis using R], Wydawnictwo Naukowe PWN, Warszawa, p. 283-317.

Green P.E., Srinivasan V. (1978), Conjoint Analysis in Consumer Research: Issues and Outlook, "Journal of Consumer Research", September, 5, p. 103-123.

SPSS 6.1 Categories (1994), SPSS Inc., Chicago.

See Also

caBTL, caLogit and ShowAllSimulations

Examples

#Example 1
library(conjoint)
data(tea)
simutil<-caMaxUtility(tsimp,tpref,tprof)
print("Percentage participation of profiles: ", quote=FALSE)
print(simutil)

#Example 2
library(conjoint)
data(chocolate)
simutil<-caMaxUtility(csimp,cpref,cprof)
print("Percentage participation of profiles:", quote=FALSE)
print(simutil)

#Example 3
library(conjoint)
data(chocolate)
ShowAllSimulations(csimp,cpref,cprof)

#Example 4
#library(conjoint)
#data(journey)
#ShowAllSimulations(jsimp,jpref,jprof)

conjoint documentation built on May 1, 2019, 8:05 p.m.