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%.
caMaxUtility(sym, y, x)
matrix of simulation profiles
matrix of preferences
matrix of profiles
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.
# NOT RUN {
#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)
# }
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