caModel {conjoint}

Function caModel estimates parameters of conjoint analysis model

Description

Function caModel estimates parameters of conjoint analysis model for one respondent. Function caModel returns vector of estimated parameters of traditional conjoint analysis model.

Usage

caModel(y, x)

Arguments

y

vector of preferences, vector should be like single profil 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

Conjoint

Examples

#Example 1
library(conjoint)
data(tea)
model=caModel(tprefm[1,], tprof)
print(model)

#Example 2
library(conjoint)
data(chocolate)
model=caModel(cprefm[1,], cprof)
print(model)

#Example 3
library(conjoint)
data(journey)
model=caModel(jpref[306,], jprof)
print(model)