optim.ms.fe.pw: Identifies the product profiles that maximazes market share,...

In jlopezsi/MDSConjoint: An implementation of metric and nonmetric conjoint models for marketing decisions

Description

Computes market share for actual product profiles as well as for all possible profiles in order to indentify the bundle that maximazes market share given actual profiles We use first choice rule If we combine all three functions into one function, we can use rule=1 for first choice, rule=2 for utility share, and the rest for logit. With a if sentence we hace combine all 3 functions into one.

Usage

optim.ms.fe.pw(mp, pw, design, hpb = 0)

Arguments

mp	a data frame with competitiors' profiles
pw	a data frame with all clients' part worths
design	a list with the experiment description (attributes and levels)
hpb	if hpb==1, then hide the progress bar. This is for rmarkdown

Value

optim.list a list with with the optim profile as well as optim market share

Examples

data(MDSConjointData)
names(MDSConjointData)
osc<-MDSConjointData$osc
names(osc)
osc.conjoint <- conjoint.estimation(osc$ratings, osc$bundles, osc$design)
names(osc.conjoint)
# [1] "summary"     "fit"         "part.worths"  "prediction"
#head(osc.conjoint$summary)
head(osc.conjoint$part.worths)
osc.ms.op.1choice<-optim.ms.fe.pw(osc$market.profiles, osc.conjoint$part.worths, osc$design, hpb=1)
osc.ms.op.1choice

jlopezsi/MDSConjoint documentation built on May 19, 2019, 12:48 p.m.