ms.fe.pw: This function computes the market share of product profiles...

Description Usage Arguments Value Examples

View source: R/ms.prediction.pw.R

Description

This function computes the market share of market product profiles according to the first choice rule. Uses a data frame with part woths to predict utilities market profiles, mp, is a matrix of market product profiles (rows) by attributes (columns); pw is a data frame of clients (rows) by attribut levels part worths (colums); design.l is a list with the definition of the conjoint design

Usage

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ms.fe.pw(mp, pw, design.l)

Arguments

mp

a data frame with the description of competitors' existing product profiles

pw

a data frame frame with all clients' part worths

design.l

a list with conjoint design

Value

ms

Examples

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data(MDSConjointData)
names(MDSConjointData)
osc<-MDSConjointData$osc
names(osc)
sapply(osc, class)
sapply(osc$market.proiles, class)
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$fit)
head(osc.conjoint$part.worths)
head(osc.conjoint$prediction)
ms.fe.pw(osc$market.profiles, osc.conjoint$part.worths, osc$design)
class(ms.fe.pw(osc$market.profiles, osc$ratings, osc$bundles))

jlopezsi/MDSConjoint documentation built on May 17, 2017, 11:25 p.m.