detergent

<p>This dataset gives the laundry detergent brand choice by households and the
price of each brand.</p>

datasets

Fits the Bayesian multinomial probit model via Markov chain
Monte Carlo.  The multinomial probit model is often used to analyze
the discrete choices made by individuals recorded in survey data.
Examples where the multinomial probit model may be useful include the
analysis of product choice by consumers in market research and the
analysis of candidate or party choice by voters in electoral studies.
The MNP package can also fit the model with different choice sets for
each individual, and complete or partial individual choice orderings
of the available alternatives from the choice set. The estimation is
based on the efficient marginal data augmentation algorithm that is
developed by Imai and van Dyk (2005). "A Bayesian Analysis of the
Multinomial Probit Model Using the Data Augmentation." Journal of
Econometrics, Vol. 124, No. 2 (February), pp. 311-334.
<doi:10.1016/j.jeconom.2004.02.002>  Detailed examples are given in
Imai and van Dyk (2005). "MNP: R Package for Fitting the Multinomial
Probit Model."  Journal of Statistical Software, Vol. 14, No. 3 (May),
pp. 1-32. <doi:10.18637/jss.v014.i03>.

Kosuke Imai

Fitting the Multinomial Probit Model

David van Dyk

Hubert Jin

detergent function

<p>A data frame containing the following 7 variables and 2657
observations.</p>
<table class="table">
<tr><td>choice</td><td>factor</td><td>a brand chosen by each household</td></tr>
<tr><td>TidePrice</td><td>numeric</td><td>log price of Tide</td></tr>
<tr><td>WiskPrice</td><td>numeric</td><td>log price of Wisk</td></tr>
<tr><td>EraPlusPrice</td><td>numeric</td><td>log price of EraPlus</td></tr>
<tr><td>SurfPrice</td><td>numeric</td><td>log price of Surf</td></tr>
<tr><td>SoloPrice</td><td>numeric</td><td>log price of Solo</td></tr>
<tr><td>AllPrice</td><td>numeric</td><td>log price of All</td></tr>
</table><p></p><p></p>

Format

Detergent Brand Choice — detergent

<p>A data frame containing the following 7 variables and 2657
observations.</p>
<table class='table'>
<tr><td>choice</td><td>factor</td><td>a brand chosen by each household</td></tr>
<tr><td>TidePrice</td><td>numeric</td><td>log price of Tide</td></tr>
<tr><td>WiskPrice</td><td>numeric</td><td>log price of Wisk</td></tr>
<tr><td>EraPlusPrice</td><td>numeric</td><td>log price of EraPlus</td></tr>
<tr><td>SurfPrice</td><td>numeric</td><td>log price of Surf</td></tr>
<tr><td>SoloPrice</td><td>numeric</td><td>log price of Solo</td></tr>
<tr><td>AllPrice</td><td>numeric</td><td>log price of All</td></tr>
</table>



detergent: Detergent Brand Choice

Description

Arguments

Format

References

choice	factor	a brand chosen by each household
TidePrice	numeric	log price of Tide
WiskPrice	numeric	log price of Wisk
EraPlusPrice	numeric	log price of EraPlus
SurfPrice	numeric	log price of Surf
SoloPrice	numeric	log price of Solo
AllPrice	numeric	log price of All