detergent

This data set gives the detergent brand choice by households and the
  price of each brand.

datasets

MNP is a publicly available R package that fits the
  Bayesian Multinomial Probit models via Markov chain Monte Carlo. Along
  with the standard Multinomial Probit model, it can also fit models
  with different choice sets for each observation and complete or
  partial ordering of all the available alternatives. The estimation
  is based on the efficient marginal data augmentation algorithm that
  is developed by Imai and van Dyk (2004).

Kosuke Imai

MNP: R Package for Fitting the Multinomial Probit Models

detergent function

A matrix containing 7 variables and 2657 observations

detergent: Detergent Brand Choice

Description

Usage

Arguments

format

References