The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Online Program Home
Abstract Details
|
Activity Number:
|
467
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Wednesday, August 1, 2012 : 8:30 AM to 10:20 AM
|
|
Sponsor:
|
Section on Statistics in Marketing
|
| Abstract - #305366 |
|
Title:
|
Copula-Based Dependence Structure Estimation for Monte Carlo Simulation in Marketing Research
|
|
Author(s):
|
Joseph Retzer*+ and Michael Conklin
|
|
Companies:
|
MarketTools Inc. and MarketTools Inc.
|
|
Address:
|
2019 E River Rd, Grafton, WI, 53024-9654, United States
|
|
Keywords:
|
copula ;
Monte Carlo ;
Shapley
|
|
Abstract:
|
Cumulative distribution functions of key driver attribute variables can be written in terms of marginal distribution functions and a copula. The marginals describe the distribution function of each driver while the copula describes the dependence structure between them. This paper will explore various market research applications of copula based density dependence structure approximation for purposes of prediction. Specifically, using this information, Monte Carlo simulation will be employed for predicting product adoption in both pharma and technology sectors. We will also explore the use of copulas in evaluating market potential and reach in CPG markets via Shapley Value model averaged reach measurement. The use of copulas will allow modeling and estimation of the distribution of drivers of product adoption and reach by separately estimating marginals and the associated copula.
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2012 program
|
2012 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.