An Efficient Algorithm for Constructing Bayesian Optimal Choice Designs
Journal of Business and Economic Statistics , Volume 27 - Issue 2 p. 279- 291
While Bayesian - and -optimal designs for the multinomial logit model have been shown to have better predictive performance than Bayesian - and -optimal designs, the algorithms for generating them have been too slow for commercial use. In this article, we present a much faster algorithm for generating Bayesian optimal designs for all four criteria while simultaneously improving the statistical efficiency of the designs. We also show how to augment a choice design allowing for correlated parameter estimates using a sports club membership study.
|Bayesian optimality, optimal choice design|
|ERIM Top-Core Articles|
|Journal of Business and Economic Statistics|
|Organisation||Erasmus Research Institute of Management|
Kessels, R, Jones, B, Goos, P.P, & Vandebroek, M. (2009). An Efficient Algorithm for Constructing Bayesian Optimal Choice Designs. Journal of Business and Economic Statistics, 27(2), 279–291. Retrieved from http://hdl.handle.net/1765/19557