Research Methods Track

How Many Iterations Do We Need: Guidelines for the Right Number of Burn-in and Used Draws in Hierarchical Bayes Estimation

About this presentation

Our Monte Carlo study explores the right number of burn-in and used draws. Experimental factors are the influence of number of choice tasks, number of parameters to be estimated and heterogeneity in the data and their influence on the draws settings. Criteria for Validation are convergence of the hierarchical Bayes model, capturing of long-term oscillations, and goodness of fit compared against the real simulated data. As a result, we present a guideline for everyday work.

Peter Kurz & Maximilian Rausch, bms Marketing Research + Strategy