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1. Introduction
2. Panel structure data
3. Heterogeneity and priors (1)
4. Heterogeneity and priors (2)
5. Marginalizing the likelihood
6. Principle number 1
7. Hierarchical Linear Model
8. Priors
9. GS for the Hierarchical Linear Model
10. Adaptive shrinkage
11. An example - key account data (1)
12. An example - key account data (2)
13. Shrinkage
14. Principle number 2
15. Heterogeneous logit model
16. Heterogeneous logit model - priors
17. Drawing beta-h
18. Random effects with regressors
19. Heterogeneous logit - rhierBinLogit
20. Heterogeneous logit - log likelihood
21. Heterogeneous logit - storage for draws
22. Heterogeneous logit - time
23. Heterogeneous logit - generating draws of beta
24. Heterogeneous logit - rmultiregfp
25. Heterogeneous logit - keeping the draws
26. Running rhierBinLogit (1)
27. Running rhierBinLogit (2)
28. Principle number 3
29. The bank study - data (1)
30. The bank study - data (2)
31. Sample observations
32. Sample demographics
33. Trace plot - average respondent part-worths
34. V beta draws
35. Posterior log likelihood
36. Rejection rate of Metropolis-Hastings algorithm
37. Distribution of heterogeneity for some part-worths
38. Part-worth distribution (respondent 250)
39. Extensions
40. Summary

Topics Covered

• Panel structure data
• Heterogeneity and priors
• Hierarchical linear model
• Priors
• Adaptive shrinkage
• Heterogeneous logit model
• Random effects with regressors
• Heterogeneous logit
• Running rhierBinLogit
• Data(bank)
• Sample observations
• Distribution of heterogeneity for selected part-worths
• Extensions

Links

Series:

• Bayesian Analysis in Marketing

Categories:

• Marketing & Sales

Talk Citation

Publication History

• Published on January 27, 2010