A comparison of generalized multinomial logit (GMNL) and latent class approaches to studying consumer heterogeneity with some extensions of the GMNL model by Peter J. Lenk
dc.contributor.author | Lenk, Peter J. | en_US |
dc.date.accessioned | 2012-01-05T22:05:07Z | |
dc.date.available | 2013-01-02T16:31:50Z | en_US |
dc.date.issued | 2011-11 | en_US |
dc.identifier.citation | Lenk, Peter (2011). "A comparison of generalized multinomial logit (GMNL) and latent class approaches to studying consumer heterogeneity with some extensions of the GMNL model by Peter J. Lenk." Applied Stochastic Models in Business and Industry 27(6): 580-583. <http://hdl.handle.net/2027.42/89466> | en_US |
dc.identifier.issn | 1524-1904 | en_US |
dc.identifier.issn | 1526-4025 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/89466 | |
dc.publisher | John Wiley & Sons, Ltd | en_US |
dc.title | A comparison of generalized multinomial logit (GMNL) and latent class approaches to studying consumer heterogeneity with some extensions of the GMNL model by Peter J. Lenk | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Mathematics | en_US |
dc.subject.hlbsecondlevel | Statistics and Numeric Data | en_US |
dc.subject.hlbtoplevel | Science | en_US |
dc.subject.hlbtoplevel | Social Sciences | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/89466/1/asmb941.pdf | |
dc.identifier.doi | 10.1002/asmb.941 | en_US |
dc.identifier.source | Applied Stochastic Models in Business and Industry | en_US |
dc.identifier.citedreference | Fiebig DG, Kean MP, Louviere JJ, Wasi N. The Generalized Multinomial Logit Model: Accounting for Scale and Coefficient Heterogeneity. Marketing Science 2010 29: 393 – 421. | en_US |
dc.identifier.citedreference | Kamakura WA, Russell GJ. A Probabilistic Choice Model for Market Segmentation and Elasticity Structure. Journal of Marketing Research 1989 26 ( 4 ): 389 – 390. | en_US |
dc.identifier.citedreference | Aitchison J, Bennet J A. Polychotomous quantal response by maximum indicant. Biometrika 1970 57: 253 – 262. | en_US |
dc.identifier.citedreference | McFadden D. Conditional logit analysis of quantitative choice behavior, In Frontiers in Econometrics, Vol. 105–142, Zarembka P (ed), Academic Press, New York, 1974. | en_US |
dc.identifier.citedreference | Lenk P, DeSarbo W, Green P, Young M. Hierarchical Bayes Conjoint Analysis: Recovery of Partworth Heterogeneity from Reduced Experimental Designs. Marketing Science 1996 15 ( 2 ): 173 – 191. | en_US |
dc.identifier.citedreference | Berger JO, Roberts C. Subjective Hierarchical Bayes Estimation of a Multivariate Normal Mean: on the Frequentist Interface. The Annals of Statistics 1990 18 ( 2 ): 617 – 651. | en_US |
dc.identifier.citedreference | Lenk P, DeSarbo W. Bayesian Inference for Finite Mixtures of Generalized Linear Models with Random Effects. Psychometrika 2000 65 ( 1 ): 93 – 119. | en_US |
dc.identifier.citedreference | Glibride T, Lenk P. Posterior Predictive Model Checking: An Application to Multivariate Normal Heterogeneity. Journal of Marketing Research 2010 47 ( 5 ): 896 – 909. | en_US |
dc.identifier.citedreference | Allenby G, Lenk P. Modeling Household Purchase Behavior with Logistic Normal Regression. Journal of the American Statistical Association 1994 83 ( 428 ): 1218 – 1231. | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.