Preliminary estimators for a mixture model of ordinal data
In this paper, we propose preliminary estimators for the parameters of a mixture distribution introduced for the analysis of ordinal data where the mixture components are given by a Combination of a discrete Uniform and a shifted Binomial distribution ( cub model). After reviewing some preliminary concepts related to the meaning of parameters which characterize such models, we introduce estimators which are related to the location and heterogeneity of the observed distributions, respectively, in order to accelerate the EM procedure for the maximum likelihood estimation. A simulation experiment has been performed to investigate their main features and to confirm their usefulness. A check of the proposal on real case studies and some comments conclude the paper. Copyright Springer-Verlag 2012
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 6 (2012)
Issue (Month): 3 (October)
|Contact details of provider:|| Web page: http://www.springer.com|
Web page: http://www.gfkl.org/en/
Web page: http://www.bunrui.jp/en/
Web page: http://dssm.unipa.it/cladag
Web page: http://www.classification-society.org/
|Order Information:||Web: http://www.springer.com/statistics/statistical+theory+and+methods/journal/11634/PS2|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Bettina Grün & Friedrich Leisch, 2008. "Identifiability of Finite Mixtures of Multinomial Logit Models with Varying and Fixed Effects," Journal of Classification, Springer;The Classification Society, vol. 25(2), pages 225-247, November.
- Richard Breen & Ruud Luijkx, 2010. "Mixture Models for Ordinal Data," Sociological Methods & Research, SAGE Publishing, vol. 39(1), pages 3-24, August.
- Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
- Karlis, Dimitris & Xekalaki, Evdokia, 2003. "Choosing initial values for the EM algorithm for finite mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 577-590, January.
- Nettleton, Dan, 2009. "Testing for the Supremacy of a Multinomial Cell Probability," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 1052-1059.
- D'Elia, Angela & Piccolo, Domenico, 2005. "A mixture model for preferences data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 49(3), pages 917-934, June.
- Michel Wedel & Wayne DeSarbo, 1995. "A mixture likelihood approach for generalized linear models," Journal of Classification, Springer;The Classification Society, vol. 12(1), pages 21-55, March.
- Biernacki, Christophe & Celeux, Gilles & Govaert, Gerard, 2003. "Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 561-575, January.
When requesting a correction, please mention this item's handle: RePEc:spr:advdac:v:6:y:2012:i:3:p:163-184. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla)or (Rebekah McClure)
If references are entirely missing, you can add them using this form.