Estimating component cumulative distribution functions in finite mixture models

Communications in Statistics - Theory and Methods

Volumn 33, Issue 9 SPEC.ISS., 2004, Pages 2075-2086

  Elmore, Ryan T ^a,c   Hettmansperger, Thomas P ^a,b   Thomas, Hoben ^b  

^a Department of Statistics ^*  (United States)

^b PENNSYLVANIA STATE UNIVERSITY   (United States)

^c AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

Author keywords

Cut point model; Empirical distribution function; Moment estimation; Multinomial mixture

Indexed keywords

CUT POINT MODELS; EMPIRICAL DISTRIBUTION FUNCTIONS; MOMENT ESTIMATION; MULTIMODAL MIXTURE;

APPROXIMATION THEORY; FUNCTIONS; MATHEMATICAL MODELS; PARAMETER ESTIMATION; RANDOM PROCESSES; VECTORS;

PROBABILITY DISTRIBUTIONS;

EID: 7544246661     PISSN: 03610926     EISSN: None     Source Type: Journal    
DOI: 10.1081/STA-200026574     Document Type: Article

References (18)

1. Cruz-Medina, R. (2000). Almost Nonparametric and Nonparametric Estimation in Mixture Models. Ph.D. thesis, The Pennsylvania State University.
2. Cruz-Medina, I. R., Hettmansperger, T. P., Thomas, H. (2004). Semi parametric mixture models and repeated measures: The multi-nomial cut point model. Appl. Statist. 53:463-474.
3. Dempster, A. P., Laird, N. M., Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm (C/R: P22-37). J. R. Statist. Soc. [B] 39:1-22.
4. Efron, B., Tibshirani, R. (1993). An Introduction to the Bootstrap. London: Chapman & Hall Ltd.
5. Elmore, R. T. (2003). Semiparametric Analysis of Finite Mixture Models with Repeated Measures. Ph.D. thesis, The Pennsylvania State University.
6. Elmore, R. T., Wang, S. (2003). Identifiability and estimation in finite mixture models with multinomial components. Technical Report #03-04, The Pennsylvania State University, Department of Statistics.
7. Hall, P. (1981). On the non-parametric estimation of mixture proportions. J. R. Statist. Soc. [B] 43:147-156.
8. Hall, P., Titterington, D. M. (1984). Efficient nonparametric estimation of mixture proportions. J. R. Statist. Soc. [B] 46:465-473.
9. Hall, P., Zhou, X. H. (2003). Nonparametric estimation of component distributions in a multivariate mixture. Ann. Stat. 31:201-224.
10. Hettmansperger, T. P., Thomas, H. (2000). Almost nonparametric inference for repeated measures in mixture models. J. R. Statist. Soc. [B] 62:811-825.
11. Hunter, D. M., Wang, S., Hettmansperger, T. P. (2003). Mixtures of Location-Shifted Symmetric Distributions. Manuscript.
12. Kim, B. S. (1984). Studies of Multinomial Mixture Models. Ph.D. thesis, University of North Carolina - Chapel Hill
13. Lindsay, B. G. (1995). Mixture Models: Theory, Geometry, and Applications. New York: Hayward.
14. McLachlan, G. J., Peel, D. (2000). Finite Mixture Models. New York: John Wiley and Sons.
15. Piaget, J., Inhelder, B. (1967). The Child's Conception of Space. New York: Norton.
16. Thomas, H., Lohaus, A. (1993). Modeling Growth and Individual Differences in Spatial Tasks. Chicago: University of Chicago Press.
17. Titterington, D. M. (1983). Minimum distance non-parametric estimation of mixture proportions. J. R. Statist. Soc. [B] 45:37-46.
18. Titterington, D. M., Smith, A. F., Makov, U. E. (1984). Statistical Analysis of Finite Mixture Distributions. New York: John Wiley and Sons.