The DOI matches its Crossref record.
Estimation and Hypothesis Testing in Finite Mixture Models
Abstract
SUMMARY: Finite mixture models are a useful class of models for application to data. When sample sizes are not large and the number of underlying densities is in question, likelihood ratio tests based on joint maximum likelihood estimation of the mixing parameter, λ, and the parameter of the underlying densities, θ, are problematical. Our approach places a prior distribution on λ and estimates θ by maximizing the likelihood of the data given θ with λ integrated out. Advantages of this approach, computational issues using the EM algorithm and directions for further work are discussed. The technique is applied to two examples.
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Cited by
McLachlan, G., & Peel, D. (2000) · Wiley Series in Probability and Statistics · doi:10.1002/0471721182 · Cited by 10,991
Practical issues in structural modeling
BENTLER, P. M., & CHOU, C.-P. (1987) · Sociological Methods & Research · doi:10.1177/0049124187016001004 · Cited by 5,804
Testing the number of components in a normal mixture
Lo, Y. (2001) · Biometrika · doi:10.1093/biomet/88.3.767 · Cited by 4,640
An entropy criterion for assessing the number of clusters in a mixture model
Celeux, G., & Soromenho, G. (1996) · Journal of Classification · doi:10.1007/bf01246098 · Cited by 2,448
Conscientiousness, Extraversion, College Education, and Longevity of High-Ability Individuals
Savelyev, P. A. (2010) · doi:10.2139/ssrn.1715942 · Cited by 52
Metadata
- Authors
- Aitkin, M., & Rubin, D. B.
- Venue
- Journal of the Royal Statistical Society Series B: Statistical Methodology
- Publisher
- Oxford University Press (OUP)
- Published
- 1985-09-01
- Volume
- 47
- Issue
- 1
- Pages
- 67-75
- ISSN
- 1369-7412 (ISSN-L)
- 1467-9868
- OpenAlex
- W26112474
- Cited by
- 308
- References
- 0
- FWCI
- 4.69
- Type
- journal article
- Language
- en
- Open access
- closed
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- Aitkin, M., & Rubin, D. B. (1985). Estimation and Hypothesis Testing in Finite Mixture Models. Journal of the Royal Statistical Society Series B: Statistical Methodology. https://doi.org/10.1111/j.2517-6161.1985.tb01331.x
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