Please use this identifier to cite or link to this item: https://doi.org/10.1093/biomet/89.1.77
Title: On the local geometry of mixture models
Authors: Marriott, P. 
Keywords: Convex geometry
Differential geometry
Measurement error
Mixture model
Prediction
Random effects model
Statistical manifold
Issue Date: 2002
Citation: Marriott, P. (2002). On the local geometry of mixture models. Biometrika 89 (1) : 77-93. ScholarBank@NUS Repository. https://doi.org/10.1093/biomet/89.1.77
Abstract: Despite the well-known difficulties of undertaking inference with mixture models, they are frequently used for modelling. These inferential problems arise because the underlying geometry of a mixture family is very complicated. This paper shows that by adding a simplifying assumption, which frequently is natural statistically, the geometric structure is reduced to a much more tractable form. This enables standard inferential techniques to be applied successfully. One result of studying the local geometry is that it unifies the convex and differential geometric theories of mixture models. The techniques proposed are applied to prediction, random effects and measurement error models. © 2002 Biometrika Trust.
Source Title: Biometrika
URI: http://scholarbank.nus.edu.sg/handle/10635/105277
ISSN: 00063444
DOI: 10.1093/biomet/89.1.77
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