From Kernels to Mixtures
- 1 August 2001
- journal article
- research article
- Published by Taylor & Francis in Technometrics
- Vol. 43 (3) , 323-335
- https://doi.org/10.1198/004017001316975916
Abstract
Mixture models, which include kernel estimators, are used widely to model complex densities; however, one is faced with the challenge of determining an appropriate number of components. This task often involves identifying those components that are close enough to be combined. This article introduces a new easily calculated measure of similarity between pairs of densities and illustrates its use in recursively collapsing components. This similarity measure leads naturally to a new algorithm (IPRA) for fitting mixture models sequentially. The algorithm is used to test for bumps in galaxy star velocity data and to examine MRI data.Keywords
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