We introduce a prior distribution for the number of components of a mixture model. The prior considers the worth of each possible mixture, measured by a loss function with two components: one measures the loss in information in choosing the wrong mixture and one the loss due to complexity.
On a loss-based prior for the number of components in mixture models / C. Grazian, C. Villa, B. Liseo. - In: STATISTICS & PROBABILITY LETTERS. - ISSN 0167-7152. - 158(2020), pp. 108656.1-108656.7. [10.1016/j.spl.2019.108656]
On a loss-based prior for the number of components in mixture models
C. Villa;
2020
Abstract
We introduce a prior distribution for the number of components of a mixture model. The prior considers the worth of each possible mixture, measured by a loss function with two components: one measures the loss in information in choosing the wrong mixture and one the loss due to complexity.
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