On choosing mixture components via non-local priors
Choosing the number of mixture components remains an elusive challenge. Model selection criteria can be either overly liberal or conservative and return poorly separated components of limited practical use. We formalize non-local priors (NLPs) for mixtures and show how they lead to well-separated co...
| Veröffentlicht in: | Journal of the Royal Statistical Society. Series B (Statistical Methodology). - Blackwell Publishers. - 81(2019), 5, Seite 809-837 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2019
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| Zugriff auf das übergeordnete Werk: | Journal of the Royal Statistical Society. Series B (Statistical Methodology) |
| Online verfügbar |
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