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Bayesian cumulative shrinkage for infinite factorizations
The dimension of the parameter space is typically unknown in a variety of models that rely on factorizations. For example, in factor analysis the number of latent factors is not known and has to be inferred from the data. Although classical shrinkage priors are useful in such contexts, increasing sh...
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| Publicado no: | Biometrika |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7430941/ https://ncbi.nlm.nih.gov/pubmed/32831355 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/biomet/asaa008 |
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