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Maximum Augmented Empirical Likelihood Estimation of Categorical Marginal Models for Large Sparse Contingency Tables
Categorical marginal models (CMMs) are flexible tools for modelling dependent or clustered categorical data, when the dependencies themselves are not of interest. A major limitation of maximum likelihood (ML) estimation of CMMs is that the size of the contingency table increases exponentially with t...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10656332/ https://www.ncbi.nlm.nih.gov/pubmed/37752345 http://dx.doi.org/10.1007/s11336-023-09932-7 |