Repositori institucional URV
| Autor según el artículo: | Palarea-Albaladejo, Javier Mateu-Figueras, Glòria Martín-Fernández, Josep Antoni Comas-Cufí, Marc |
| Año de publicación de la revista: | 2020 |
| Tipo de publicación: | ##rt.metadata.pkp.peerReviewed## info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| Resumen: | The logratio-normal-multinomial distribution is a count data model resulting from compounding a multinomial distribution for the counts with a multivariate logratio-normal distribution for the multinomial event probabilities. However, the logratio-normal-multinomial probability mass function does not admit a closed form expression and, consequently, numerical approximation is required for parameter estimation. In this work, different estimation approaches are introduced and evaluated. We concluded that estimation based on a quasi-Monte Carlo Expectation-Maximisation algorithm provides the best overall results. Building on this, the performances of the Dirichlet-multinomial and logratio-normal-multinomial models are compared through a number of examples using simulated and real count data. |
| Palabras clave: | count data |
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