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Finite Mixture and Markov Switching Models
The prominence of finite mixture modelling is greater than ever. Many important statistical topics like clustering data, outlier treatment, or dealing with unobserved heterogeneity involve finite mixture models in some way or other. The area of potential applications goes beyond simple data analysis...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York, NY :
Springer New York : Imprint: Springer,
2006.
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| Edición: | 1st ed. 2006. |
| Colección: | Springer Series in Statistics,
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| Temas: | |
| Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- Finite Mixture Modeling
- Statistical Inference for a Finite Mixture Model with Known Number of Components
- Practical Bayesian Inference for a Finite Mixture Model with Known Number of Components
- Statistical Inference for Finite Mixture Models Under Model Specification Uncertainty
- Computational Tools for Bayesian Inference for Finite Mixtures Models Under Model Specification Uncertainty
- Finite Mixture Models with Normal Components
- Data Analysis Based on Finite Mixtures
- Finite Mixtures of Regression Models
- Finite Mixture Models with Nonnormal Components
- Finite Markov Mixture Modeling
- Statistical Inference for Markov Switching Models
- Nonlinear Time Series Analysis Based on Markov Switching Models
- Switching State Space Models.