On matrix-variate Birnbaum–Saunders distributions and their estimation and application
Diverse phenomena from the real-world can be modeled using random matrices, allowing matrix-variate distributions to be considered. The normal distribution is often employed in this modeling, but usually the mentioned random matrices do not follow such a distribution. An asymmetric non-normal model...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2015
- Institución:
- Universidad de Medellín
- Repositorio:
- Repositorio UDEM
- Idioma:
- eng
- OAI Identifier:
- oai:repository.udem.edu.co:11407/1554
- Acceso en línea:
- http://hdl.handle.net/11407/1554
- Palabra clave:
- Computer language
Data analysis
Elliptically contoured distribution
Maximum likelihood estimator
Monte Carlo method
Shape theory
- Rights
- restrictedAccess
- License
- http://purl.org/coar/access_right/c_16ec
| Summary: | Diverse phenomena from the real-world can be modeled using random matrices, allowing matrix-variate distributions to be considered. The normal distribution is often employed in this modeling, but usually the mentioned random matrices do not follow such a distribution. An asymmetric non-normal model that is receiving considerable attention due to its good properties is the Birnbaum–Saunders (BS) distribution. We propose a statistical methodology based on matrix-variate BS distributions. This methodology is implemented in the statistical software R. A simulation study is conducted to evaluate its performance. Finally, an application with real-world matrix-variate data is carried out to illustrate its potentiality and suitability. |
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