Entropies and Fisher information matrix for extended beta distribution
ABSTRACT: The extended beta type 1 distribution has the probability density function proportional to x α−1 (1 − x) β−1 exp[−σ/x(1 − x)], 0 < x < 1. In this article, we derive the Fisher information matrix and entropies such as R´enyi and Shannon for the extended beta type 1 distribution....
- Autores:
-
Nagar, Daya Krishna
Zarrazola Rivera, Edwin de Jesús
Sánchez Herrera, Luz Estela
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2015
- Institución:
- Universidad de Antioquia
- Repositorio:
- Repositorio UdeA
- Idioma:
- eng
- OAI Identifier:
- oai:bibliotecadigital.udea.edu.co:10495/26794
- Acceso en línea:
- http://hdl.handle.net/10495/26794
- Palabra clave:
- Entropy
Entropía
Beta function
Extended beta function
Information matrix
Probability distribution
http://aims.fao.org/aos/agrovoc/c_1fc62594
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by/2.5/co/
| Summary: | ABSTRACT: The extended beta type 1 distribution has the probability density function proportional to x α−1 (1 − x) β−1 exp[−σ/x(1 − x)], 0 < x < 1. In this article, we derive the Fisher information matrix and entropies such as R´enyi and Shannon for the extended beta type 1 distribution. |
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