This article defines the so called Generalized Matrix Variate Jensen-Logistic distribution. The relevant applications of this class of distributions in Configuration Shape Theory consist of a more efficient computation, supported by the corresponding inference. This demands the solution of two impor...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2015
- Institución:
- Universidad de Medellín
- Repositorio:
- Repositorio UDEM
- Idioma:
- eng
- OAI Identifier:
- oai:repository.udem.edu.co:11407/1552
- Acceso en línea:
- http://hdl.handle.net/11407/1552
- Palabra clave:
- Generalized Kummer relations
Jensen-Logistic distribution
Pascal triangle
Statistical shape theory
Zonal polynomials
- Rights
- restrictedAccess
- License
- http://purl.org/coar/access_right/c_16ec
| Summary: | This article defines the so called Generalized Matrix Variate Jensen-Logistic distribution. The relevant applications of this class of distributions in Configuration Shape Theory consist of a more efficient computation, supported by the corresponding inference. This demands the solution of two important problems: (1) the development of analytical and efficient formulae for their k-th derivatives and (2) the use of the derivatives to transform the configuration density into a polynomial density under some special matrix Kummer relation, indexed in this case by the Jensen-Logistic kernel. In this article, we solve these problems by deriving a simple formula for the k-th derivative of the density function, avoiding the usual partition theory framework and using a generalization of Pascal triangles. Then we apply the results by obtaining the associated Jensen-Logistic Kummer relations and the configuration polynomial density in the setting of Statistical Shape Theory. © 2015 Taylor and Francis Group, LLC. |
|---|