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.

• 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