Estimation of mean form and mean form difference under elliptical laws
The matrix variate elliptical generalization of [30] is presented in this work. The published Gaussian case is revised and modified. Then, new aspects of identifiability and consistent estimation of mean form and mean form difference are considered under elliptical laws. For example, instead of usin...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2017
- Institución:
- Universidad de Medellín
- Repositorio:
- Repositorio UDEM
- Idioma:
- eng
- OAI Identifier:
- oai:repository.udem.edu.co:11407/4271
- Acceso en línea:
- http://hdl.handle.net/11407/4271
- Palabra clave:
- Coordinate free approach
Matrix variate elliptical distribution
Matrix variate Gaussian distribution
Non-central singular Pseudo-Wishart distribution
Statistical shape theory
- Rights
- License
- http://purl.org/coar/access_right/c_16ec
| Summary: | The matrix variate elliptical generalization of [30] is presented in this work. The published Gaussian case is revised and modified. Then, new aspects of identifiability and consistent estimation of mean form and mean form difference are considered under elliptical laws. For example, instead of using the Euclidean distance matrix for the consistent estimates, exact formulae are derived for the moments of the matrix B = Xc(Xc)T; where Xcis the centered landmark matrix. Finally, a complete application in Biology is provided; it includes estimation, model selection and hypothesis testing. © 2017, Institute of Mathematical Statistics. All rights reserved. |
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