Compositional ideas in the bayesian analysis of categorical data with application to dose finding clinical trials


Autoria(s): Gasparini, Mauro; Eisele, J.
Contribuinte(s)

Thió i Fernández de Henestrosa, Santiago

Martín Fernández, Josep Antoni

Universitat de Girona. Departament d'Informàtica i Matemàtica Aplicada

Data(s)

17/10/2003

Resumo

Compositional random vectors are fundamental tools in the Bayesian analysis of categorical data. Many of the issues that are discussed with reference to the statistical analysis of compositional data have a natural counterpart in the construction of a Bayesian statistical model for categorical data. This note builds on the idea of cross-fertilization of the two areas recommended by Aitchison (1986) in his seminal book on compositional data. Particular emphasis is put on the problem of what parameterization to use

Geologische Vereinigung; Universitat de Barcelona, Equip de Recerca Arqueomètrica; Institut d’Estadística de Catalunya; International Association for Mathematical Geology; Patronat de l’Escola Politècnica Superior de la Universitat de Girona; Fundació privada: Girona, Universitat i Futur.

Formato

application/pdf

Identificador

Gasparini, M.; Eisele, J. 'Compositional ideas in the bayesian analysis of categorical data with application to dose finding clinical trials' a CODAWORK’03. Girona: La Universitat, 2003 [consulta: maig 2008]. Necessita Adobe Acrobat. Disponible a Internet a: http://hdl.handle.net/10256/686

84-8458-111-X

http://hdl.handle.net/10256/686

Idioma(s)

eng

Publicador

Universitat de Girona. Departament d’Informàtica i Matemàtica Aplicada

Direitos

Tots els drets reservats

Palavras-Chave #Estadística bayesiana
Tipo

info:eu-repo/semantics/conferenceObject