Compositional ideas in the bayesian analysis of categorical data with application to dose finding clinical trials
dc.contributor.author
dc.contributor.editor
dc.date.accessioned
2008-05-06T09:44:08Z
dc.date.available
2008-05-06T09:44:08Z
dc.date.issued
2003-10-17
dc.identifier.citation
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
dc.identifier.isbn
84-8458-111-X
dc.identifier.uri
dc.description.abstract
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
dc.description.sponsorship
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.
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
Universitat de Girona. Departament d’Informàtica i Matemàtica Aplicada
dc.rights
Tots els drets reservats
dc.subject
dc.title
Compositional ideas in the bayesian analysis of categorical data with application to dose finding clinical trials
dc.type
info:eu-repo/semantics/conferenceObject
dc.rights.accessRights
info:eu-repo/semantics/openAccess