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Universitat de Girona. Departament dâ€™InformÃ tica i MatemÃ tica Aplicada  
Aitchison, John  
Finite probability distributions and compositional data are mathematically similar, consisting ofDdimensional positive vectors with sum 1. Despite this similarity the meaningful forms of analysisin these different areas may require substantially different concepts and statistical modelling. Thispaper highlights these differences, but also poses the question of how such differences may contributeto understanding in the different areas. At CoDa workshops we have become so accustomed to, evenobsessed with, modelling all compositional data problems within a simplex sample space togetherwith its algebraicgeometric Hilbert space structure. The context of this Hilbert sample space iscertainly often relevant to the formulation of a number of compositional data problems, but itsmathematical elegance should not override appropriate meaningful statistical modelling to resolvethe real compositional problem. In this paper I illustrate some relevant modelling by considerationof how a variety of persons differ in their ability to perform inferential tasks particularly in theprocess of differential diagnosis  
http://hdl.handle.net/2072/273652  
eng  
Universitat de Girona. Departament dâ€™InformÃ tica i MatemÃ tica Aplicada  
Tots els drets reservats  
EstadÃstica matemÃ tica  Congressos
Mathematical statistics  Congresses AnÃ lisi multivariable  Congressos Multivariate analysis  Congresses DistribuciÃ³ (Teoria de la probabilitat)  Congressos Distribution (Probability theory)  Congresses 

Statistical Modelling of Compositional Problems Involving Finite Probability Distributions  
info:eurepo/semantics/conferenceObject  
Recercat 