dc.contributor
Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental
dc.contributor
Universitat Politècnica de Catalunya. COSDA-UPC - COmpositional and Spatial Data Analysis
dc.contributor.author
Egozcue Rubí, Juan José
dc.contributor.author
Pawlowsky Glahn, Vera
dc.date.issued
2018-07-01
dc.identifier
Egozcue, J. J.; Pawlowsky, V. Evidence functions: a compositional approach to information. "SORT: statistics and operations research transactions", 1 Juliol 2018, vol. 42, núm. 2, p. 101-124.
dc.identifier
https://hdl.handle.net/2117/129877
dc.identifier
10.2436/20.8080.02.71
dc.description.abstract
The discrete case of Bayes’ formula is considered the paradigm of information acquisition. Prior and posterior probability functions, as well as likelihood functions, called evidence functions, are compositions following the Aitchison geometry of the simplex, and have thus vector character. Bayes’ formula becomes a vector addition. The Aitchison norm of an evidence function is introduced as a scalar measurement of information. A fictitious fire scenario serves as illustration. Two different inspections of affected houses are considered. Two questions are addressed: (a) which is the information provided by the outcomes of inspections, and (b) which is the most informative inspection.
dc.description.abstract
Peer Reviewed
dc.description.abstract
Postprint (author's final draft)
dc.format
application/pdf
dc.publisher
Institut d'Estadística de Catalunya
dc.relation
https://www.idescat.cat/sort/sort422/42.2.1.egozcue-pawlowsky.pdf
dc.subject
Àrees temàtiques de la UPC::Matemàtiques i estadística::Probabilitat
dc.subject
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica::Anàlisi multivariant
dc.subject
Distribution (Probability theory)
dc.subject
Evidence function
dc.subject
Bayes' formula
dc.subject
Aitchison geometry
dc.subject
orthonormal basis
dc.subject
scalar information
dc.subject
Distribució (Teoria de la probabilitat)
dc.subject
Classificació AMS::60 Probability theory and stochastic processes::60A Foundations of probability theory
dc.subject
Classificació AMS::62 Statistics::62E Distribution theory
dc.title
Evidence functions: a compositional approach to information
