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Evidence functions: a compositional approach to information

Author
Egozcue, J. J.; Pawlowsky, V.
Type of activity
Journal article
Journal
SORT: statistics and operations research transactions
Date of publication
2018-07-01
Volume
42
Number
2
First page
101
Last page
124
DOI
10.2436/20.8080.02.71
Repository
http://hdl.handle.net/2117/129877 Open in new window
URL
https://www.idescat.cat/sort/sort422/42.2.1.egozcue-pawlowsky.pdf Open in new window
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 ...
Citation
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.
Keywords
Aitchison geometry, Bayes' formula, Evidence function, compositions, orthonormal basis, scalar information, simplex
Group of research
COSDA-UPC - COmpositional and Spatial Data Analysis

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