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Auteur Igor Vajda |
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Titre : Theory of statistical inference and information Type de document : texte imprimé Auteurs : Igor Vajda, Auteur Editeur : Boston : Kluwer academic publishers Année de publication : 1989 Collection : Theory and decision library Sous-collection : Series B: Mathematical and statistical methods num. 11 Importance : 432 p. Présentation : ill. Format : 25 cm ISBN/ISSN/EAN : 978-90-277-2781-7 Note générale : Trad. de : "Teória informácie a štatistického rozhodovania".
Bibliogr. p. [404]-423. Index
Langues : Anglais (eng) Mots-clés : Convex functions
Mathematical statistics
Information theory
Fonctions convexes
Statistique mathématique
Information, Théorie de l'Index. décimale : 519.72 Théorie de l'information: aspects mathématiques. Résumé : Theory of statistical inference and information contributes to the literature on mathematical statistics in two ways: (1) know methods are characterized in a generalized from using the results of convex analysis in spaces of measures, and (2) new methods are introduced and studied in light of the general mathematical background. Note de contenu : Contents:
* Prerequisities.
* Conditional probabilities and expectations.
* Convex functions of real variables.
* Supplements and examples.
* Convex functions of measures.
* Kantorovich- Vasershtein and related functions of measures.
...Theory of statistical inference and information [texte imprimé] / Igor Vajda, Auteur . - Boston : Kluwer academic publishers, 1989 . - 432 p. : ill. ; 25 cm. - (Theory and decision library. Series B: Mathematical and statistical methods; 11) .
ISBN : 978-90-277-2781-7
Trad. de : "Teória informácie a štatistického rozhodovania".
Bibliogr. p. [404]-423. Index
Langues : Anglais (eng)
Mots-clés : Convex functions
Mathematical statistics
Information theory
Fonctions convexes
Statistique mathématique
Information, Théorie de l'Index. décimale : 519.72 Théorie de l'information: aspects mathématiques. Résumé : Theory of statistical inference and information contributes to the literature on mathematical statistics in two ways: (1) know methods are characterized in a generalized from using the results of convex analysis in spaces of measures, and (2) new methods are introduced and studied in light of the general mathematical background. Note de contenu : Contents:
* Prerequisities.
* Conditional probabilities and expectations.
* Convex functions of real variables.
* Supplements and examples.
* Convex functions of measures.
* Kantorovich- Vasershtein and related functions of measures.
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