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Condition: Très bon. Tome 9. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Volume 9. Ammareal gives back up to 15% of this item's net price to charity organizations.
Paperback. Condition: Good. Texte Francais, Couverture Souple. État D'usage: Bon État. Book.
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Paperback. Condition: Very Good. Couverture Souple, Texte Francais. État D'usage: Très Bon État. (French Edition). Book.
Paperback. Condition: Very Good. Couverture Souple, Texte Francais. État D'usage: Très Bon État. Book.
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Add to basketPaperBack. Condition: Good. No Jacket. Lecture Notes in Statistics 102.388pp. Good condition paperback version.
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Softcover. Condition: Gut. Bln., Springer (1995). gr.8°. XII, 376 p. Pbck. (sligthly stained).- Lecture Notes in Statistics, 102.- Title missing, otherwise inside in good condition.
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Add to basketHardcover. Condition: Brand New. 934 pages. 9.25x6.10x2.05 inches. In Stock.
Condition: new. Expédition le jour même. Libraire depuis 27 ans. Envoi soigné avec suivi.
Condition: new. Expédition le jour même. Libraire depuis 27 ans. Envoi soigné avec suivi.
gebundene Ausgabe. Condition: Gut. 367 Seiten; Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber. Es befindet sich neben dem Rückenschild lediglich ein Bibliotheksstempel im Buch; ordnungsgemäß entwidmet. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 740.
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Condition: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.
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Condition: Hervorragend. Zustand: Hervorragend | Seiten: 952 | Sprache: Englisch | Produktart: Bücher | This book explores topics in multivariate statistical analysis, relevant in the real and complex domains. It utilizes simplified and unified notations to render the complex subject matter both accessible and enjoyable, drawing from clear exposition and numerous illustrative examples. The book features an in-depth treatment of theory with a fair balance of applied coverage, and a classroom lecture style so that the learning process feels organic. It also contains original results, with the goal of driving research conversations forward. This will be particularly useful for researchers working in machine learning, biomedical signal processing, and other fields that increasingly rely on complex random variables to model complex-valued data. It can also be used in advanced courses on multivariate analysis. Numerous exercises are included throughout.
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