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Mathematics Mathematical Logic for Computer Science (3rd edition)
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-Mathematics for the Physical Sciences- by Herbert S. Wilf
Mathematics for Elementary Teachers - A Conceptual Approach, 9 edition
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How to Fold It - The Mathematics of Linkages, Origami and Polyhedra
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Topology (Allyn and Bacon Series in Advanced Mathematics) by James Dugundji
Mathematics Fundamentals of Algebraic Modeling - An Introduction to Mathematical Modeling with Algebra and Statistics, 5 edition
Mathematics LMSST - 24 Lectures on Elliptic Curves (London Mathematical Society Student Texts) by J. W. S. Cassels
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Mathematics Le raisonnement bay¨¦sien: Mod¨¦lisation et inf¨¦rence
Posted on 2010-04-12
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More ¨¦ric Parent, Jacques Bernier ¡°Le raisonnement bay¨¦sien: Mod¨¦lisation et inf¨¦rence" Cet ouvrage expose de fa?on d¨¦taill¨¦e la pratique de l'approche statistique bay¨¦sienne ¨¤ l'aide de nombreux exemples choisis pour leur int¨¦r¨ºt p¨¦dagogique. Il insiste particuli¨¨rement sur l'emploi du raisonnement conditionnel qui fonde la coh¨¦rence profonde des m¨¦thodes de la mod¨¦lisation et de l'inf¨¦rence statistique sous le paradigme bay¨¦sien. La premi¨¨re partie donne les principes g¨¦n¨¦raux de mod¨¦lisation statistique permettant d'encadrer mais aussi de venir au secours de l'imagination de l'apprenti mod¨¦lisateur. En examinant des exemples de difficult¨¦ croissante, le lecteur forge les cl¨¦s pour construire son propre mod¨¨le. La seconde partie pr¨¦sente les algorithmes de calcul les plus utiles pour estimer les inconnues du mod¨¨le. Chaque m¨¦thode d'inf¨¦rence est pr¨¦sent¨¦e et illustr¨¦e par de nombreux cas d'applications. Si n¨¦cessaire, un rappel de leur cadre th¨¦orique essentiel est pr¨¦sent¨¦ sans d¨¦monstration. Le livre cherche ainsi ¨¤ d¨¦gager les ¨¦l¨¦ments cl¨¦s de la statistique bay¨¦sienne, en faisant l'hypoth¨¨se que le lecteur poss¨¨de les bases de la th¨¦orie des probabilit¨¦s et s'est d¨¦j¨¤ trouv¨¦ confront¨¦ ¨¤ des probl¨¨mes ordinaires d'analyse statistique classique. Il peut servir de support ¨¤ un cours de mod¨¦lisation ou de statistique appliqu¨¦e dans un programme de Master ou d'Ecole d'Ing¨¦nieurs. Il s'adresse ¨¦galement aux chercheurs et utilisateurs d¨¦sireux de s'assurer de la pertinence des m¨¦thodes qu'ils emploient. Le d¨¦butant, au prix d'un investissement intellectuel acceptable, aussi bien que le sp¨¦cialiste, pourront y trouver les informations fondamentales pour comprendre et mettre en uvre des mod¨¨les r¨¦pondant ¨¤ leurs besoins sp¨¦cifiques. "
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