9780387945279 - Monte Carlo: Concepts, Algorithms, and Applications (Springer Series in Operations Research and Financial Engineering) von Fishman, George (6 Ergebnisse)

Hardcover. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Hardcover-Großformat. Zustand: Gut. 698 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: 1405.

Zustand: Sehr gut. 723 p. In very good condition. Upper spine bumped. ISBN: 9780387945279 Sprache: Englisch Gewicht in Gramm: 1310 19,1 x 4,4 x 24,1 cm, hardcover.

Hardcover. 7. [print.]. 698 S. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. Ex-library with stamp and library-signature. GOOD condition, some traces of use. 9780387945279 Sprache: Englisch Gewicht in Gramm: 550.

Zustand: leido. Includes bibliographical references and index. cartone 698.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an introduction to the Monte Carlo method suitable for a one-or two-semester course for graduate and advanced undergraduate students in the mathematical and engineering sciences. It also can serve as a reference for the professional analyst. In the past, my inability to provide students with a single source book on this topic for class and for later professional reference had left me repeatedly frustrated, and eventually motivated me to write this book. In addition to focused accounts of major topics, the book has two unifying themes: One concerns the effective use of information and the other concerns error control and reduction. The book describes how to incorporate information about a problem into a sampling plan in a way that reduces the cost of estimating its solution to within a specified error bound. Although exploiting special structures to reduce cost long has been a hallmark of the Monte Carlo method, the propen sity of users of the method to discard useful information because it does not fit traditional textbook models repeatedly has impressed me. The present account aims at reducing the impediments to integrating this information. Errors, both statistical and computational, abound in every Monte Carlo sam pling experiment, and a considerable methodology exists for controlling them.