Monte Carlo : Concepts, Algorithms, and Applications

George Fishman

ISBN 10: 038794527X / ISBN 13: 9780387945279

Editore: Springer New York, Springer US, 1996

Riguardo questo articolo

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.

Codice articolo 9780387945279

Dati bibliografici

• Titolo: Monte Carlo : Concepts, Algorithms, and Applications
• Editore: Springer New York, Springer US
• Data di pubblicazione: 1996
• Lingua: Inglese
• ISBN 10: 038794527X
• ISBN 13: 9780387945279
• Rilegatura: Buch
• Condizione: Neu

Descrizione articolo

Riassunto

Apart from a thorough exploration of all the important concepts, this volume includes over 75 algorithms, ready for putting into practice. The book also contains numerous hands-on implementations of selected algorithms to demonstrate applications in realistic settings. Readers are assumed to have a sound understanding of calculus, introductory matrix analysis, and intermediate statistics, but otherwise the book is self-contained. Suitable for graduates and undergraduates in mathematics and engineering, in particular operations research, statistics, and computer science.

Contenuti

Preface * Selected Notation * 1 Introduction * 2 Estimating Volume and Count * 3 Generating Samples * 4 Increasing Efficiency * 5 Random Tours * 6 Designing and Analyzing Sample Paths * 7 Generating Pseudorandom Numbers * Author Index * Subject Index