Monte Carlo strategies in scientific computing
"This book provides a self-contained and up-to-date treatment of the Monte Carlo method and develops a common framework under which various Monte Carlo techniques can be "standardized" and compared. Given the interdisciplinary nature of the topics and a moderate prerequisite for the r...
Enregistré dans:
Auteur principal : | |
---|---|
Format : | Livre |
Langue : | anglais |
Titre complet : | Monte Carlo strategies in scientific computing / Jun S. Liu |
Publié : |
New York :
Springer
, cop. 2001 |
Description matérielle : | 1 vol. (XVI-343 p.) |
Collection : | Springer series in statistics |
Sujets : |
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200 | 1 | |a Monte Carlo strategies in scientific computing |f Jun S. Liu | |
210 | |a New York |c Springer |d cop. 2001 | ||
215 | |a 1 vol. (XVI-343 p.) |c ill., graph., fig. |d 24 cm | ||
225 | 2 | |a Springer series in statistics | |
305 | |a Autres tirages : 2004, 2008 (1er tirage broché ) | ||
320 | |a Bibliogr. p. [313]-332. Index | ||
330 | |a "This book provides a self-contained and up-to-date treatment of the Monte Carlo method and develops a common framework under which various Monte Carlo techniques can be "standardized" and compared. Given the interdisciplinary nature of the topics and a moderate prerequisite for the reader, this book should be of interest to a broad audience of quantitative researchers such as computational biologists, computer scientists, econometricians, engineers, probabilists, and statisticians. It can also be used as the textbook for a graduate-level course on Monte Carlo methods. Many problems discussed in the alter chapters can be potential thesis topics for masters or Ph.D. students in statistics or computer science departments" | ||
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