Statistical Physics: An Advanced Approach with Applications. Web-enhanced with Problems and Solutions (Advanced Texts in Physics)

Josef Honerkamp

ISBN 10: 364207703X / ISBN 13: 9783642077036

Editore: Springer Berlin Heidelberg 2009-12-28, 2009

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Codice articolo 6666-IUK-9783642077036

Dati bibliografici

• Titolo: Statistical Physics: An Advanced Approach with Applications. Web-enhanced with Problems and Solutions (Advanced Texts in Physics)
• Editore: Springer Berlin Heidelberg 2009-12-28
• Data di pubblicazione: 2009
• Lingua: Inglese
• ISBN 10: 364207703X
• ISBN 13: 9783642077036
• Rilegatura: Paperback
• Edizione: seconda edizione
• Condizione: New

Descrizione articolo

Riassunto

The application of statistical methods to physics is essen- tial. This unique book on statistical physics offers an advanced approach with numerous applications to the modern problems students are confronted with. Therefore the text contains more concepts and methods in statistics than the student would need for statistical mechanics alone. Methods from mathematical statistics and stochastics for the analy- sis of data are discussed as well. The book is divided into two parts, focusing first on the modeling of statistical systems and then on the analysis of these systems. Problems with hints for solution help the students to deepen their knowledge. The second edition has been updated and enlarged with new material on estimators based on a probability dis- tribution for the parameters, identification of stochastic models from observations, and statistical tests and classi- fication methods (Chaps. 10-12). Moreover, a customized set of set of problems with solutions is accessible on the Web.

Dalla quarta di copertina

The application of statistical methods to physics is essential. This unique book on statistical physics offers an advanced approach with numerous applications to the modern problems students are confronted with. Therefore the text contains more concepts and methods in statistics than the student would need for statistical mechanics alone. Methods from mathematical statistics and stochastics for the analysis of data are discussed as well. The book is divided into two parts, focusing first on the modeling of statistical systems and then on the analysis of these systems. Problems with hints for solution help the students to deepen their knowledge. The second edition has been updated and enlarged with new material on estimators based on a probability distribution for the parameters, identification of stochastic models from observations, and statistical tests and classification methods (Chaps. 10-12). Moreover, a customized set of problems with solutions is accessible on the Web. The author teaches and conducts research on stochastic dynamical systems at the University of Freiburg, Germany.