Statistical Physics: An Advanced Approach With Applications

Honerkamp, Josef

ISBN 10: 3540430202 / ISBN 13: 9783540430209

Editore: Springer, 2002

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This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Book contains pencil & highlighter markings. In poor condition, suitable as a reading copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1000grams, ISBN:9783540430209.

Codice articolo 5554332

Dati bibliografici

• Titolo: Statistical Physics: An Advanced Approach With Applications
• Editore: Springer
• Data di pubblicazione: 2002
• Lingua: Inglese
• ISBN 10: 3540430202
• ISBN 13: 9783540430209
• Rilegatura: Rilegato
• Edizione: seconda edizione
• Condizione: Poor
• Cataloghi dei venditori:
  • Physics

Descrizione articolo

Riassunto

The book is divided into two parts. The first part looks at the modeling of statistical systems before moving on to an analysis of these systems. This second edition contains new material on: estimators based on a probability distribution for the parameters; identification of stochastic models from observations; and statistical tests and classification methods.

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.