Statistical physics : an advanced approach with applications ; web enhanced with problems and solutions ; with 7 tables and 57 problems with solutions. Physics and astronomy online library; Advanced texts in physics

Honerkamp, Josef:

ISBN 10: 3540430202 / ISBN 13: 9783540430209

Verlag: Berlin ; Heidelberg ; New York ; Barcelona ; Hong Kong ; London ; Milan ; Paris ; Tokyo : Springer, 2002

Beschreibung

XIV, 515 Seiten. Mit zahlreichen graphischen Darstellungen ; 24 cm FRISCHES, SEHR schönes Exemplar. (We offer a lot of books on PHYSICS and MATHEMATICS on stock in EXCELLENT shape). Sprache: Englisch Gewicht in Gramm: 1005. Bestandsnummer des Verkäufers 297479

Bibliografische Details

Titel: Statistical physics : an advanced approach ...

Verlag: Berlin ; Heidelberg ; New York ; Barcelona ; Hong Kong ; London ; Milan ; Paris ; Tokyo : Springer

Erscheinungsdatum: 2002

Einband: Originalpappband.

Zustand: Wie neu

Auflage: 2. edition.

Über diesen Titel

Inhaltsangabe:

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.

Von der hinteren Coverseite:

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.