Stochastic World [electronic resource] / by Sergey S. Stepanov.

Por: Stepanov, Sergey S [author.]Tipo de material: TextoTextoSeries Mathematical EngineeringEditor: Heidelberg : Springer International Publishing : Imprint: Springer, 2013Descripción: X, 339 p. 70 illus., 32 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783319000718Trabajos contenidos: SpringerLink (Online service)Tema(s): Mathematics | Electronic data processing | Distribution (Probability theory) | Mathematical physics | Statistics | Mathematics | Probability Theory and Stochastic Processes | Numeric Computing | Mathematical Methods in Physics | Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law | Statistics for Engineering, Physics, Computer Science, Chemistry and Earth SciencesFormatos físicos adicionales: Sin títuloClasificación CDD: 519.2 Clasificación LoC:QA273.A1-274.9QA274-274.9Recursos en línea: de clik aquí para ver el libro electrónico
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Springer eBooksResumen: This book is an introduction into stochastic processes for physicists, biologists and financial analysts. Using an informal approach, all the necessary mathematical tools and techniques are covered, including the stochastic differential equations, mean values, probability distribution functions, stochastic integration and numerical modeling. Numerous examples of practical applications of the stochastic mathematics are considered in detail, ranging from physics to the financial theory. A reader with basic knowledge of the probability theory should have no difficulty in accessing the book content.
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Random Events -- Stochastic Equations -- Mean Values -- Probabilities -- Stochastic Integrals -- Systems of Equations -- Stochastic Nature -- Stochastic Society -- Computer Modeling.

This book is an introduction into stochastic processes for physicists, biologists and financial analysts. Using an informal approach, all the necessary mathematical tools and techniques are covered, including the stochastic differential equations, mean values, probability distribution functions, stochastic integration and numerical modeling. Numerous examples of practical applications of the stochastic mathematics are considered in detail, ranging from physics to the financial theory. A reader with basic knowledge of the probability theory should have no difficulty in accessing the book content.

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