Stochastic tools in mathematics and science
Author(s)
Bibliographic Information
Stochastic tools in mathematics and science
（Surveys and tutorials in the applied mathematical sciences, v. 1）
Springer, c2009
2nd ed
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
This introduction to probability-based modeling covers basic stochastic tools used in physics, chemistry, engineering and the life sciences. Topics covered include conditional expectations, stochastic processes, Langevin equations, and Markov chain Monte Carlo algorithms. The applications include data assimilation, prediction from partial data, spectral analysis and turbulence. A special feature is the systematic analysis of memory effects.
Table of Contents
Preliminaries.- Probability.- Brownian Motion.- Stationary Stochastic Processes.- Statistical Mechanics.- Time-Dependent Statistical Mechanics.
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