Beginning with an explanation of the differences between deterministic and probabilistic models, Brown then introduces the reader to chaotic dynamics. Other topics covered are finding settings in which chaos can be measured, estimating chaos using nonlinear least squares and specifying catastrophe models. Finally a nonlinear system of equations that models catastrophe using real survey data is estimated.
Brown is well known for research on mathematical modeling in the social sciences. His book introduces the graph algebra approach to modeling systems in the social sciences.
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Graph Algebra: Mathematical Modeling with a Systems Approach introduces a new modeling tool to students and researchers in the social sciences. Derived from engineering literature that uses similar techniques to map electronic circuits and physical systems, graph algebra utilizes a systems approach to modeling that offers social scientists a variety of tools that are both sophisticated and easily applied.
Key Features:
This text is ideal for use in graduate courses such as Statistical Modeling, Quantitative Methods, and Applied Mathematics.
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Readers can use graphical methods to produce penetrating analysis of differential equation systems.
Linear and nonlinear model specifications are explained from a social science perspective. Most interesting differential equation models are nonlinear, and readers need to know how to specify and work with such models in the social sciences.
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