1985•Journal of the American Statistical AssociationRequires access

Applications of Catastrophe Theory for Statistical Modeling in the Biosciences

Loren Cobb, Shelemyahu Zacks

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Abstract

Although catastrophe theory has been applied with mixed success to many problems in the biosciences, very few of these applications have used any form of statistical modeling. We present examples of the applications of statistical catastrophe theory in the analysis of experimental data. These include examples of hysteresis effects, bifurcation effects, and the full cusp catastrophe model. The methods of statistical catastrophe theory draw upon the theories of parameter estimation for multiparameter exponential families, nonlinear time-series analysis, and stochastic differential equations. We discuss the application of these methods to both canonical and noncanonical catastrophe models.

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What this paper is about

Although catastrophe theory has been applied with mixed success to many problems in the biosciences, very few of these applications have used any form of statistical modeling. We present examples of the applications of statistical catastrophe theory in the analysis of experimental data. These include examples of hysteresis effects, bifurcation effects, and the full cusp catastrophe model. The methods of statistical catastrophe theory draw upon the theories of parameter estimation for multiparameter exponential families, nonlinear time-series analysis, and stochastic differential equations. We discuss the application of these methods to both canonical and noncanonical catastrophe models.

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Available abstract

Although catastrophe theory has been applied with mixed success to many problems in the biosciences, very few of these applications have used any form of statistical modeling. We present examples of the applications of statistical catastrophe theory in the analysis of experimental data. These include examples of hysteresis effects, bifurcation effects, and the full cusp catastrophe model. The methods of statistical catastrophe theory draw upon the theories of parameter estimation for multiparameter exponential families, nonlinear time-series analysis, and stochastic differential equations. We discuss the application of these methods to both canonical and noncanonical catastrophe models.

Key concepts: Catastrophe theory, Statistical theory, Statistical physics, Cusp (singularity), Applied mathematics, Series (stratigraphy), Statistical model, Nonlinear system

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