Stochastic Population Theory: Mathematical Evolution of a Genetical Model

Kenneth J. Hochberg
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Kenneth J. Hochberg: Case Western Reserve University, Department of Mathematics and Statistics

A chapter in The Merging of Disciplines: New Directions in Pure, Applied, and Computational Mathematics, 1986, pp 101-115 from Springer

Abstract: Abstract The use of mathematical modeling in characterizing and analyzing stochastic fluctuation phenomena among individuals in natural populations has a long and honorable history dating back to the first quarter of the twentieth century. Indeed, more than sixty years have passed since R. A. Fisher (1922) introduced diffusion theory in his analysis of the dominance ratio in population genetics theory. However, in the last decade, coincident with monumental progress in computational techniques and the introduction of novel ideas from the mathematical theory of probability and stochastic processes, the pace of the evolution of stochastic population theory—the use of mathematical techniques to explain and predict the random behavior of individuals in natural populations—has quickened markedly.

Keywords: Markov Process; Finite Population; Dual Process; Allelic Frequency Distribution; Dominance Ratio (search for similar items in EconPapers)
Date: 1986
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4612-4984-9_8

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DOI: 10.1007/978-1-4612-4984-9_8

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