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Information geometry and population ...
~
Hofrichter, Julian.
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Information geometry and population genetics = the mathematical structure of the Wright-Fisher model /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Information geometry and population genetics/ by Julian Hofrichter, Jurgen Jost, Tat Dat Tran.
Reminder of title:
the mathematical structure of the Wright-Fisher model /
Author:
Hofrichter, Julian.
other author:
Jost, Jurgen.
Published:
Cham :Springer International Publishing : : 2017.,
Description:
xii, 319 p. :ill., digital ;24 cm.
[NT 15003449]:
1. Introduction -- 2. The Wright-Fisher model -- 3. Geometric structures and information geometry -- 4. Continuous approximations -- 5. Recombination -- 6. Moment generating and free energy functionals -- 7. Large deviation theory -- 8. The forward equation -- 9. The backward equation -- 10.Applications -- Appendix -- A. Hypergeometric functions and their generalizations -- Bibliography.
Contained By:
Springer eBooks
Subject:
Population genetics - Mathematical models. -
Online resource:
http://dx.doi.org/10.1007/978-3-319-52045-2
ISBN:
9783319520452
Information geometry and population genetics = the mathematical structure of the Wright-Fisher model /
Hofrichter, Julian.
Information geometry and population genetics
the mathematical structure of the Wright-Fisher model /[electronic resource] :by Julian Hofrichter, Jurgen Jost, Tat Dat Tran. - Cham :Springer International Publishing :2017. - xii, 319 p. :ill., digital ;24 cm. - Understanding complex systems,1860-0832. - Understanding complex systems..
1. Introduction -- 2. The Wright-Fisher model -- 3. Geometric structures and information geometry -- 4. Continuous approximations -- 5. Recombination -- 6. Moment generating and free energy functionals -- 7. Large deviation theory -- 8. The forward equation -- 9. The backward equation -- 10.Applications -- Appendix -- A. Hypergeometric functions and their generalizations -- Bibliography.
The present monograph develops a versatile and profound mathematical perspective of the Wright--Fisher model of population genetics. This well-known and intensively studied model carries a rich and beautiful mathematical structure, which is uncovered here in a systematic manner. In addition to approaches by means of analysis, combinatorics and PDE, a geometric perspective is brought in through Amari's and Chentsov's information geometry. This concept allows us to calculate many quantities of interest systematically; likewise, the employed global perspective elucidates the stratification of the model in an unprecedented manner. Furthermore, the links to statistical mechanics and large deviation theory are explored and developed into powerful tools. Altogether, the manuscript provides a solid and broad working basis for graduate students and researchers interested in this field.
ISBN: 9783319520452
Standard No.: 10.1007/978-3-319-52045-2doiSubjects--Topical Terms:
651612
Population genetics
--Mathematical models.
LC Class. No.: QH455
Dewey Class. No.: 576.58015118
Information geometry and population genetics = the mathematical structure of the Wright-Fisher model /
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1. Introduction -- 2. The Wright-Fisher model -- 3. Geometric structures and information geometry -- 4. Continuous approximations -- 5. Recombination -- 6. Moment generating and free energy functionals -- 7. Large deviation theory -- 8. The forward equation -- 9. The backward equation -- 10.Applications -- Appendix -- A. Hypergeometric functions and their generalizations -- Bibliography.
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The present monograph develops a versatile and profound mathematical perspective of the Wright--Fisher model of population genetics. This well-known and intensively studied model carries a rich and beautiful mathematical structure, which is uncovered here in a systematic manner. In addition to approaches by means of analysis, combinatorics and PDE, a geometric perspective is brought in through Amari's and Chentsov's information geometry. This concept allows us to calculate many quantities of interest systematically; likewise, the employed global perspective elucidates the stratification of the model in an unprecedented manner. Furthermore, the links to statistical mechanics and large deviation theory are explored and developed into powerful tools. Altogether, the manuscript provides a solid and broad working basis for graduate students and researchers interested in this field.
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Mathematics and Statistics (Springer-11649)
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