Descripción del título
Information Geometry and Po...
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
Monografía
monografia Rebiun22985073 https://catalogo.rebiun.org/rebiun/record/Rebiun22985073 170224s2017 gw s 00 0 eng d 9783319520452 9783319520445 9783319520469 9783319848051 UMA.RE Hofrichter, Julian. aut. http://id.loc.gov/vocabulary/relators/aut Information Geometry and Population Genetics Recurso electrónico] :] The Mathematical Structure of the Wright-Fisher Model by Julian Hofrichter, Jürgen Jost, Tat Dat Tran Cham Springer International Publishing 2017 Cham Cham Springer International Publishing XII, 320 p. 3 il., 2 il. col XII, 320 p. 3 il., 2 il. col Text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Understanding Complex Systems 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 Mathematical statistics Human genetics Global analysis (Mathematics) Geometry Distribution (Probability theory Mathematical and Computational Biology Statistical Theory and Methods Human Genetics Analysis Probability Theory and Stochastic Processes Jost, Jürgen Tran, Tat Dat Understanding Complex Systems