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Titlebook: Stochastic Problems in Population Genetics; Takeo Maruyama Book 1977 Springer-Verlag Berlin Heidelberg 1977 Biomathematik.Derivation.Finit

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書(shū)目名稱(chēng)Stochastic Problems in Population Genetics
編輯Takeo Maruyama
視頻videohttp://file.papertrans.cn/879/878094/878094.mp4
叢書(shū)名稱(chēng)Lecture Notes in Biomathematics
圖書(shū)封面Titlebook: Stochastic Problems in Population Genetics;  Takeo Maruyama Book 1977 Springer-Verlag Berlin Heidelberg 1977 Biomathematik.Derivation.Finit
描述These are" notes based on courses in Theoretical Population Genetics given at the University of Texas at Houston during the winter quarter, 1974, and at the University of Wisconsin during the fall semester, 1976. These notes explore problems of population genetics and evolution involving stochastic processes. Biological models and various mathematical techniques are discussed. Special emphasis is given to the diffusion method and an attempt is made to emphasize the underlying unity of various problems based on the Kolmogorov backward equation. A particular effort was made to make the subject accessible to biology students who are not familiar with stochastic processes. The references are not exhaustive but were chosen to provide a starting point for the reader interested in pursuing the subject further. Acknowledgement I would like to use this opportunity to express my thanks to Drs. J. F. Crow, M. Nei and W. J. Schull for their hospitality during my stays at their universities. I am indebted to Dr. M. Kimura for his continuous encouragement. My thanks also go to the small but resolute groups of.students, visitors and colleagues whose enthusiasm was a great source of encouragement.
出版日期Book 1977
關(guān)鍵詞Biomathematik; Derivation; Finite; Invariant; Markov process; Populationsgenetik; Stochastischer Prozess; e
版次1
doihttps://doi.org/10.1007/978-3-642-93065-2
isbn_softcover978-3-540-08349-8
isbn_ebook978-3-642-93065-2Series ISSN 0341-633X Series E-ISSN 2196-9981
issn_series 0341-633X
copyrightSpringer-Verlag Berlin Heidelberg 1977
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Geographical Structure of Populations,is N, every mutant is unique, the mutation rate is u, and all alleles are selectively neutral. The circularity of the population is for mathematical convenience, and analogous results hold for a linear case with two ends.
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Population Genetics Models,Consider a population consisting of 2N genes at a single locus (N diploid individuals) which are either A or a, where N is fixed number.
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Expectation of Integration Along Sample Paths,We have repeatedly emphasized the correspondence between a diffusion process and the appropriate KBE . where .with ..
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Approximation Methods,We shall mainly discuss perturbation methods which are often useful, particularly when a specific problem deviates only slightly from an analytically solvable case.
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Lecture Notes in Biomathematicshttp://image.papertrans.cn/s/image/878094.jpg
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https://doi.org/10.1007/978-3-642-93065-2Biomathematik; Derivation; Finite; Invariant; Markov process; Populationsgenetik; Stochastischer Prozess; e
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