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Population dynamics based on individ...
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Oizumi, Ryo.
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Population dynamics based on individual stochasticity
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Population dynamics based on individual stochasticity/ by Ryo Oizumi.
作者:
Oizumi, Ryo.
出版者:
Singapore :Springer Nature Singapore : : 2022.,
面頁冊數:
x, 101 p. :ill., digital ;24 cm.
內容註:
Introduction : Stochasticity in Demography -- 1. Deterministic and Stochastic Population Models -- 2. Linear Structured Population based on SDE -- 3. Nonlinear Structured Population Models -- 4. Life-History Evolution and Adaptive Stochastic Controls -- 5 Application to External Stochasticity -- Epilogue: Population Dynamics from Perspective of Individual Diversity.
Contained By:
Springer Nature eBook
標題:
Stochastic analysis. -
標題:
Japan - Population. -
電子資源:
https://doi.org/10.1007/978-981-19-3548-0
ISBN:
9789811935480
Population dynamics based on individual stochasticity
Oizumi, Ryo.
Population dynamics based on individual stochasticity
[electronic resource] /by Ryo Oizumi. - Singapore :Springer Nature Singapore :2022. - x, 101 p. :ill., digital ;24 cm. - Population studies of Japan,2198-2732. - Population studies of Japan..
Introduction : Stochasticity in Demography -- 1. Deterministic and Stochastic Population Models -- 2. Linear Structured Population based on SDE -- 3. Nonlinear Structured Population Models -- 4. Life-History Evolution and Adaptive Stochastic Controls -- 5 Application to External Stochasticity -- Epilogue: Population Dynamics from Perspective of Individual Diversity.
This book demonstrates that population structure and dynamics can be reconstructed by stochastic analysis. Population projection is usually based on age-structured population models. These models consist of age-dependent fertility and mortality, whereas birth and death processes generally arise from states of individuals. For example, a number of seeds are proportional to tree size, and amount of income and savings are the basis of decision making for birth behavior in human beings. Thus, even though individuals belong to an identical cohort, they have different fertility and mortality. To treat this kind of individual heterogeneity, stochastic state transitions are reasonable rather than the deterministic states. This book extends deterministic systems to stochastic systems specifically, constructing a state transition model represented by stochastic differential equations. The diffusion process generated by stochastic differential equations provides statistics determining population dynamics, i.e., heterogeneity is incorporated in population dynamics as its statistics. Applying this perspective to demography and evolutionary biology, we can consider the role of heterogeneity in life history or evolution. These concepts are provided to readers with explanations of stochastic analysis.
ISBN: 9789811935480
Standard No.: 10.1007/978-981-19-3548-0doiSubjects--Topical Terms:
533923
Stochastic analysis.
Subjects--Geographical Terms:
761036
Japan
--Population.
LC Class. No.: HB3651
Dewey Class. No.: 304.60952
Population dynamics based on individual stochasticity
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Introduction : Stochasticity in Demography -- 1. Deterministic and Stochastic Population Models -- 2. Linear Structured Population based on SDE -- 3. Nonlinear Structured Population Models -- 4. Life-History Evolution and Adaptive Stochastic Controls -- 5 Application to External Stochasticity -- Epilogue: Population Dynamics from Perspective of Individual Diversity.
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This book demonstrates that population structure and dynamics can be reconstructed by stochastic analysis. Population projection is usually based on age-structured population models. These models consist of age-dependent fertility and mortality, whereas birth and death processes generally arise from states of individuals. For example, a number of seeds are proportional to tree size, and amount of income and savings are the basis of decision making for birth behavior in human beings. Thus, even though individuals belong to an identical cohort, they have different fertility and mortality. To treat this kind of individual heterogeneity, stochastic state transitions are reasonable rather than the deterministic states. This book extends deterministic systems to stochastic systems specifically, constructing a state transition model represented by stochastic differential equations. The diffusion process generated by stochastic differential equations provides statistics determining population dynamics, i.e., heterogeneity is incorporated in population dynamics as its statistics. Applying this perspective to demography and evolutionary biology, we can consider the role of heterogeneity in life history or evolution. These concepts are provided to readers with explanations of stochastic analysis.
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