Titlebook: Dynamic Data Analysis; Modeling Data with D James Ramsay,Giles Hooker Book 2017 Springer Science+Business Media LLC 2017 functional data an

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書目名稱Dynamic Data Analysis影響因子(影響力)




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書目名稱Dynamic Data Analysis網絡公開度學科排名




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書目名稱Dynamic Data Analysis被引頻次學科排名




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亞當心理陰影

Differential Equations: Notation and Architecture,used in subsequent chapters. Classifications of differential equations include linear versus nonlinear, homogeneous (no external input) and non-homogeneous or forced (with external input), single equations versus systems of equations, and first order equations and higher order equations. The exposit

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Linear Differential Equations and Systems, is useful from a modelling perspective. Linear differential equations do a great deal of the heavy lifting in many fields of application, including, for example, chemical engineering, electrical circuit theory, financial analysis, kinesiology and pharmacology. Stationary linear differential equatio

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https://doi.org/10.1007/978-3-531-19761-6change on the output side. Six examples are taken up, which will reappear later in the book. Each of these examples involve data spread out over the interval of change that will be used later to estimate parameters defining the differential equation. The introduction of vaccination for smallpox in M

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Sarah Alexi,Friederike Heinzel,Uta Mariniused in subsequent chapters. Classifications of differential equations include linear versus nonlinear, homogeneous (no external input) and non-homogeneous or forced (with external input), single equations versus systems of equations, and first order equations and higher order equations. The exposit

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Sarah Alexi,Friederike Heinzel,Uta Marini is useful from a modelling perspective. Linear differential equations do a great deal of the heavy lifting in many fields of application, including, for example, chemical engineering, electrical circuit theory, financial analysis, kinesiology and pharmacology. Stationary linear differential equatio

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https://doi.org/10.1007/978-3-531-19761-6ations must be approximated numerically. This chapter reviews two classes of numerical methods: Euler and Runge–Kutta methods that solve equations forwards in time starting from an initial value, and collocation methods which approximate solutions using a basis expansion. The chapter also discusses