Dynamic Models in Biology

Dynamic Models in Biology PDF Author: Stephen P. Ellner
Publisher: Princeton University Press
ISBN: 1400840961
Category : Science
Languages : en
Pages : 352

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Book Description
From controlling disease outbreaks to predicting heart attacks, dynamic models are increasingly crucial for understanding biological processes. Many universities are starting undergraduate programs in computational biology to introduce students to this rapidly growing field. In Dynamic Models in Biology, the first text on dynamic models specifically written for undergraduate students in the biological sciences, ecologist Stephen Ellner and mathematician John Guckenheimer teach students how to understand, build, and use dynamic models in biology. Developed from a course taught by Ellner and Guckenheimer at Cornell University, the book is organized around biological applications, with mathematics and computing developed through case studies at the molecular, cellular, and population levels. The authors cover both simple analytic models--the sort usually found in mathematical biology texts--and the complex computational models now used by both biologists and mathematicians. Linked to a Web site with computer-lab materials and exercises, Dynamic Models in Biology is a major new introduction to dynamic models for students in the biological sciences, mathematics, and engineering.

Dynamic Models in Biology

Dynamic Models in Biology PDF Author: Stephen P. Ellner
Publisher: Princeton University Press
ISBN: 1400840961
Category : Science
Languages : en
Pages : 352

Get Book

Book Description
From controlling disease outbreaks to predicting heart attacks, dynamic models are increasingly crucial for understanding biological processes. Many universities are starting undergraduate programs in computational biology to introduce students to this rapidly growing field. In Dynamic Models in Biology, the first text on dynamic models specifically written for undergraduate students in the biological sciences, ecologist Stephen Ellner and mathematician John Guckenheimer teach students how to understand, build, and use dynamic models in biology. Developed from a course taught by Ellner and Guckenheimer at Cornell University, the book is organized around biological applications, with mathematics and computing developed through case studies at the molecular, cellular, and population levels. The authors cover both simple analytic models--the sort usually found in mathematical biology texts--and the complex computational models now used by both biologists and mathematicians. Linked to a Web site with computer-lab materials and exercises, Dynamic Models in Biology is a major new introduction to dynamic models for students in the biological sciences, mathematics, and engineering.

Topics in Dynamic Model Analysis

Topics in Dynamic Model Analysis PDF Author: Mario Faliva
Publisher: Springer Science & Business Media
ISBN: 354029239X
Category : Business & Economics
Languages : en
Pages : 152

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Book Description
Classical econometrics - which plunges its roots in economic theory with simultaneous equations models (SEM) as offshoots - and time series econometrics - which stems from economic data with vector autoregr- sive (VAR) models as offsprings - scour, like the Janus's facing heads, the flowing of economic variables so as to bring to the fore their autonomous and non-autonomous dynamics. It is up to the so-called final form of a dy namic SEM, on the one hand, and to the so-called representation theorems of (unit-root) VAR models, on the other, to provide informative closed form expressions for the trajectories, or time paths, of the economic vari ables of interest. Should we look at the issues just put forward from a mathematical standpoint, the emblematic models of both classical and time series econometrics would turn out to be difference equation systems with ad hoc characteristics, whose solutions are attained via a final form or a represen tation theorem approach. The final form solution - algebraic technicalities apart - arises in the wake of classical difference equation theory, display ing besides a transitory autonomous component, an exogenous one along with a stochastic nuisance term. This follows from a properly defined ma trix function inversion admitting a Taylor expansion in the lag operator be cause of the assumptions regarding the roots of a determinant equation pe culiar to SEM specifications.

Dynamic Modeling and Applications for Global Economic Analysis

Dynamic Modeling and Applications for Global Economic Analysis PDF Author: Elena Ianchovichina
Publisher: Cambridge University Press
ISBN: 1107011698
Category : Business & Economics
Languages : en
Pages : 449

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Book Description
This book presents the technical aspects of an economic model used to examine issues of global economic significance, such as the impact on the world economy of changes in trade and environmental policy. The book provides a number of studies using the model to examine trade reform, growth and investment, climate change, natural resources, technology, and demographic change and migration.

Analytical Methods for Dynamic Modelers

Analytical Methods for Dynamic Modelers PDF Author: Hazhir Rahmandad
Publisher: MIT Press
ISBN: 0262331438
Category : Business & Economics
Languages : en
Pages : 443

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Book Description
A user-friendly introduction to some of the most useful analytical tools for model building, estimation, and analysis, presenting key methods and examples. Simulation modeling is increasingly integrated into research and policy analysis of complex sociotechnical systems in a variety of domains. Model-based analysis and policy design inform a range of applications in fields from economics to engineering to health care. This book offers a hands-on introduction to key analytical methods for dynamic modeling. Bringing together tools and methodologies from fields as diverse as computational statistics, econometrics, and operations research in a single text, the book can be used for graduate-level courses and as a reference for dynamic modelers who want to expand their methodological toolbox. The focus is on quantitative techniques for use by dynamic modelers during model construction and analysis, and the material presented is accessible to readers with a background in college-level calculus and statistics. Each chapter describes a key method, presenting an introduction that emphasizes the basic intuition behind each method, tutorial style examples, references to key literature, and exercises. The chapter authors are all experts in the tools and methods they present. The book covers estimation of model parameters using quantitative data; understanding the links between model structure and its behavior; and decision support and optimization. An online appendix offers computer code for applications, models, and solutions to exercises. Contributors Wenyi An, Edward G. Anderson Jr., Yaman Barlas, Nishesh Chalise, Robert Eberlein, Hamed Ghoddusi, Winfried Grassmann, Peter S. Hovmand, Mohammad S. Jalali, Nitin Joglekar, David Keith, Juxin Liu, Erling Moxnes, Rogelio Oliva, Nathaniel D. Osgood, Hazhir Rahmandad, Raymond Spiteri, John Sterman, Jeroen Struben, Burcu Tan, Karen Yee, Gönenç Yücel

Dynamic Data Analysis

Dynamic Data Analysis PDF Author: James Ramsay
Publisher: Springer
ISBN: 1493971905
Category : Mathematics
Languages : en
Pages : 230

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Book Description
This text focuses on the use of smoothing methods for developing and estimating differential equations following recent developments in functional data analysis and building on techniques described in Ramsay and Silverman (2005) Functional Data Analysis. The central concept of a dynamical system as a buffer that translates sudden changes in input into smooth controlled output responses has led to applications of previously analyzed data, opening up entirely new opportunities for dynamical systems. The technical level has been kept low so that those with little or no exposure to differential equations as modeling objects can be brought into this data analysis landscape. There are already many texts on the mathematical properties of ordinary differential equations, or dynamic models, and there is a large literature distributed over many fields on models for real world processes consisting of differential equations. However, a researcher interested in fitting such a model to data, or a statistician interested in the properties of differential equations estimated from data will find rather less to work with. This book fills that gap.

Dynamic Analysis of Structures

Dynamic Analysis of Structures PDF Author: John T. Katsikadelis
Publisher: Academic Press
ISBN: 0128186445
Category : Technology & Engineering
Languages : en
Pages : 808

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Book Description
Dynamic Analysis of Structures reflects the latest application of structural dynamics theory to produce more optimal and economical structural designs. Written by an author with over 37 years of researching, teaching and writing experience, this reference introduces complex structural dynamics concepts in a user-friendly manner. The author includes carefully worked-out examples which are solved utilizing more recent numerical methods. These examples pave the way to more accurately simulate the behavior of various types of structures. The essential topics covered include principles of structural dynamics applied to particles, rigid and deformable bodies, thus enabling the formulation of equations for the motion of any structure. Covers the tools and techniques needed to build realistic modeling of actual structures under dynamic loads Provides the methods to formulate the equations of motion of any structure, no matter how complex it is, once the dynamic model has been adopted Provides carefully worked-out examples that are solved using recent numerical methods Includes simple computer algorithms for the numerical solution of the equations of motion and respective code in FORTRAN and MATLAB

Bayesian Forecasting and Dynamic Models

Bayesian Forecasting and Dynamic Models PDF Author: Mike West
Publisher: Springer Science & Business Media
ISBN: 1475793650
Category : Mathematics
Languages : en
Pages : 720

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Book Description
In this book we are concerned with Bayesian learning and forecast ing in dynamic environments. We describe the structure and theory of classes of dynamic models, and their uses in Bayesian forecasting. The principles, models and methods of Bayesian forecasting have been developed extensively during the last twenty years. This devel opment has involved thorough investigation of mathematical and sta tistical aspects of forecasting models and related techniques. With this has come experience with application in a variety of areas in commercial and industrial, scientific and socio-economic fields. In deed much of the technical development has been driven by the needs of forecasting practitioners. As a result, there now exists a relatively complete statistical and mathematical framework, although much of this is either not properly documented or not easily accessible. Our primary goals in writing this book have been to present our view of this approach to modelling and forecasting, and to provide a rea sonably complete text for advanced university students and research workers. The text is primarily intended for advanced undergraduate and postgraduate students in statistics and mathematics. In line with this objective we present thorough discussion of mathematical and statistical features of Bayesian analyses of dynamic models, with illustrations, examples and exercises in each Chapter.

System Dynamics Modeling with R

System Dynamics Modeling with R PDF Author: Jim Duggan
Publisher: Springer
ISBN: 3319340433
Category : Computers
Languages : en
Pages : 176

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Book Description
This new interdisciplinary work presents system dynamics as a powerful approach to enable analysts build simulation models of social systems, with a view toward enhancing decision making. Grounded in the feedback perspective of complex systems, the book provides a practical introduction to system dynamics, and covers key concepts such as stocks, flows, and feedback. Societal challenges such as predicting the impact of an emerging infectious disease, estimating population growth, and assessing the capacity of health services to cope with demographic change can all benefit from the application of computer simulation. This text explains important building blocks of the system dynamics approach, including material delays, stock management heuristics, and how to model effects between different systemic elements. Models from epidemiology, health systems, and economics are presented to illuminate important ideas, and the R programming language is used to provide an open-source and interoperable way to build system dynamics models. System Dynamics Modeling with R also describes hands-on techniques that can enhance client confidence in system dynamic models, including model testing, model analysis, and calibration. Developed from the author’s course in system dynamics, this book is written for undergraduate and postgraduate students of management, operations research, computer science, and applied mathematics. Its focus is on the fundamental building blocks of system dynamics models, and its choice of R as a modeling language make it an ideal reference text for those wishing to integrate system dynamics modeling with related data analytic methods and techniques.

Topics in Modal Analysis II, Volume 6

Topics in Modal Analysis II, Volume 6 PDF Author: R. Allemang
Publisher: Springer Science & Business Media
ISBN: 1461424194
Category : Technology & Engineering
Languages : en
Pages : 652

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Book Description
Topics in Modal Analysis II, Volume 6: Proceedings of the 30th IMAC, A Conference and Exposition on Structural Dynamics, 2012, is the sixth volume of six from the Conference and brings together 65 contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: Aerospace, Acoustics, Energy Harvesting, Shock and Vibration, Finite Element, Structural Health Monitoring, Biodynamics Experimental Techniques, Damage Detection, Rotating Machinery, Sports Equipment Dynamics, Aircraft/Aerospace.

Dynamic Modeling for Business Management

Dynamic Modeling for Business Management PDF Author: Bernard McGarvey
Publisher: Springer Science & Business Media
ISBN: 0387215565
Category : Mathematics
Languages : en
Pages : 320

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Book Description
Modelling is a tool used by savvy business managers to understand the processes of their business and to estimate the impact of changes. Dynamic Modelling for Business Management applies dynamic modelling to business management, using accessible modelling techniques that are demonstrated starting with fundamental processes and advancing to more complex business models. Discussions of modelling emphasize its practical use for decision making and implementing change for measurable results. Readers will learn about both manufacturing and service-oriented business processes using hands-on lessons. Then will then be able to manipulate additional models to try out their knowledge and address issues specific to their own businesses and interests. Some of the topics covered include workflow management, supply-chain-management, and strategy.