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Model Description And Validation
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Book Synopsis Agent-Based Models in Economics by : Domenico Delli Gatti
Download or read book Agent-Based Models in Economics written by Domenico Delli Gatti and published by Cambridge University Press. This book was released on 2018-03-22 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first step-by-step introduction to the methodology of agent-based models in economics, their mathematical and statistical analysis, and real-world applications.
Book Synopsis Verification and Validation in Scientific Computing by : William L. Oberkampf
Download or read book Verification and Validation in Scientific Computing written by William L. Oberkampf and published by Cambridge University Press. This book was released on 2010-10-14 with total page 782 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in scientific computing have made modelling and simulation an important part of the decision-making process in engineering, science, and public policy. This book provides a comprehensive and systematic development of the basic concepts, principles, and procedures for verification and validation of models and simulations. The emphasis is placed on models that are described by partial differential and integral equations and the simulations that result from their numerical solution. The methods described can be applied to a wide range of technical fields, from the physical sciences, engineering and technology and industry, through to environmental regulations and safety, product and plant safety, financial investing, and governmental regulations. This book will be genuinely welcomed by researchers, practitioners, and decision makers in a broad range of fields, who seek to improve the credibility and reliability of simulation results. It will also be appropriate either for university courses or for independent study.
Book Synopsis Risk Model Validation by : Peter Quell
Download or read book Risk Model Validation written by Peter Quell and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Verification and Validation for Modeling and Simulation by : Jeffrey Strickland
Download or read book Verification and Validation for Modeling and Simulation written by Jeffrey Strickland and published by Lulu.com. This book was released on 2014-12-08 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work began when I was appointed as a Technical Director for Modeling and Simulation (M&S) Verification and Validation (V&V) for a major defense system in 2008. It is intended to provide the nuts and bolts of performing M&S V&V in one volume. It is not intended to provide a holistic approach to M&S V&V, as that can be derived from other sources. As such, this book assumes a basic understanding of V&V, including its place in the lifecycle, its purpose and its scope for ensuring the quality of models and simulations. During the process of developing this text, the Simulation Interoperability Standards Organization (SISO) completed SISO-GUIDE-001.2-2013, Guide for Generic Methodology for Verification and Validation (GM-VV) to Support Acceptance of Models, Simulations, and Data, 2 Volumes, June 2013. The guide does serve the purpose not covered by this book. This text provides procedural details for performing V&V. The procedures are static, dynamic and informal.
Book Synopsis Encyclopedia of Systems Biology by : Werner Dubitzky
Download or read book Encyclopedia of Systems Biology written by Werner Dubitzky and published by Springer. This book was released on 2013-08-17 with total page 2367 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systems biology refers to the quantitative analysis of the dynamic interactions among several components of a biological system and aims to understand the behavior of the system as a whole. Systems biology involves the development and application of systems theory concepts for the study of complex biological systems through iteration over mathematical modeling, computational simulation and biological experimentation. Systems biology could be viewed as a tool to increase our understanding of biological systems, to develop more directed experiments, and to allow accurate predictions. The Encyclopedia of Systems Biology is conceived as a comprehensive reference work covering all aspects of systems biology, in particular the investigation of living matter involving a tight coupling of biological experimentation, mathematical modeling and computational analysis and simulation. The main goal of the Encyclopedia is to provide a complete reference of established knowledge in systems biology – a ‘one-stop shop’ for someone seeking information on key concepts of systems biology. As a result, the Encyclopedia comprises a broad range of topics relevant in the context of systems biology. The audience targeted by the Encyclopedia includes researchers, developers, teachers, students and practitioners who are interested or working in the field of systems biology. Keeping in mind the varying needs of the potential readership, we have structured and presented the content in a way that is accessible to readers from wide range of backgrounds. In contrast to encyclopedic online resources, which often rely on the general public to author their content, a key consideration in the development of the Encyclopedia of Systems Biology was to have subject matter experts define the concepts and subjects of systems biology.
Book Synopsis Embedded System Design by : Peter Marwedel
Download or read book Embedded System Design written by Peter Marwedel and published by Springer Science & Business Media. This book was released on 2010-11-16 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Until the late 1980s, information processing was associated with large mainframe computers and huge tape drives. During the 1990s, this trend shifted toward information processing with personal computers, or PCs. The trend toward miniaturization continues and in the future the majority of information processing systems will be small mobile computers, many of which will be embedded into larger products and interfaced to the physical environment. Hence, these kinds of systems are called embedded systems. Embedded systems together with their physical environment are called cyber-physical systems. Examples include systems such as transportation and fabrication equipment. It is expected that the total market volume of embedded systems will be significantly larger than that of traditional information processing systems such as PCs and mainframes. Embedded systems share a number of common characteristics. For example, they must be dependable, efficient, meet real-time constraints and require customized user interfaces (instead of generic keyboard and mouse interfaces). Therefore, it makes sense to consider common principles of embedded system design. Embedded System Design starts with an introduction into the area and a survey of specification models and languages for embedded and cyber-physical systems. It provides a brief overview of hardware devices used for such systems and presents the essentials of system software for embedded systems, like real-time operating systems. The book also discusses evaluation and validation techniques for embedded systems. Furthermore, the book presents an overview of techniques for mapping applications to execution platforms. Due to the importance of resource efficiency, the book also contains a selected set of optimization techniques for embedded systems, including special compilation techniques. The book closes with a brief survey on testing. Embedded System Design can be used as a text book for courses on embedded systems and as a source which provides pointers to relevant material in the area for PhD students and teachers. It assumes a basic knowledge of information processing hardware and software. Courseware related to this book is available at http://ls12-www.cs.tu-dortmund.de/~marwedel.
Book Synopsis Secondary Analysis of Electronic Health Records by : MIT Critical Data
Download or read book Secondary Analysis of Electronic Health Records written by MIT Critical Data and published by Springer. This book was released on 2016-09-09 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.
Book Synopsis Spatial Microsimulation with R by : Robin Lovelace
Download or read book Spatial Microsimulation with R written by Robin Lovelace and published by CRC Press. This book was released on 2017-09-07 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generate and Analyze Multi-Level Data Spatial microsimulation involves the generation, analysis, and modeling of individual-level data allocated to geographical zones. Spatial Microsimulation with R is the first practical book to illustrate this approach in a modern statistical programming language. Get Insight into Complex Behaviors The book progresses from the principles underlying population synthesis toward more complex issues such as household allocation and using the results of spatial microsimulation for agent-based modeling. This equips you with the skills needed to apply the techniques to real-world situations. The book demonstrates methods for population synthesis by combining individual and geographically aggregated datasets using the recent R packages ipfp and mipfp. This approach represents the "best of both worlds" in terms of spatial resolution and person-level detail, overcoming issues of data confidentiality and reproducibility. Implement the Methods on Your Own Data Full of reproducible examples using code and data, the book is suitable for students and applied researchers in health, economics, transport, geography, and other fields that require individual-level data allocated to small geographic zones. By explaining how to use tools for modeling phenomena that vary over space, the book enhances your knowledge of complex systems and empowers you to provide evidence-based policy guidance.
Book Synopsis Concepts of Model Verification and Validation by : M. C. Anderson
Download or read book Concepts of Model Verification and Validation written by M. C. Anderson and published by . This book was released on 2004 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model verification and validation (V & V) is an enabling methodology for the development of computational models that can be used to make engineering predictions with quantified confidence. Model V & V procedures are needed by government and industry to reduce the time, cost, and risk associated with full-scale testing of products, materials, and weapon systems. Quantifying the confidence and predictive accuracy of model calculations provides the decision-maker with the information necessary for making high-consequence decisions. The development of guidelines and procedures for conducting a model V & V program are currently being defined by a broad spectrum of researchers. This report reviews the concepts involved in such a program. Model V & V is a current topic of great interest to both government and industry. In response to a ban on the production of new strategic weapons and nuclear testing, the Department of Energy (DOE) initiated the Science-Based Stockpile Stewardship Program (SSP). An objective of the SSP is to maintain a high level of confidence in the safety, reliability, and performance of the existing nuclear weapons stockpile in the absence of nuclear testing. This objective has challenged the national laboratories to develop high-confidence tools and methods that can be used to provide credible models needed for stockpile certification via numerical simulation. There has been a significant increase in activity recently to define V & V methods and procedures. The U.S. Department of Defense (DoD) Modeling and Simulation Office (DMSO) is working to develop fundamental concepts and terminology for V & V applied to high-level systems such as ballistic missile defense and battle management simulations. The American Society of Mechanical Engineers (ASME) has recently formed a Standards Committee for the development of V & V procedures for computational solid mechanics models. The Defense Nuclear Facilities Safety Board (DNFSB) has been a proponent of model V & V for all safety-related nuclear facility design, analyses, and operations. In fact, DNFSB 2002-1 recommends to the DOE and National Nuclear Security Administration (NNSA) that a V & V process be performed for all safety related software and analysis. Model verification and validation are the primary processes for quantifying and building credibility in numerical models. Verification is the process of determining that a model implementation accurately represents the developer's conceptual description of the model and its solution. Validation is the process of determining the degree to which a model is an accurate representation of the real world from the perspective of the intended uses of the model. Both verification and validation are processes that accumulate evidence of a model's correctness or accuracy for a specific scenario; thus, V & V cannot prove that a model is correct and accurate for all possible scenarios, but, rather, it can provide evidence that the model is sufficiently accurate for its intended use. Model V & V is fundamentally different from software V & V. Code developers developing computer programs perform software V & V to ensure code correctness, reliability, and robustness. In model V & V, the end product is a predictive model based on fundamental physics of the problem being solved. In all applications of practical interest, the calculations involved in obtaining solutions with the model require a computer code, e.g., finite element or finite difference analysis. Therefore, engineers seeking to develop credible predictive models critically need model V & V guidelines and procedures. The expected outcome of the model V & V process is the quantified level of agreement between experimental data and model prediction, as well as the predictive accuracy of the model. This report attempts to describe the general philosophy, definitions, concepts, and processes for conducting a successful V & V program. This objective is motivated by the need for highly accurate numerical models for making predictions to support the SSP, and also by the lack of guidelines, standards and procedures for performing V & V for complex numerical models.
Book Synopsis On Standardized Model Integration by : Robert Hällqvist
Download or read book On Standardized Model Integration written by Robert Hällqvist and published by Linköping University Electronic Press. This book was released on 2019-12-20 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designing modern aircraft is not an easy task. Today, it is not enough to optimize aircraft sub-systems at a sub-system level. Instead, a holistic approach is taken whereby the constituent sub-systems need to be designed for the best joint performance. The State-of-the-Art (SotA) in simulating and exchanging simulation models is moving forward at a fast pace. As such, the feasible use of simulation models has increased and additional benefits can be exploited, such as analysing coupled sub-systems in simulators. Furthermore, if aircraft sub-system simulation models are to be utilized to their fullest extent, opensource tooling and the use of open standards, interoperability between domain specific modeling tools, alongside robust and automated processes for model Verification and Validation (V&V) are required. The financial and safety related risks associated with aircraft development and operation require well founded design and operational decisions. If those decisions are to be founded upon information provided by models and simulators, then the credibility of that information needs to be assessed and communicated. Today, the large number of sensors available in modern aircraft enable model validation and credibility assessment on a different scale than what has been possible up to this point. This thesis aims to identify and address challenges to allow for automated, independent, and objective methods of integrating sub-system models into simulators while assessing and conveying the constituent models aggregated credibility. The results of the work include a proposed method for presenting the individual models’ aggregated credibility in a simulator. As the communicated credibility of simulators here relies on the credibility of each included model, the assembly procedure itself cannot introduce unknown discrepancies with respect to the System of Interest (SoI). Available methods for the accurate simulation of coupled models are therefore exploited and tailored to the applications of aircraft development under consideration. Finally, a framework for automated model validation is outlined, supporting on-line simulator credibility assessment according to the presented proposed method.
Book Synopsis Model Validation by : Malcolm G. Anderson
Download or read book Model Validation written by Malcolm G. Anderson and published by John Wiley & Sons. This book was released on 2001-06-11 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: Validation is a central issue to future model design in environmental science. This book is the first to provide a critical appraisal of today's validation needs, capabilities, and required changes in philosophy. It takes examples from four different scales: hillslope and river channel, catchment, regional, and global. This timely book offers unique, multifaceted coverage of model validation in hydrological science today. Topics covered include calibration procedures, data assimilation, scaling, critical future need in validation, and evidence of field data. * State-of-the-art research book on an important new topic * End-of-section discussion chapters written by leading international researchers
Book Synopsis Testing and Validation of Computer Simulation Models by : David J. Murray-Smith
Download or read book Testing and Validation of Computer Simulation Models written by David J. Murray-Smith and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This must-read text/reference provides a practical guide to processes involved in the development and application of dynamic simulation models, covering a wide range of issues relating to testing, verification and validation. Illustrative example problems in continuous system simulation are presented throughout the book, supported by extended case studies from a number of interdisciplinary applications. Topics and features: Provides an emphasis on practical issues of model quality and validation, along with questions concerning the management of simulation models, the use of model libraries, and generic models Contains numerous step-by-step examples Presents detailed case studies, often with accompanying datasets for readers to use in model validation and testing exercises Includes discussion of hybrid models, which involve a combination of continuous system and discrete-event descriptions Examines experimental modeling approaches that involve system identification and parameter estimation, emphasizing the practical importance of more theoretical concepts such as identifiability and test input design Offers supplementary material at an associated website, including links for readers without prior experience in this field to expand their background knowledge This highly useful, hands-on work will be of great benefit to practitioners and professionals who use simulation and modeling techniques in their work, as well as to students in graduate-level courses on modeling and simulation. Dr. David Murray-Smith is an Emeritus Professor and Honorary Senior Research Fellow at the University of Glasgow.
Book Synopsis Design and Development Research by : Rita C. Richey
Download or read book Design and Development Research written by Rita C. Richey and published by Routledge. This book was released on 2014-07-16 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: AECT Design & Development Outstanding Book Award for 2008! Design and Development Research thoroughly discusses methods and strategies appropriate for conducting design and development research. Rich with examples and explanations, the book describes actual strategies that researchers have used to conduct two major types of design and development research: 1) product and tool research and 2) model research. Common challenges confronted by researchers in the field when planning and conducting a study are explored and procedural explanations are supported by a wide variety of examples taken from current literature. Samples of actual research tools are also presented. Important features in this volume include: concise checklists at the end of each chapter to give a clear summary of the steps involved in the various phases of a project; an examination of the critical types of information and data often gathered in studies, and unique procedures for collecting these data; examples of data collection instruments, as well as the use of technology in data collection; and a discussion of the process of extracting meaning from data and interpreting product and tool and model research findings. Design and Development Research is appropriate for both experienced researchers and those preparing to become researchers. It is intended for scholars interested in planning and conducting design and development research, and is intended to stimulate future thinking about methods, strategies, and issues related to the field.
Book Synopsis Computer Simulation Validation by : Claus Beisbart
Download or read book Computer Simulation Validation written by Claus Beisbart and published by Springer. This book was released on 2019-04-09 with total page 1074 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique volume introduces and discusses the methods of validating computer simulations in scientific research. The core concepts, strategies, and techniques of validation are explained by an international team of pre-eminent authorities, drawing on expertise from various fields ranging from engineering and the physical sciences to the social sciences and history. The work also offers new and original philosophical perspectives on the validation of simulations. Topics and features: introduces the fundamental concepts and principles related to the validation of computer simulations, and examines philosophical frameworks for thinking about validation; provides an overview of the various strategies and techniques available for validating simulations, as well as the preparatory steps that have to be taken prior to validation; describes commonly used reference points and mathematical frameworks applicable to simulation validation; reviews the legal prescriptions, and the administrative and procedural activities related to simulation validation; presents examples of best practice that demonstrate how methods of validation are applied in various disciplines and with different types of simulation models; covers important practical challenges faced by simulation scientists when applying validation methods and techniques; offers a selection of general philosophical reflections that explore the significance of validation from a broader perspective. This truly interdisciplinary handbook will appeal to a broad audience, from professional scientists spanning all natural and social sciences, to young scholars new to research with computer simulations. Philosophers of science, and methodologists seeking to increase their understanding of simulation validation, will also find much to benefit from in the text.
Book Synopsis Identifying the Information Space of a Model by : Hubert (Hubert M.) Lipinski
Download or read book Identifying the Information Space of a Model written by Hubert (Hubert M.) Lipinski and published by . This book was released on 1977 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Analytics of Risk Model Validation by : George A. Christodoulakis
Download or read book The Analytics of Risk Model Validation written by George A. Christodoulakis and published by Elsevier. This book was released on 2007-11-14 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Risk model validation is an emerging and important area of research, and has arisen because of Basel I and II. These regulatory initiatives require trading institutions and lending institutions to compute their reserve capital in a highly analytic way, based on the use of internal risk models. It is part of the regulatory structure that these risk models be validated both internally and externally, and there is a great shortage of information as to best practise. Editors Christodoulakis and Satchell collect papers that are beginning to appear by regulators, consultants, and academics, to provide the first collection that focuses on the quantitative side of model validation. The book covers the three main areas of risk: Credit Risk and Market and Operational Risk. *Risk model validation is a requirement of Basel I and II *The first collection of papers in this new and developing area of research *International authors cover model validation in credit, market, and operational risk
Book Synopsis Clinical Prediction Models by : Ewout W. Steyerberg
Download or read book Clinical Prediction Models written by Ewout W. Steyerberg and published by Springer. This book was released on 2019-07-22 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of this volume provides insight and practical illustrations on how modern statistical concepts and regression methods can be applied in medical prediction problems, including diagnostic and prognostic outcomes. Many advances have been made in statistical approaches towards outcome prediction, but a sensible strategy is needed for model development, validation, and updating, such that prediction models can better support medical practice. There is an increasing need for personalized evidence-based medicine that uses an individualized approach to medical decision-making. In this Big Data era, there is expanded access to large volumes of routinely collected data and an increased number of applications for prediction models, such as targeted early detection of disease and individualized approaches to diagnostic testing and treatment. Clinical Prediction Models presents a practical checklist that needs to be considered for development of a valid prediction model. Steps include preliminary considerations such as dealing with missing values; coding of predictors; selection of main effects and interactions for a multivariable model; estimation of model parameters with shrinkage methods and incorporation of external data; evaluation of performance and usefulness; internal validation; and presentation formatting. The text also addresses common issues that make prediction models suboptimal, such as small sample sizes, exaggerated claims, and poor generalizability. The text is primarily intended for clinical epidemiologists and biostatisticians. Including many case studies and publicly available R code and data sets, the book is also appropriate as a textbook for a graduate course on predictive modeling in diagnosis and prognosis. While practical in nature, the book also provides a philosophical perspective on data analysis in medicine that goes beyond predictive modeling. Updates to this new and expanded edition include: • A discussion of Big Data and its implications for the design of prediction models • Machine learning issues • More simulations with missing ‘y’ values • Extended discussion on between-cohort heterogeneity • Description of ShinyApp • Updated LASSO illustration • New case studies
