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Handbook of Product Graphs (Discrete Mathematics and Its Applications)
by null Richard Hammack null Wilfried Imrich null Sandi KlavžarThis handbook examines the dichotomy between the structure of products and their subgraphs. It also features the design of efficient algorithms that recognize products and their subgraphs and explores the relationship between graph parameters of the product and factors. Extensively revised and expanded, this second edition presents full proofs of many important results as well as up-to-date research and conjectures. It illustrates applications of graph products in several areas and contains well over 300 exercises. Supplementary material is available on the book's website.
A Handbook of Public Speaking for Scientists and Engineers
by Peter KennyA Handbook of Public Speaking for Scientists and Engineers helps scientists and engineers improve their skills at speaking in public in the course of their professional activities. The book shows how best to prepare papers for presentation at a technical conference and how to put cases to committee meetings. Not only does the book deal with specific events, but it also provides the techniques of more effective speaking, whether presenting papers, answering questions, or speaking "off-the-cuff." The book is written in a highly entertaining manner and should put all complacent lecturers on their guard.
Handbook of Quantitative Criminology
by Alex R. Piquero David WeisburdThe "Handbook of Quantitative Criminology" is designed to be the authoritative volume on methodological and statistical issues in the criminology/criminal justice field. Like handbooks available in other disciplines (economics, psychology, sociology), this book will be the go-to book for new and advanced methods in the field that will provide overviews of the issues, with examples and figures as warranted, for students, faculty, and researchers alike. Authored by leading scholars in criminology/criminal justice, the Handbook contains 24 chapters on topics in the following key areas: (1) research design, (2) experimental methods, (3) methods for overcoming data limitations, (4) innovative descriptive methods, (5) estimation techniques for theory and policy, (6) topics in multiple regression, and (7) new directions in statistical analysis.
Handbook of Quantitative Ecology
by Justin KitzesAn essential guide to quantitative research methods in ecology and conservation biology, accessible for even the most math-averse student or professional. Quantitative research techniques have become increasingly important in ecology and conservation biology, but the sheer breadth of methods that must be understood—from population modeling and probabilistic thinking to modern statistics, simulation, and data science—and a lack of computational or mathematics training have hindered quantitative literacy in these fields. In this book, ecologist Justin Kitzes addresses those challenges for students and practicing scientists alike. Requiring only basic algebra and the ability to use a spreadsheet, Handbook of Quantitative Ecology is designed to provide a practical, intuitive, and integrated introduction to widely used quantitative methods. Kitzes builds each chapter around a specific ecological problem and arrives, step by step, at a general principle through the process of solving that problem. Grouped into five broad categories—difference equations, probability, matrix models, likelihood statistics, and other numerical methods—the book introduces basic concepts, starting with exponential and logistic growth, and helps readers to understand the field’s more advanced subjects, such as bootstrapping, stochastic optimization, and cellular automata. Complete with online solutions to all numerical problems, Kitzes’s Handbook of Quantitative Ecology is an ideal coursebook for both undergraduate and graduate students of ecology, as well as a useful and necessary resource for mathematically out-of-practice scientists.
Handbook of Quantitative Finance and Risk Management
by John Lee Cheng-Few LeeQuantitative finance is a combination of economics, accounting, statistics, econometrics, mathematics, stochastic process, and computer science and technology. Increasingly, the tools of financial analysis are being applied to assess, monitor, and mitigate risk, especially in the context of globalization, market volatility, and economic crisis. This two-volume handbook, comprised of over 100 chapters, is the most comprehensive resource in the field to date, integrating the most current theory, methodology, policy, and practical applications. Showcasing contributions from an international array of experts, the Handbook of Quantitative Finance and Risk Management is unparalleled in the breadth and depth of its coverage. Volume 1 presents an overview of quantitative finance and risk management research, covering the essential theories, policies, and empirical methodologies used in the field. Chapters provide in-depth discussion of portfolio theory and investment analysis. Volume 2 covers options and option pricing theory and risk management. Volume 3 presents a wide variety of models and analytical tools. Throughout, the handbook offers illustrative case examples, worked equations, and extensive references; additional features include chapter abstracts, keywords, and author and subject indices. From "arbitrage" to "yield spreads," the Handbook of Quantitative Finance and Risk Management will serve as an essential resource for academics, educators, students, policymakers, and practitioners.
Handbook of Quantum Gravity
by Cosimo Bambi Leonardo Modesto Ilya ShapiroThe search for a theory of quantum gravity is one of the most important and fascinating problems in modern theoretical physics. While we do not have yet a complete theory of quantum gravity, significant advancements have been done in the past decades. In this handbook, every section is dedicated to a specific approach towards a theory of quantum gravity and is edited by the leading experts in the field. This book represents both a valuable resource for graduate students and an important reference for researchers in quantum gravity.
Handbook of Radar Signal Analysis (Advances in Applied Mathematics)
by Bassem R. MahafzaThis new handbook on radar signal analysis adopts a deliberate and systematic approach. It uses a clear and consistent level of delivery while maintaining strong and easy-to-follow mathematical details. The emphasis of this book is on radar signal types and their relevant signal processing and not on radar systems hardware or components. This handbook serves as a valuable reference to a wide range of audience. More specifically, college-level students, practicing radar engineers, as well as casual readers of the subject are the intended target audience of the first few chapters of this book. As the book chapters progress, these grow in complexity and specificity. Accordingly, later chapters are intended for practicing engineers, graduate college students, and advanced readers. Finally, the last few chapters contain several special topics on radar systems that are both educational and scientifically entertaining to all readers. The presentation of topics in this handbook takes the reader on a scientific journey whose major landmarks comprise the different radar subsystems and components. In this context, the chapters follow the radar signal along this journey from its birth to the end of its life. Along the way, the different relevant radar subsystems are analyzed and discussed in great detail. The chapter contributors of this new handbook comprise experienced academia members and practicing radar engineers. Their combined years of academic and real-world experiences are in excess of 175. Together, they bring a unique, easy-to-follow mix of mathematical and practical presentations of the topics discussed in this book. See the "Chapter Contributors" section to learn more about these individuals.
Handbook of Ratings
by Alexander Karminsky Andrey PolozovThis handbook presents a systematic overview of approaches to, diversity, and problems involved in interdisciplinary rating methodologies. Historically, the purpose of ratings is to achieve information transparency regarding a given body's activities, whether in the field of finance, banking, or sports for example. This book focuses on commonly used rating methods in three important fields: finance, sports, and the social sector. In the world of finance, investment decisions are largely shaped by how positively or negatively economies or financial instruments are rated. Ratings have thus become a basis of trust for investors. Similarly, sports evaluation and funding are largely based on core ratings. From local communities to groups of nations, public investment and funding are also dependent on how these bodies are continuously rated against expected performance targets. As such, ratings need to reflect the consensus of all stakeholders on selected aspects of the work and how to evaluate their success. The public should also have the opportunity to participate in this process. The authors examine current rating approaches from a variety of proposals that are closest to the public consensus, analyzing the rating models and summarizing the methods of their construction. This handbook offers a valuable reference guide for managers, analysts, economists, business informatics specialists, and researchers alike.
Handbook of Real-Time and Embedded Systems (Chapman & Hall/CRC Computer and Information Science Series)
by Insup Lee Joseph Y-T. Leung Sang H. SonReal-time and embedded systems are essential to our lives, from controlling car engines and regulating traffic lights to monitoring plane takeoffs and landings to providing up-to-the-minute stock quotes. Bringing together researchers from both academia and industry, the Handbook of Real-Time and Embedded Systems provides comprehensive covera
Handbook of Real-World Applications in Modeling and Simulation
by Catherine M. Banks John A. SokolowskiIntroduces various modeling and simulation methods and paradigms that are used to explain and solve the predominant challenges facing societyHandbook of Real-World Applications in Modeling and Simulation provides a thorough explanation of modeling and simulation in the most useful, current, and predominant applied areas of transportation, homeland security, medicine, operational research, military science, and business modeling. Offering a cutting-edge and accessible presentation, this book discusses how and why the presented domains have become leading applications of modeling and simulation techniques.Contributions from leading academics and researchers integrate modeling and simulation theories, methods, and data to analyze challenges that involve technological and social issues. The book begins with an introduction that explains why modeling and simulation is a reliable analysis assessment tool for complex systems problems. Subsequent chapters provide an orientation to various modeling and simulation methods and paradigms that are used to explain and solve the predominant challenges across real-world applied domains. Additionally, the handbook:Provides a practical one-stop reference on modeling and simulation and contains an accessible introduction to key concepts and techniquesIntroduces, trains, and prepares readers from statistics, mathematics, engineering, computer science, economics, and business to use modeling and simulation in their studies and researchFeatures case studies that are representative of fundamental areas of multidisciplinary studies and provides a concise look at the key concepts of modeling and simulationContains a collection of original ideas on modeling and simulation to help academics and practitioners develop a multifunctional perspectiveSelf-contained chapters offer a comprehensive approach to explaining each respective domain and include sections that explore the related history, theory, modeling paradigms, and case studies. Key terms and techniques are clearly outlined, and exercise sets allow readers to test their comprehension of the presented material.Handbook of Real-World Applications in Modeling and Simulation is an essential reference for academics and practitioners in the areas of operations research, business, management science, engineering, statistics, mathematics, and computer science. The handbook is also a suitable supplement for courses on modeling and simulation at the graduate level.
Handbook of Regional Science
by Manfred M. Fischer Peter NijkampThe Handbook of Regional Science is a multi-volume reference work providing a state-of-the-art knowledge on regional science composed by renowned scientists in the field. The Handbook is intended to serve the academic needs of graduate students, and junior and senior scientists in regional science and related fields, with an interest in studying local and regional socio-economic issues. The multi-volume handbook seeks to cover the field of regional science comprehensively, including areas such as regional housing and labor markets, regional economic growth, innovation and regional economic development, new and evolutionary economic geography, location and interaction, the environment and natural resources, spatial analysis and geo-computation as well as spatial statistics and econometrics.
Handbook of Regression Analysis
by Samprit Chatterjee Jeffrey S. SimonoffA Comprehensive Account for Data Analysts of the Methods and Applications of Regression Analysis. Written by two established experts in the field, the purpose of the Handbook of Regression Analysis is to provide a practical, one-stop reference on regression analysis. The focus is on the tools that both practitioners and researchers use in real life. It is intended to be a comprehensive collection of the theory, methods, and applications of regression methods, but it has been deliberately written at an accessible level. The handbook provides a quick and convenient reference or "refresher" on ideas and methods that are useful for the effective analysis of data and its resulting interpretations. Students can use the book as an introduction to and/or summary of key concepts in regression and related course work (including linear, binary logistic, multinomial logistic, count, and nonlinear regression models). Theory underlying the methodology is presented when it advances conceptual understanding and is always supplemented by hands-on examples. References are supplied for readers wanting more detailed material on the topics discussed in the book. R code and data for all of the analyses described in the book are available via an author-maintained website.
Handbook of Regression Analysis With Applications in R (Wiley Series in Probability and Statistics)
by Samprit Chatterjee Jeffrey S. SimonoffHandbook and reference guide for students and practitioners of statistical regression-based analyses in R Handbook of Regression Analysis with Applications in R, Second Edition is a comprehensive and up-to-date guide to conducting complex regressions in the R statistical programming language. The authors’ thorough treatment of “classical” regression analysis in the first edition is complemented here by their discussion of more advanced topics including time-to-event survival data and longitudinal and clustered data. The book further pays particular attention to methods that have become prominent in the last few decades as increasingly large data sets have made new techniques and applications possible. These include: Regularization methods Smoothing methods Tree-based methods In the new edition of the Handbook, the data analyst’s toolkit is explored and expanded. Examples are drawn from a wide variety of real-life applications and data sets. All the utilized R code and data are available via an author-maintained website. Of interest to undergraduate and graduate students taking courses in statistics and regression, the Handbook of Regression Analysis will also be invaluable to practicing data scientists and statisticians.
Handbook of Regression and Modeling: Applications for the Clinical and Pharmaceutical Industries (Chapman & Hall/CRC Biostatistics Series)
by null Daryl S. PaulsonCarefully designed for use by clinical and pharmaceutical researchers and scientists, Handbook of Regression Analysis and Modeling explores statistical methods that have been adapted into biological applications for the quickly evolving field of biostatistics. The author clearly delineates a six-step method for hypothesis testing using data that mi
Handbook of Regression Methods
by Derek Scott YoungHandbook of Regression Methods concisely covers numerous traditional, contemporary, and nonstandard regression methods. The handbook provides a broad overview of regression models, diagnostic procedures, and inference procedures, with emphasis on how these methods are applied. The organization of the handbook benefits both practitioners and researchers, who seek either to obtain a quick understanding of regression methods for specialized problems or to expand their own breadth of knowledge of regression topics. This handbook covers classic material about simple linear regression and multiple linear regression, including assumptions, effective visualizations, and inference procedures. It presents an overview of advanced diagnostic tests, remedial strategies, and model selection procedures. Finally, many chapters are devoted to a diverse range of topics, including censored regression, nonlinear regression, generalized linear models, and semiparametric regression. Features Presents a concise overview of a wide range of regression topics not usually covered in a single text Includes over 80 examples using nearly 70 real datasets, with results obtained using R Offers a Shiny app containing all examples, thus allowing access to the source code and the ability to interact with the analyses
Handbook of Regression Modeling in People Analytics: With Examples in R and Python
by Keith McNultyDespite the recent rapid growth in machine learning and predictive analytics, many of the statistical questions that are faced by researchers and practitioners still involve explaining why something is happening. Regression analysis is the best ‘swiss army knife’ we have for answering these kinds of questions. This book is a learning resource on inferential statistics and regression analysis. It teaches how to do a wide range of statistical analyses in both R and in Python, ranging from simple hypothesis testing to advanced multivariate modelling. Although it is primarily focused on examples related to the analysis of people and talent, the methods easily transfer to any discipline. The book hits a ‘sweet spot’ where there is just enough mathematical theory to support a strong understanding of the methods, but with a step-by-step guide and easily reproducible examples and code, so that the methods can be put into practice immediately. This makes the book accessible to a wide readership, from public and private sector analysts and practitioners to students and researchers. Key Features:• 16 accompanying datasets across a wide range of contexts (e.g. academic, corporate, sports, marketing) • Clear step-by-step instructions on executing the analyses. • Clear guidance on how to interpret results. • Primary instruction in R but added sections for Python coders. • Discussion exercises and data exercises for each of the main chapters.• Final chapter of practice material and datasets ideal for class homework or project work.
Handbook of Research Design in Mathematics and Science Education: Innovations In Science, Technology, Engineering, And Mathematics Learning And Teaching
by Anthony E. Kelly Richard A. LeshThe Handbook of Research Design in Mathematics and Science Education is based on results from an NSF-supported project (REC 9450510) aimed at clarifying the nature of principles that govern the effective use of emerging new research designs in mathematics and science education. A primary goal is to describe several of the most important types of research designs that: * have been pioneered recently by mathematics and science educators; * have distinctive characteristics when they are used in projects that focus on mathematics and science education; and * have proven to be especially productive for investigating the kinds of complex, interacting, and adapting systems that underlie the development of mathematics or science students and teachers, or for the development, dissemination, and implementation of innovative programs of mathematics or science instruction. The volume emphasizes research designs that are intended to radically increase the relevance of research to practice, often by involving practitioners in the identification and formulation of the problems to be addressed or in other key roles in the research process. Examples of such research designs include teaching experiments, clinical interviews, analyses of videotapes, action research studies, ethnographic observations, software development studies (or curricula development studies, more generally), and computer modeling studies. This book's second goal is to begin discussions about the nature of appropriate and productive criteria for assessing (and increasing) the quality of research proposals, projects, or publications that are based on the preceding kind of research designs. A final objective is to describe such guidelines in forms that will be useful to graduate students and others who are novices to the fields of mathematics or science education research. The NSF-supported project from which this book developed involved a series of mini conferences in which leading researchers in mathematics and science education developed detailed specifications for the book, and planned and revised chapters to be included. Chapters were also field tested and revised during a series of doctoral research seminars that were sponsored by the University of Wisconsin's OERI-supported National Center for Improving Student Learning and Achievement in Mathematics and Science. In these seminars, computer-based videoconferencing and www-based discussion groups were used to create interactions in which authors of potential chapters served as "guest discussion leaders" responding to questions and comments from doctoral students and faculty members representing more than a dozen leading research universities throughout the USA and abroad. A Web site with additional resource materials related to this book can be found at http://www.soe.purdue.edu/smsc/lesh/ This internet site includes directions for enrolling in seminars, participating in ongoing discussion groups, and submitting or downloading resources which range from videotapes and transcripts, to assessment instruments or theory-based software, to publications or data samples related to the research designs being discussed.
Handbook of Research on Elderly Entrepreneurship
by Adnane MaâlaouiThis handbook introduces readers to the concept of elderly entrepreneurship, and analyzes key issues concerning individuals and institutions. In addition, it presents theoretical and empirical studies exploring the reasons why elderly persons choose to pursue entrepreneurship, despite their advanced age. To investigate this comparatively new entrepreneurial phenomenon, the contributors address psychological, sociological and gerontological aspects, and share unique interdisciplinary insights. The book’s chapters are methodologically diverse, and the scale of analysis ranges from individual cases to country-level patterns. At a time when the world’s major economies are facing a demographic challenge due to ageing populations, elderly entrepreneurship may provide new economic opportunities and motivate more inclusive policymaking.
Handbook of Risk Theory
by Per Sandin Rafaela Hillerbrand Sabine Roeser Martin PetersonRisk has become one of the main topics in fields as diverse as engineering, medicine and economics, and it is also studied by social scientists, psychologists and legal scholars. But the topic of risk also leads to more fundamental questions such as: What is risk? What can decision theory contribute to the analysis of risk? What does the human perception of risk mean for society? How should we judge whether a risk is morally acceptable or not? Over the last couple of decades questions like these have attracted interest from philosophers and other scholars into risk theory. This handbook provides for an overview into key topics in a major new field of research. It addresses a wide range of topics, ranging from decision theory, risk perception to ethics and social implications of risk, and it also addresses specific case studies. It aims to promote communication and information among all those who are interested in theoetical issues concerning risk and uncertainty. This handbook brings together internationally leading philosophers and scholars from other disciplines who work on risk theory. The contributions are accessibly written and highly relevant to issues that are studied by risk scholars. We hope that the Handbook of Risk Theory will be a helpful starting point for all risk scholars who are interested in broadening and deepening their current perspectives.
Handbook of Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video Processing
by Thierry Bouwmans, Necdet Serhat Aybat and El-hadi ZahzahHandbook of Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video Processing shows you how robust subspace learning and tracking by decomposition into low-rank and sparse matrices provide a suitable framework for computer vision applications. Incorporating both existing and new ideas, the book conveniently gives you one-stop access to a number of different decompositions, algorithms, implementations, and benchmarking techniques. Divided into five parts, the book begins with an overall introduction to robust principal component analysis (PCA) via decomposition into low-rank and sparse matrices. The second part addresses robust matrix factorization/completion problems while the third part focuses on robust online subspace estimation, learning, and tracking. Covering applications in image and video processing, the fourth part discusses image analysis, image denoising, motion saliency detection, video coding, key frame extraction, and hyperspectral video processing. The final part presents resources and applications in background/foreground separation for video surveillance. With contributions from leading teams around the world, this handbook provides a complete overview of the concepts, theories, algorithms, and applications related to robust low-rank and sparse matrix decompositions. It is designed for researchers, developers, and graduate students in computer vision, image and video processing, real-time architecture, machine learning, and data mining.
Handbook of SAS DATA Step Programming
by Arthur LiThis handbook shows readers how best to manage and manipulate data by using the DATA step in SAS, helping them avoid common problems when creating SAS data sets. The author explains that learning syntax does not solve all problems; rather, a thorough comprehension of SAS processing is needed for successful programming. He also guides readers through a programming task. In most of the examples, the author first presents strategies and steps for solving the problem, then offers a solution, and finally gives a more detailed explanation of the solution.
Handbook of Scan Statistics
by Joseph Glaz Markos V. KoutrasScan statistics, one of the most active research areas in applied probability and statistics, has seen a tremendous growth during the last 25 years. Google Scholar lists about 3,500 hits to references of articles on scan statistics since the year 2020, resulting in over 850 hits to articles per year. This is mainly due to extensive and diverse areas of science and technology where scan statistics have been employed, including: atmospheric and climate sciences, business, computer science, criminology, ecology, epidemiology, finance, genetics and genomics, geographic sciences, medical and health sciences, nutrition, pharmaceutical sciences, physics, quality control and reliability, social networks and veterinary science. This volume of the Handbook of Scan Statistics is a collection of forty chapters, authored by leading experts in the field, outlines the research and the breadthof applications of scan statistics to the numerous areas of science and technology listed above. These chapters present an overview of the theory, methods and computational techniques, related to research in the area of scan statistics and outline future developments. It contains extensive references to research articles, books and relevant computer software. Handbook of Scan Statistics is an excellent reference for researchers and graduate students in applied probability and statistics, as well as for scientists in research areas where scan statistics are used. This volume may also be used as a textbook for a graduate level course on scan statistics.
Handbook of Scheduling: Algorithms, Models, and Performance Analysis (Chapman & Hall/CRC Computer and Information Science Series)
by Joseph Y-T. LeungThis handbook provides full coverage of the most recent and advanced topics in scheduling, assembling researchers from all relevant disciplines to facilitate new insights. Presented in six parts, these experts provides introductory material, complete with tutorials and algorithms, then examine classical scheduling problems. Part 3 explores scheduling models that originate in areas such as computer science, operations research. The following section examines scheduling problems that arise in real-time systems. Part 5 discusses stochastic scheduling and queueing networks, and the final section discusses a range of applications in a variety of areas, from airlines to hospitals.
Handbook of Scientific Proposal Writing
by A.Yavuz OrucInvestigators, their home institutions, and funding agencies play significant roles in the development and outcomes of scientific projects. Submitting a proposal to a funding agency is only one dimension of a multivariable and complex funding process, and understanding this is a good first step toward unlocking the puzzle behind why some research p
Handbook of Sharing Confidential Data: Differential Privacy, Secure Multiparty Computation, and Synthetic Data (ISSN)
by Jörg Drechsler, Daniel Kifer, Jerome Reiter and Aleksandra Slavkovi´cStatistical agencies, research organizations, companies, and other data stewards that seek to share data with the public face a challenging dilemma. They need to protect the privacy and confidentiality of data subjects and their attributes while providing data products that are useful for their intended purposes. In an age when information on data subjects is available from a wide range of data sources, as are the computational resources to obtain that information, this challenge is increasingly difficult. The Handbook of Sharing Confidential Data helps data stewards understand how tools from the data confidentiality literature—specifically, synthetic data, formal privacy, and secure computation—can be used to manage trade-offs in disclosure risk and data usefulness.Key features:• Provides overviews of the potential and the limitations of synthetic data, differential privacy, and secure computation• Offers an accessible review of methods for implementing differential privacy, both from methodological and practical perspectives• Presents perspectives from both computer science and statistical science for addressing data confidentiality and privacy• Describes genuine applications of synthetic data, formal privacy, and secure computation to help practitioners implement these approachesThe handbook is accessible to both researchers and practitioners who work with confidential data. It requires familiarity with basic concepts from probability and data analysis.