- Table View
- List View
Modeling and Valuation of Energy Structures: Analytics, Econometrics, and Numerics (Applied Quantitative Finance)
by Daniel MahoneyCommodity markets present several challenges for quantitative modeling. These include high volatilities, small sample data sets, and physical, operational complexity. In addition, the set of traded products in commodity markets is more limited than in financial or equity markets, making value extraction through trading more difficult. These facts make it very easy for modeling efforts to run into serious problems, as many models are very sensitive to noise and hence can easily fail in practice. Modeling and Valuation of Energy Structures is a comprehensive guide to quantitative and statistical approaches that have been successfully employed in support of trading operations, reflecting the author's 17 years of experience as a front-office 'quant'. The major theme of the book is that simpler is usually better, a message that is drawn out through the reality of incomplete markets, small samples, and informational constraints. The necessary mathematical tools for understanding these issues are thoroughly developed, with many techniques (analytical, econometric, and numerical) collected in a single volume for the first time. A particular emphasis is placed on the central role that the underlying market resolution plays in valuation. Examples are provided to illustrate that robust, approximate valuations are to be preferred to overly ambitious attempts at detailed qualitative modeling.
Gesundheitsökonomische Evaluation von AAL-Technologien: Eine Analyse am Beispiel von intelligenten Rollatoren in der häuslichen Versorgung (Vechtaer Beiträge zur Gerontologie)
by Mareike MähsUm die Informationsbasis über AAL-Technologien zu erhöhen, wird Wissen über die Effektivität, den Nutzen und die Kosten dieser Technologien benötigt. Es fehlen jedoch gerade für AAL-Technologien qualitativ hochwertige gesundheitsökonomische Evaluationsstudien. Die vorliegende Arbeit hat deshalb das Ziel, gesundheitsökonomische Evaluationsverfahren hinsichtlich ihres Einsatzes zur Abschätzung der Wirksamkeit und Wirtschaftlichkeit von AAL-Technologien zu untersuchen und eine geeignete Vorgehensweise zur Evaluationen von AAL-Technologien am Beispiel von intelligenten Rollatoren aufzuzeigen. Mareike Mähs zeigt, dass eine gesundheitsökonomische Evaluation von AAL-Technologien mit spezifischen Herausforderungen einhergeht. Dementsprechend sind vorhandene Verfahren an die Charakteristika der Technologie und ihrer Nutzerinnen sowie Nutzer anzupassen bzw. alternative Verfahren zu wählen. Aus diesem Grund wird ein Framework entwickelt, das eine Orientierung für eine strukturierte Vorgehensweise zur entwicklungsbegleitenden Evaluation von AAL-Technologien am Beispiel von intelligenten Rollatoren entlang deren Lebenszyklus bietet.
Number Theory in Memory of Eduard Wirsing
by Helmut Maier Jörn Steuding Rasa SteudingEduard Wirsing was an outstanding number theorist. In his research he made significant contributions to various subfields of number theory and also collaborated with other eminent scientists (e.g., with the Fields Medalist Alan Baker as well as Don Zagier). This commemorative volume includes numerous papers on current research in number theory by well-known experts, as well as some personal recollections by companions of Wirsing. The topics covered in this volume include arithmetical functions, continued fractions, elementary proofs of the prime number theorem, friable integers, the Goldbach problem, Dirichlet series, Euler products, and more. There is something for every interested reader.
The Data Game: Controversies in Social Science Statistics (Habitat Guides)
by Mark Maier Jennifer ImazekiThis book introduces students to the collection, uses, and interpretation of statistical data in the social sciences. It would suit all social science introductory statistics and research methods courses. Separate chapters are devoted to data in the fields of demography, housing, health, education, crime, the economy, wealth, income, poverty, labor, business statistics, and public opinion polling, with a concluding chapter devoted to the common problem of ambiguity. Each chapter includes multiple case studies illustrating the controversies, overview of data sources including web sites, chapter summary and a set of case study questions designed to stimulate further thought.
Scalar and Vector Risk in the General Framework of Portfolio Theory: A Convex Analysis Approach (CMS/CAIMS Books in Mathematics #9)
by Stanislaus Maier-Paape Pedro Júdice Andreas Platen Qiji Jim ZhuThis book is the culmination of the authors’ industry-academic collaboration in the past several years. The investigation is largely motivated by bank balance sheet management problems. The main difference between a bank balance sheet management problem and a typical portfolio optimization problem is that the former involves multiple risks. The related theoretical investigation leads to a significant extension of the scope of portfolio theories. The book combines practitioners’ perspectives and mathematical rigor. For example, to guide the bank managers to trade off different Pareto efficient points, the topological structure of the Pareto efficient set is carefully analyzed. Moreover, on top of computing solutions, the authors focus the investigation on the qualitative properties of those solutions and their financial meanings. These relations, such as the role of duality, are most useful in helping bank managers to communicate their decisions to the different stakeholders. Finally, bank balance sheet management problems of varying levels of complexity are discussed to illustrate how to apply the central mathematical results. Although the primary motivation and application examples in this book are focused in the area of bank balance sheet management problems, the range of applications of the general portfolio theory is much wider. As a matter of fact, most financial problems involve multiple types of risks. Thus, the book is a good reference for financial practitioners in general and students who are interested in financial applications. This book can also serve as a nice example of a case study for applied mathematicians who are interested in engaging in industry-academic collaboration.
Advanced Object-Oriented Programming in R: Statistical Programming for Data Science, Analysis and Finance
by Thomas MailundLearn how to write object-oriented programs in R and how to construct classes and class hierarchies in the three object-oriented systems available in R. This book gives an introduction to object-oriented programming in the R programming language and shows you how to use and apply R in an object-oriented manner. You will then be able to use this powerful programming style in your own statistical programming projects to write flexible and extendable software. After reading Advanced Object-Oriented Programming in R, you'll come away with a practical project that you can reuse in your own analytics coding endeavors. You'll then be able to visualize your data as objects that have state and then manipulate those objects with polymorphic or generic methods. Your projects will benefit from the high degree of flexibility provided by polymorphism, where the choice of concrete method to execute depends on the type of data being manipulated. What You'll Learn Define and use classes and generic functions using R Work with the R class hierarchies Benefit from implementation reuse Handle operator overloading Apply the S4 and R6 classes Who This Book Is For Experienced programmers and for those with at least some prior experience with R programming language.
Domain-Specific Languages in R: Advanced Statistical Programming
by Thomas MailundGain an accelerated introduction to domain-specific languages in R, including coverage of regular expressions. This compact, in-depth book shows you how DSLs are programming languages specialized for a particular purpose, as opposed to general purpose programming languages. Along the way, you’ll learn to specify tasks you want to do in a precise way and achieve programming goals within a domain-specific context. Domain-Specific Languages in R includes examples of DSLs including large data sets or matrix multiplication; pattern matching DSLs for application in computer vision; and DSLs for continuous time Markov chains and their applications in data science. After reading and using this book, you’ll understand how to write DSLs in R and have skills you can extrapolate to other programming languages.What You'll LearnProgram with domain-specific languages using RDiscover the components of DSLsCarry out large matrix expressions and multiplications Implement metaprogramming with DSLsParse and manipulate expressions Who This Book Is ForThose with prior programming experience. R knowledge is helpful but not required.
Data Analysis and Graphics Using R - an Example-Based Approach
by John Maindonald W. John BraunDiscover what you can do with R! Introducing the R system, covering standard regression methods, then tackling more advanced topics, this book guides users through the practical, powerful tools that the R system provides. The emphasis is on hands-on analysis, graphical display, and interpretation of data. The many worked examples, from real-world research, are accompanied by commentary on what is done and why. The companion website has code and datasets, allowing readers to reproduce all analyses, along with solutions to selected exercises and updates. Assuming basic statistical knowledge and some experience with data analysis (but not R), the book is ideal for research scientists, final-year undergraduate or graduate-level students of applied statistics, and practising statisticians. It is both for learning and for reference. This third edition expands upon topics such as Bayesian inference for regression, errors in variables, generalized linear mixed models, and random forests.
Dispersal, Individual Movement and Spatial Ecology
by Philip K. Maini Mark A. Lewis Sergei V. PetrovskiiDispersal of plants and animals is one of the most fascinating subjects in ecology. It has long been recognized as an important factor affecting ecosystem dynamics. Dispersal is apparently a phenomenon of biological origin; however, because of its complexity, it cannot be studied comprehensively by biological methods alone. Deeper insights into dispersal properties and implications require interdisciplinary approaches involving biologists, ecologists and mathematicians. The purpose of this book is to provide a forum for researches with different backgrounds and expertise and to ensure further advances in the study of dispersal and spatial ecology. This book is unique in its attempt to give an overview of dispersal studies across different spatial scales, such as the scale of individual movement, the population scale and the scale of communities and ecosystems. It is written by top-level experts in the field of dispersal modeling and covers a wide range of problems ranging from the identification of Levy walks in animal movement to the implications of dispersal on an evolutionary timescale.
Topics in Modal Analysis & Testing, Volume 9
by Michael Mains Brandon J. DilworthTopics in Modal Analysis & Testing, Volume 9: Proceedings of the 36th IMAC, A Conference and Exposition on Structural Dynamics, 2018, the ninth volume of nine from the Conference, brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Modal Analysis, including papers on:Operational Modal & Modal Analysis ApplicationsExperimental TechniquesModal Analysis, Measurements & Parameter EstimationModal Vectors & ModelingBasics of Modal AnalysisAdditive Manufacturing & Modal Testing of Printed Parts
Wie berechenbar ist unsere Welt: Herausforderungen Für Mathematik, Informatik Und Philosophie Im Zeitalter Der Digitalisierung (Essentials)
by Klaus MainzerKlaus Mainzer legt in diesem essential dar, dass die Zukunft von KI und Digitalisierung eine nüchterne Analyse erfordert, die Grundlagenforschung mit Anwendung verbindet. Berechenbarkeits- und Beweistheorie können dazu beitragen, Big Data und Machine Learning sicherer zu bewältigen. Dabei zeigt sich, dass die komplexen Herausforderungen der digitalen und analogen Welt in Grundlagenfragen der Mathematik, Informatik und Philosophie tief verwurzelt sind.
Limits of AI - theoretical, practical, ethical (Technik im Fokus)
by Klaus Mainzer Reinhard KahleArtificial intelligence is a key technology with great expectations in science, industry, and everyday life. This book discusses both the perspectives and the limitations of this technology. This concerns the practical, theoretical, and conceptual challenges that AI has to face. In an early phase of symbolic AI, AI focused on formal programs (e.g., expert systems), in which rule-based knowledge was processed with the help of symbolic logic. Today, AI is dominated by statistics-based machine learning methods and Big Data. While this sub-symbolic AI is extremely successful (e.g., chatbots like ChatGPT), it is often not transparent. The book argues for explainable and reliable AI, in which the logical and mathematical foundations of AI-algorithms become understandable and verifiable.
Rotating Machinery, Optical Methods & Scanning LDV Methods, Volume 6: Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics 2021 (Conference Proceedings of the Society for Experimental Mechanics Series)
by Dario Di Maio Javad BaqersadRotating Machinery, Optical Methods & Scanning LDV Methods, Volume 6: Proceedings of the 39th IMAC, A Conference and Exposition on Structural Dynamics, 2021, the sixth volume of nine from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Health Monitoring, including papers on:Novel TechniquesOptical Methods,Scanning LDV MethodsPhotogrammetry & DICRotating Machinery
Distributed Large-Scale Dimensional Metrology
by Domenico Maisano Fiorenzo Franceschini Luca Mastrogiacomo Barbara Pralio Maurizio GalettoThe field of large-scale dimensional metrology (LSM) deals with objects that have linear dimensions ranging from tens to hundreds of meters. It has recently attracted a great deal of interest in many areas of production, including the automotive, railway, and shipbuilding sectors. Distributed Large-Scale Dimensional Metrology introduces a new paradigm in this field that reverses the classical metrological approach: measuring systems that are portable and can be easily moved around the location of the measured object, which is preferable to moving the object itself. Distributed Large-Scale Dimensional Metrology combines the concepts of distributed systems and large scale metrology at the application level. It focuses on the latest insights and challenges of this new generation of systems from the perspective of the designers and developers. The main topics are: coverage of measuring area,sensors calibration,on-line diagnostics,probe management, andanalysis of metrological performance.The general descriptions of each topic are further enriched by specific examples concerning the use of commercially available systems or the development of new prototypes. This will be particularly useful for professional practitioners such as quality engineers, manufacturing and development engineers, and procurement specialists, but Distributed Large-Scale Dimensional Metrology also has a wealth of information for interested academics.
Multivariate Statistical Modeling in Engineering and Management
by Jhareswar MaitiThe book focuses on problem solving for practitioners and model building for academicians under multivariate situations. This book helps readers in understanding the issues, such as knowing variability, extracting patterns, building relationships, and making objective decisions. A large number of multivariate statistical models are covered in the book. The readers will learn how a practical problem can be converted to a statistical problem and how the statistical solution can be interpreted as a practical solution. Key features: • Links data generation process with statistical distributions in multivariate domain • Provides step by step procedure for estimating parameters of developed models • Provides blueprint for data driven decision making • Includes practical examples and case studies relevant for intended audiences The book will help everyone involved in data driven problem solving, modeling and decision making.
Question Evaluation Methods
by Aaron Maitland Jennifer Madans Kristen Miller Gordon WillisInsightful observations on common question evaluation methods and best practices for data collection in survey researchFeaturing contributions from leading researchers and academicians in the field of survey research, Question Evaluation Methods: Contributing to the Science of Data Quality sheds light on question response error and introduces an interdisciplinary, cross-method approach that is essential for advancing knowledge about data quality and ensuring the credibility of conclusions drawn from surveys and censuses. Offering a variety of expert analyses of question evaluation methods, the book provides recommendations and best practices for researchers working with data in the health and social sciences.Based on a workshop held at the National Center for Health Statistics (NCHS), this book presents and compares various question evaluation methods that are used in modern-day data collection and analysis. Each section includes an introduction to a method by a leading authority in the field, followed by responses from other experts that outline related strengths, weaknesses, and underlying assumptions. Topics covered include:Behavior codingCognitive interviewingItem response theoryLatent class analysisSplit-sample experimentsMultitrait-multimethod experimentsField-based data methodsA concluding discussion identifies common themes across the presented material and their relevance to the future of survey methods, data analysis, and the production of Federal statistics. Together, the methods presented in this book offer researchers various scientific approaches to evaluating survey quality to ensure that the responses to these questions result in reliable, high-quality data.Question Evaluation Methods is a valuable supplement for courses on questionnaire design, survey methods, and evaluation methods at the upper-undergraduate and graduate levels. it also serves as a reference for government statisticians, survey methodologists, and researchers and practitioners who carry out survey research in the areas of the social and health sciences.
Beginner's Guide to Code Algorithms: Experiments to Enhance Productivity and Solve Problems
by Deepankar MaitraDo you have creative ideas that you wish you could transform into code?Do you want to boost your problem solving and logic skills?Do you want to enhance your career by adopting an algorithmic mindset?In our increasingly digital world, coding is an essential skill. Communicating an algorithm to a machine to perform a set of tasks is vital. Beginner’s Guide to Code Algorithms: Experiments to Enhance Productivity and Solve Problems written by Deepankar Maitra teaches you how to think like a programmer. The author unravels the secret behind writing code – building a good algorithm. Algorithmic thinking leads to asking the right question and enables a shift from issue resolution to value creation. Having this mindset will make you more marketable to employers. This book takes you on a problem-solving journey to expand your mind and increase your willingness to experiment with code. You will: Learn the art of building an algorithm through hands-on exercises Understand how to develop code for inspiring productivity concepts Build a mentality of developing algorithms to solve problems Develop, test, review, and improve code through guided experimentation This book is designed to develop a culture of logical thinking through intellectual stimulation. It will benefit students and teachers of programming, business professionals, as well as experienced users of Microsoft Excel who wish to become proficient with macros.
Advances in Fluid Mechanics and Solid Mechanics: Proceedings of the 63rd Congress of ISTAM 2018 (Lecture Notes in Mechanical Engineering)
by Damodar Maity Pradeep G. Siddheshwar Sunanda SahaThis book comprises select proceedings of the 63rd Congress of the Indian Society of Theoretical and Applied Mechanics (ISTAM) held in Bangalore, in December 2018. Latest research in computational, experimental, and applied mechanics is presented in the book. The chapters are broadly classified into two sections - (i) fluid mechanics and (ii) solid mechanics. Each section covers computational and experimental studies on various contemporary topics such as aerospace dynamics and propulsion, atmospheric sciences, boundary layers, compressible flow, environmental fluid dynamics, control structures, fracture and crack, viscoelasticity, and mechanics of composites. The contents of this book will serve as a useful reference to students, researchers, and practitioners interested in the broad field of mechanics.
Statistical Methods in Hydrology and Hydroclimatology (Springer Transactions in Civil and Environmental Engineering)
by Rajib MaityThis book focuses on the application of statistical methods in the field of hydrology and hydroclimatology. Among the latest theories being used in these fields, the book introduces the theory of copulas and its applications in this context. The purpose is to develop an understanding and illustrate the usefulness of the statistical techniques with detailed theory and numerous worked out examples. Apart from this, MATLAB-based codes and solutions of some worked out examples are also provided to assist the readers to handle real life data. This book presents a comprehensive knowledge of statistical techniques combining the basics of probability and the current advances in stochastic hydrology. Besides serving as a textbook for graduate courses on stochastic modeling in hydrology and related disciplines, the book offers valuable resources for researchers and professionals involved in the field of hydrology and climatology.
Tropical Intraseasonal Variability and the Stochastic Skeleton Method (Mathematics of Planet Earth)
by Andrew J. Majda Samuel N. Stechmann Shengqian Chen H. Reed Ogrosky Sulian ThualIn this text, modern applied mathematics and physical insight are used to construct the simplest and first nonlinear dynamical model for the Madden-Julian oscillation (MJO), i.e. the stochastic skeleton model. This model captures the fundamental features of the MJO and offers a theoretical prediction of its structure, leading to new detailed methods to identify it in observational data. The text contributes to understanding and predicting intraseasonal variability, which remains a challenging task in contemporary climate, atmospheric, and oceanic science. In the tropics, the Madden-Julian oscillation (MJO) is the dominant component of intraseasonal variability. One of the strengths of this text is demonstrating how a blend of modern applied mathematical tools, including linear and nonlinear partial differential equations (PDEs), simple stochastic modeling, and numerical algorithms, have been used in conjunction with physical insight to create the model. These tools are also applied in developing several extensions of the model in order to capture additional features of the MJO, including its refined vertical structure and its interactions with the extratropics. This book is of interest to graduate students, postdocs, and senior researchers in pure and applied mathematics, physics, engineering, and climate, atmospheric, and oceanic science interested in turbulent dynamical systems as well as other complex systems.
Distributed Computing and Optimization Techniques: Select Proceedings of ICDCOT 2021 (Lecture Notes in Electrical Engineering #903)
by Sudhan Majhi Rocío Pérez de Prado Chandrappa Dasanapura NanjundaiahThis book introduces research presented at the International Conference on Distributed Computing and Optimization Techniques (ICDCOT–2021), a two-day conference, where researchers, engineers, and academicians from all over the world came together to share their experiences and findings on all aspects of distributed computing and its applications in diverse areas. The book includes papers on distributed computing, intelligent system, optimization method, mathematical modeling, fuzzy logic, neural networks, grid computing, load balancing, communication. It will be a valuable resource for students, academics, and practitioners in the industry working on distributed computing.
Scalable Pattern Recognition Algorithms
by Pradipta Maji Sushmita PaulThis book addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models. The text reviews both established and cutting-edge research, providing a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics. Features: integrates different soft computing and machine learning methodologies with pattern recognition tasks; discusses in detail the integration of different techniques for handling uncertainties in decision-making and efficiently mining large biological datasets; presents a particular emphasis on real-life applications, such as microarray expression datasets and magnetic resonance images; includes numerous examples and experimental results to support the theoretical concepts described; concludes each chapter with directions for future research and a comprehensive bibliography.
On the Estimation of Multiple Random Integrals and U-Statistics
by Péter MajorThis work starts with the study of those limit theorems in probability theory for which classical methods do not work. In many cases some form of linearization can help to solve the problem, because the linearized version is simpler. But in order to apply such a method we have to show that the linearization causes a negligible error. The estimation of this error leads to some important large deviation type problems, and the main subject of this work is their investigation. We provide sharp estimates of the tail distribution of multiple integrals with respect to a normalized empirical measure and so-called degenerate U-statistics and also of the supremum of appropriate classes of such quantities. The proofs apply a number of useful techniques of modern probability that enable us to investigate the non-linear functionals of independent random variables. This lecture note yields insights into these methods, and may also be useful for those who only want some new tools to help them prove limit theorems when standard methods are not a viable option.
Decentralization In Infinite Horizon Economies
by Mukul MajumdarThis book summarizes some issues involved in developing a theory of decentralized resource allocation mechanism in infinite horizon economies. It constitutes a definitive account of cutting-edge research on a topic of continuing importance in price theory. .
Computer Aided Verification: 29th International Conference, CAV 2017, Heidelberg, Germany, July 24-28, 2017, Proceedings, Part II (Lecture Notes in Computer Science #10427)
by Rupak Majumdar Viktor KunčakThe two-volume set LNCS 10426 and LNCS 10427 constitutes the refereed proceedings of the 29th International Conference on Computer Aided Verification, CAV 2017, held in Heidelberg, Germany, in July 2017. The total of 50 full and 7 short papers presented together with 5 keynotes and tutorials in the proceedings was carefully reviewed and selected from 191 submissions. The CAV conference series is dedicated to the advancement of the theory and practice of computer-aided formal analysis of hardware and software systems. The conference covers the spectrum from theoretical results to concrete applications, with an emphasis on practical verification tools and the algorithms and techniques that are needed for their implementation.