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Models for Data Analysis: SIS 2018, Palermo, Italy, June 20–22 (Springer Proceedings in Mathematics & Statistics #402)
by Eugenio Brentari Marcello Chiodi Ernst-Jan Camiel WitThe 49Th Scientific meeting of the Italian Statistical Society was held in June 2018 in Palermo, with more than 450 attendants. There were plenary sessions as well as specialized and solicited and contributed sessions.This volume collects a selection of twenty extended contributions covering a wide area of applied and theoretical issues, according to the modern trends in statistical sciences. Only to mention some topics, there are papers on modern textual analysis, sensorial analysis, social inequalities, themes on demography, modern modeling of functional data and high dimensional data, and many other topics.This volume is addressed to academics, PhD students, professionals and researchers in applied and theoretical statistical models for data analysis.
Models for Dependent Time Series (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
by Granville Tunnicliffe Wilson Marco Reale John HaywoodModels for Dependent Time Series addresses the issues that arise and the methodology that can be applied when the dependence between time series is described and modeled. Whether you work in the economic, physical, or life sciences, the book shows you how to draw meaningful, applicable, and statistically valid conclusions from multivariate (or vect
Models for Life
by Jeffrey T. BartonFeatures an authentic and engaging approach to mathematical modeling driven by real-world applications With a focus on mathematical models based on real and current data, Models for Life: An Introduction to Discrete Mathematical Modeling with Microsoft® Office Excel® guides readers in the solution of relevant, practical problems by introducing both mathematical and Excel techniques. The book begins with a step-by-step introduction to discrete dynamical systems, which are mathematical models that describe how a quantity changes from one point in time to the next. Readers are taken through the process, language, and notation required for the construction of such models as well as their implementation in Excel. The book examines single-compartment models in contexts such as population growth, personal finance, and body weight and provides an introduction to more advanced, multi-compartment models via applications in many areas, including military combat, infectious disease epidemics, and ranking methods. Models for Life: An Introduction to Discrete Mathematical Modeling with Microsoft® Office Excel® also features: A modular organization that, after the first chapter, allows readers to explore chapters in any order Numerous practical examples and exercises that enable readers to personalize the presented models by using their own data Carefully selected real-world applications that motivate the mathematical material such as predicting blood alcohol concentration, ranking sports teams, and tracking credit card debt References throughout the book to disciplinary research on which the presented models and model parameters are based in order to provide authenticity and resources for further study Relevant Excel concepts with step-by-step guidance, including screenshots to help readers better understand the presented material Both mathematical and graphical techniques for understanding concepts such as equilibrium values, fixed points, disease endemicity, maximum sustainable yield, and a drug's therapeutic window A companion website that includes the referenced Excel spreadsheets, select solutions to homework problems, and an instructor's manual with solutions to all homework problems, project ideas, and a test bank The book is ideal for undergraduate non-mathematics majors enrolled in mathematics or quantitative reasoning courses such as introductory mathematical modeling, applications of mathematics, survey of mathematics, discrete mathematical modeling, and mathematics for liberal arts. The book is also an appropriate supplement and project source for honors and/or independent study courses in mathematical modeling and mathematical biology. Jeffrey T. Barton, PhD, is Professor of Mathematics in the Mathematics Department at Birmingham-Southern College. A member of the American Mathematical Society and Mathematical Association of America, his mathematical interests include approximation theory, analytic number theory, mathematical biology, mathematical modeling, and the history of mathematics.
Models for Multi-State Survival Data: Rates, Risks, and Pseudo-Values (Chapman & Hall/CRC Texts in Statistical Science)
by Per Kragh Andersen Henrik RavnMulti-state models provide a statistical framework for studying longitudinal data on subjects when focus is on the occurrence of events that the subjects may experience over time. They find application particularly in biostatistics, medicine, and public health. The book includes mathematical detail which can be skipped by readers more interested in the practical examples. It is aimed at biostatisticians and at readers with an interest in the topic having a more applied background, such as epidemiology. This book builds on several courses the authors have taught on the subject. Key Features: · Intensity-based and marginal models. · Survival data, competing risks, illness-death models, recurrent events. · Includes a full chapter on pseudo-values. · Intuitive introductions and mathematical details. · Practical examples of event history data. · Exercises. Software code in R and SAS and the data used in the book can be found on the book’s webpage.
Models for Research and Understanding: Exploring Dynamic Systems, Unconventional Approaches, and Applications (Simulation Foundations, Methods and Applications)
by Stanislaw RaczynskiThis introductory textbook/reference addresses the fundamental and mostly applied kinds of models. The focus is on models of dynamic systems that move and change over time. However, the work also proposes new methods of uncertainty treatment, offering supporting examples.Topics and features: Chapters suitable for textbook use in teaching modeling and simulationIncludes sections of questions and answers, helpful in didactic workProposes new methodology in addition to examining conventional approachesOffers some cognitive, more abstract models to give a wider insight on model building The book’s readership may consist of researchers working on multidisciplinary problems, as well educators and students. It may be used while teaching computer simulation, applied mathematics, system analysis and system dynamics.
Models for Tropical Climate Dynamics: Waves, Clouds, and Precipitation (Mathematics of Planet Earth #3)
by Boualem KhouiderThis book is a survey of the research work done by the author over the last 15 years, in collaboration with various eminent mathematicians and climate scientists on the subject of tropical convection and convectively coupled waves. In the areas of climate modelling and climate change science, tropical dynamics and tropical rainfall are among the biggest uncertainties of future projections. This not only puts at risk billions of human beings who populate the tropical continents but it is also of central importance for climate predictions on the global scale. This book aims to introduce the non-expert readers in mathematics and theoretical physics to this fascinating topic in order to attract interest into this difficult and exciting research area. The general thyme revolves around the use of new deterministic and stochastic multi-cloud models for tropical convection and convectively coupled waves. It draws modelling ideas from various areas of mathematics and physics and used in conjunction with state-of-the-art satellite and in-situ observations and detailed numerical simulations. After a review of preliminary material on tropical dynamics and moist thermodynamics, including recent discoveries based on satellite observations as well as Markov chains, the book immerses the reader into the area of models for convection and tropical waves. It begins with basic concepts of linear stability analysis and ends with the use of these models to improve the state-of-the-art global climate models. The book also contains a fair amount of exercises that makes it suitable as a textbook complement on the subject.
Models in Statistical Social Research (Social Research Today)
by G¨otz RohwerModels in Statistical Social Research provides a comprehensive insight of models used in statistical social research based on statistical data and methods. While traditionally understood statistical models relate to data generating processes which presuppose facts, this book focuses on analytical models which relate to substantial processes generating social facts. It formally develops individual-level, population-level, and multilevel versions of such models and uses these models as frameworks for the definition of notions of functional causality. The book further develops a distinction between the representation of states and events, which is then used to formally distinguish between comparative and dynamic notions of causality. It is shown that, due to the involvement of human actors in substantial processes considered in social research, the conceptual framework of randomized experiments is of only limited use. Instead, modelling selection processes should become an explicit task of social research.
Models, Mathematics, and Methodology in Economic Explanation
by Donald W. KatznerThis book provides a practitioner's foundation for the process of explanatory model building, breaking down that process into five stages. Donald W. Katzner presents a concrete example with unquantified variable values to show how the five-stage procedure works. He describes what is involved in explanatory model building for those interested in this practice, while simultaneously providing a guide for those actually engaged in it. The combination of Katzner's focus on modeling and on mathematics, along with his focus on the explanatory performance of modeling, promises to become an important contribution to the field.
Models, Methods, Concepts & Applications of the Analytic Hierarchy Process
by Thomas L. Saaty Luis G. VargasThe Analytic Hierarchy Process (AHP) is a prominent and powerful tool for making decisions in situations involving multiple objectives. Models, Methods, Concepts and Applications of the Analytic Hierarchy Process, 2nd Edition applies the AHP in order to solve problems focused on the following three themes: economics, the social sciences, and the linking of measurement with human values. For economists, the AHP offers a substantially different approach to dealing with economic problems through ratio scales. Psychologists and political scientists can use the methodology to quantify and derive measurements for intangibles. Meanwhile researchers in the physical and engineering sciences can apply the AHP methods to help resolve the conflicts between hard measurement data and human values. Throughout the book, each of these topics is explored utilizing real life models and examples, relevant to problems in today's society. This new edition has been updated and includes five new chapters that includes discussions of the following: - The eigenvector and why it is necessary - A summary of ongoing research in the Middle East that brings together Israeli and Palestinian scholars to develop concessions from both parties - A look at the Medicare Crisis and how AHP can be used to understand the problems and help develop ideas to solve them.
Models, Mindsets, Meta: Essays Dedicated to Bernhard Steffen on the Occasion of His 60th Birthday (Lecture Notes in Computer Science #11200)
by Tiziana Margaria Susanne Graf Kim G. LarsenThis Festschrift volume is published in honor of Bernhard Steffen, Professor at the Technical University of Dortmund, on the occasion of his 60th birthday. His vision as well as his theoretical and practical work span the development and implementation of novel, specific algorithms, and the establishment of cross-community relationships with the effect to obtain simpler, yet more powerful solutions. He initiated many new lines of research through seminal papers that pioneered various fields, starting with the Concurrency Workbench, a model checking toolbox that significantly influenced the research and development of mode based high assurance systems worldwide. The contributions in this volume reflect the breadth and impact of his work. The introductory paper by the volume editors, the 23 full papers and two personal statements relate to Bernhard’s research and life. This volume, the talks and the entire B-Day at ISoLA 2018 are a tribute to the first 30 years of Bernhard’s passion, impact and vision for many facets of computer science in general and for formal methods in particular. Impact and vision include the many roles that formal methods-supported software development should play in education, in industry and in society.
Models of Computation for Big Data (Advanced Information and Knowledge Processing)
by Rajendra AkerkarThe big data tsunami changes the perspective of industrial and academic research in how they address both foundational questions and practical applications. This calls for a paradigm shift in algorithms and the underlying mathematical techniques. There is a need to understand foundational strengths and address the state of the art challenges in big data that could lead to practical impact. The main goal of this book is to introduce algorithmic techniques for dealing with big data sets. Traditional algorithms work successfully when the input data fits well within memory. In many recent application situations, however, the size of the input data is too large to fit within memory. Models of Computation for Big Data, covers mathematical models for developing such algorithms, which has its roots in the study of big data that occur often in various applications. Most techniques discussed come from research in the last decade. The book will be structured as a sequence of algorithmic ideas, theoretical underpinning, and practical use of that algorithmic idea. Intended for both graduate students and advanced undergraduate students, there are no formal prerequisites, but the reader should be familiar with the fundamentals of algorithm design and analysis, discrete mathematics, probability and have general mathematical maturity.
Models of Network Reliability: Analysis, Combinatorics, and Monte Carlo
by Ilya B. Gertsbakh Yoseph ShpunginUnique in its approach, Models of Network Reliability: Analysis, Combinatorics, and Monte Carlo provides a brief introduction to Monte Carlo methods along with a concise exposition of reliability theory ideas. From there, the text investigates a collection of principal network reliability models, such as terminal connectivity for networks with unre
Models of Neurons and Perceptrons: Selected Problems and Challenges (Studies In Computational Intelligence #770)
by Andrzej BieleckiThis book describes models of the neuron and multilayer neural structures, with a particular focus on mathematical models. It also discusses electronic circuits used as models of the neuron and the synapse, and analyses the relations between the circuits and mathematical models in detail. The first part describes the biological foundations and provides a comprehensive overview of the artificial neural networks. The second part then presents mathematical foundations, reviewing elementary topics, as well as lesser-known problems such as topological conjugacy of dynamical systems and the shadowing property. The final two parts describe the models of the neuron, and the mathematical analysis of the properties of artificial multilayer neural networks. Combining biological, mathematical and electronic approaches, this multidisciplinary book it useful for the mathematicians interested in artificial neural networks and models of the neuron, for computer scientists interested in formal foundations of artificial neural networks, and for the biologists interested in mathematical and electronic models of neural structures and processes.
Models of Strategic Reasoning
by Johan Van Benthem Sujata Ghosh Rineke VerbruggeStrategic behavior is the key to social interaction, from the ever-evolving world of living beings to the modern theatre of designed computational agents. Strategies can make or break participants' aspirations, whether they are selling a house, playing the stock market, or working toward a treaty that limits global warming. This book aims at understanding the phenomenon of strategic behavior in its proper width and depth. A number of experts have combined forces in order to create a comparative view of the different frameworks for strategic reasoning in social interactions that have been developed in game theory, computer science, logic, linguistics, philosophy, and cognitive and social sciences. The chapters are organized in three topic-based sections, namely reasoning about games; formal frameworks for strategies; and strategies in social situations. The book concludes with a discussion on the future of logical studies of strategies.
Models, Simulation, and Experimental Issues in Structural Mechanics
by Michel Frémond Franco Maceri Giuseppe VairoThis book offers valuable insights and provides effective tools useful for imagining, creating, and promoting novel and challenging developments in structural mechanics. It addresses a wide range of topics, such as mechanics and geotechnics, vibration and damping, damage and friction, experimental methods, and advanced structural materials. It also discusses analytical, experimental and numerical findings, focusing on theoretical and practical issues and innovations in the field. Collecting some of the latest results from the Lagrange Laboratory, a European scientific research group, mainly consisting of Italian and French engineers, mechanicians and mathematicians, the book presents the most recent example of the long-term scientific cooperation between well-established French and Italian Mechanics, Mathematics and Engineering Schools. It is a valuable resource for postgraduate students, researchers and practitioners dealing with theoretical and practical issues in structural engineering.
A Model–Theoretic Approach to Proof Theory (Trends in Logic #51)
by Henryk KotlarskiThis book presents a detailed treatment of ordinal combinatorics of large sets tailored for independence results. It uses model theoretic and combinatorial methods to obtain results in proof theory, such as incompleteness theorems or a description of the provably total functions of a theory.In the first chapter, the authors first discusses ordinal combinatorics of finite sets in the style of Ketonen and Solovay. This provides a background for an analysis of subsystems of Peano Arithmetic as well as for combinatorial independence results. Next, the volume examines a variety of proofs of Gödel's incompleteness theorems. The presented proofs differ strongly in nature. They show various aspects of incompleteness phenomena. In additon, coverage introduces some classical methods like the arithmetized completeness theorem, satisfaction predicates or partial satisfaction classes. It also applies them in many contexts. The fourth chapter defines the method of indicators for obtaining independence results. It shows what amount of transfinite induction we have in fragments of Peano arithmetic. Then, it uses combinatorics of large sets of the first chapter to show independence results. The last chapter considers nonstandard satisfaction classes. It presents some of the classical theorems related to them. In particular, it covers the results by S. Smith on definability in the language with a satisfaction class and on models without a satisfaction class. Overall, the book's content lies on the border between combinatorics, proof theory, and model theory of arithmetic. It offers readers a distinctive approach towards independence results by model-theoretic methods.
Modern Adaptive Randomized Clinical Trials: Statistical and Practical Aspects (Chapman & Hall/CRC Biostatistics Series)
by Oleksandr SverdlovIs adaptive randomization always better than traditional fixed-schedule randomization? Which procedures should be used and under which circumstances? What special considerations are required for adaptive randomized trials? What kind of statistical inference should be used to achieve valid and unbiased treatment comparisons following adaptive random
Modern Algebra
by Seth WarnerThis standard text, written for junior and senior undergraduates, is unusual in that its presentation is accessible enough for the beginner, yet its thoroughness and mathematical rigor provide the more advanced student with an exceptionally comprehensive treatment of every aspect of modern algebra. It especially lends itself to use by beginning graduate students unprepared in modern algebra.The presentation opens with a study of algebraic structures in general; the first part then carries the development from natural numbers through rings and fields, vector spaces, and polynomials. The second part (originally published as a separate volume) is made up of five chapters on the real and complex number fields, algebraic extensions of fields, linear operations, inner product spaces, and the axiom of choice.For the benefit of the beginner who can best absorb the principles of algebra by solving problems, the author has provided over 1300 carefully selected exercises. "There is a vast amount of material in these books and a great deal is either new or presented in a new form." -- Mathematical Reviews. Preface. List of Symbols. Exercises. Index. 28 black-and-white line illustrations.
Modern Algebra Essentials
by Lufti A. LutfiyyaREA's Essentials provide quick and easy access to critical information in a variety of different fields, ranging from the most basic to the most advanced. As its name implies, these concise, comprehensive study guides summarize the essentials of the field covered. Essentials are helpful when preparing for exams, doing homework and will remain a lasting reference source for students, teachers, and professionals. Modern Algebra includes set theory, operations, relations, basic properties of the integers, group theory, and ring theory.
Modern Analysis (CRC Press Revivals)
by Kenneth KuttlerModern Analysis provides coverage of real and abstract analysis, offering a sensible introduction to functional analysis as well as a thorough discussion of measure theory, Lebesgue integration, and related topics. This significant study clearly and distinctively presents the teaching and research literature of graduate analysis:Providing a fundamental, modern approach to measure theoryInvestigating advanced material on the Bochner integral, geometric theory, and major theorems in Fourier Analysis Rn, including the theory of singular integrals and Milhin's theorem - material that does not appear in textbooksOffering exceptionally concise and cardinal versions of all the main theorems about characteristic functionsContaining an original examination of sufficient statistics, based on the general theory of Radon measuresWith an ambitious scope, this resource unifies various topics into one volume succinctly and completely. The contents span basic measure theory in an abstract and concrete form, material on classic linear functional analysis, probability, and some major results used in the theory of partial differential equations. Two different proofs of the central limit theorem are examined as well as a straightforward approach to conditional probability and expectation.Modern Analysis provides ample and well-constructed exercises and examples. Introductory topology is included to help the reader understand such items as the Riesz theorem, detailing its proofs and statements. This work will help readers apply measure theory to probability theory, guiding them to understand the theorems rather than merely follow directions.
Modern Analysis of Automorphic Forms By Example: Volume 1 (Cambridge Studies in Advanced Mathematics #173)
by Paul GarrettThis is Volume 1 of a two-volume book that provides a self-contained introduction to the theory and application of automorphic forms, using examples to illustrate several critical analytical concepts surrounding and supporting the theory of automorphic forms. The two-volume book treats three instances, starting with some small unimodular examples, followed by adelic GL2, and finally GLn. Volume 1 features critical results, which are proven carefully and in detail, including discrete decomposition of cuspforms, meromorphic continuation of Eisenstein series, spectral decomposition of pseudo-Eisenstein series, and automorphic Plancherel theorem. Volume 2 features automorphic Green's functions, metrics and topologies on natural function spaces, unbounded operators, vector-valued integrals, vector-valued holomorphic functions, and asymptotics. With numerous proofs and extensive examples, this classroom-tested introductory text is meant for a second-year or advanced graduate course in automorphic forms, and also as a resource for researchers working in automorphic forms, analytic number theory, and related fields.
Modern Analysis of Automorphic Forms By Example: Volume 2 (Cambridge Studies in Advanced Mathematics #174)
by Paul GarrettThis is Volume 2 of a two-volume book that provides a self-contained introduction to the theory and application of automorphic forms, using examples to illustrate several critical analytical concepts surrounding and supporting the theory of automorphic forms. The two-volume book treats three instances, starting with some small unimodular examples, followed by adelic GL2, and finally GLn. Volume 2 features critical results, which are proven carefully and in detail, including automorphic Green's functions, metrics and topologies on natural function spaces, unbounded operators, vector-valued integrals, vector-valued holomorphic functions, and asymptotics. Volume 1 features discrete decomposition of cuspforms, meromorphic continuation of Eisenstein series, spectral decomposition of pseudo-Eisenstein series, and automorphic Plancherel theorem. With numerous proofs and extensive examples, this classroom-tested introductory text is meant for a second-year or advanced graduate course in automorphic forms, and also as a resource for researchers working in automorphic forms, analytic number theory, and related fields.
Modern Analysis of Customer Surveys
by Silvia Salini Ron KenettCustomer survey studies deals with customers, consumers and user satisfaction from a product or service. In practice, many of the customer surveys conducted by business and industry are analyzed in a very simple way, without using models or statistical methods. Typical reports include descriptive statistics and basic graphical displays. As demonstrated in this book, integrating such basic analysis with more advanced tools, provides insights on non-obvious patterns and important relationships between the survey variables. This knowledge can significantly affect the conclusions derived from a survey.Key features:Provides an integrated, case-studies based approach to analysing customer survey data.Presents a general introduction to customer surveys, within an organization's business cycle.Contains classical techniques with modern and non standard tools.Focuses on probabilistic techniques from the area of statistics/data analysis and covers all major recent developments.Accompanied by a supporting website containing datasets and R scripts.Customer survey specialists, quality managers and market researchers will benefit from this book as well as specialists in marketing, data mining and business intelligence fields.
Modern Analytic Methods for Computing Scattering Amplitudes: With Application to Two-Loop Five-Particle Processes (Springer Theses)
by Simone ZoiaThis work presents some essential techniques that constitute the modern strategy for computing scattering amplitudes. It begins with an introductory chapter to fill the gap between a standard QFT course and the latest developments in the field. The author then tackles the main bottleneck: the computation of the loop Feynman integrals. The most efficient technique for their computation is the method of the differential equations. This is discussed in detail, with a particular focus on the mathematical aspects involved in the derivation of the differential equations and their solution. Ample space is devoted to the special functions arising from the differential equations, to their analytic properties, and to the mathematical techniques which allow us to handle them systematically. The thesis also addresses the application of these techniques to a cutting-edge problem of importance for the physics programme of the Large Hadron Collider: five-particle amplitudes at two-loop order. It presents the first analytic results for complete two-loop five-particle amplitudes, in supersymmetric theories and QCD. The techniques discussed here open the door to precision phenomenology for processes of phenomenological interest, such as three-photon, three-jet, and di-photon + jet production.
Modern and Interdisciplinary Problems in Network Science: A Translational Research Perspective
by Zengqiang Chen, Matthias Dehmer, Frank Emmert-Streib and Yongtang ShiModern and Interdisciplinary Problems in Network Science: A Translational Research Perspective covers a broad range of concepts and methods, with a strong emphasis on interdisciplinarity. The topics range from analyzing mathematical properties of network-based methods to applying them to application areas. By covering this broad range of topics, the book aims to fill a gap in the contemporary literature in disciplines such as physics, applied mathematics and information sciences.