Presents numerous exercises with solutions to help the reader better understand different aspects of modern statistics.
Applications with R and Matlab code show how to practically use the methods.
Includes numerous explanations and tips on how to apply modern statistical methods.
The complexity of today’s statistical data calls for modern mathematical tools. Many fields of science make use of mathematical statistics and require continuous updating on statistical technologies. Practice makes perfect, since mastering the tools makes them applicable. Our book of exercises and solutions offers a wide range of applications and numerical solutions based on R. In modern mathematical statistics, the purpose is to provide statistics students with a number of basic exercises and also an understanding of how the theory can be applied to real-world problems. The application aspect is also quite important, as most previous exercise books are mostly on theoretical derivations. Also we add some problems from topics often encountered in recent research papers. The book was written for statistics students with one or two years of coursework in mathematical statistics and probability, professors who hold courses in mathematical statistics, and researchers in other fields who would like to do some exercises on math statistics.
Presents over twenty case studies drawn from practical experience ; Demonstrates how success is measured, providing reader with tools for implementation; Organized around five themes with specific comments for case comparisons from experts in the field; Introduces readers to several contexts that can be applied in various situations; Resource for further study of service innovation
Case Studies in Service Innovation provides the reader fresh insight into how innovation occurs in practice, and stimulates learning from one context to another. The volume brings together contributions from researchers and practitioners in a celebration of achievements with the intention of adding to the wider understanding of how service innovation develops. Each case presents a brief description of the context in which the innovation occurred, the opportunity that led to the innovation and an overview of the innovation itself, also addressing how success was measured, what success has been achieved to date and providing links to further information.
The book is organized around five major themes, each reflecting recognized sources of service innovation: Business Model Innovation: new ways of creating, delivering or capturing economic, social, environmental and other types of value; The Organization in its Environment: an organization engaging beyond its own boundaries, with public private partnerships, sourcing knowledge externally, innovation networks, and open or distributed innovation; Innovation Management within an Organization: an organization actively encouraging innovation within its own boundaries using project teams, internal governance of innovation, and methods or tools that stimulate innovation; Process Innovation: changes in service design and delivery processes, such as consumer led innovation or consumers as part of the innovation process, service operations management, and educational processes; Technology Innovation: the use of technology, including ICT enabled innovation, ICTs that are themselves innovative and support the delivery of new services, new ICT services, new ways of delivering services associated with ICT products, and technology other than ICT.
The final part of the book is given to four extended cases allowing for a more in-depth treatment of innovation within a complex service system. The extended cases also illustrate two important and growing trends, firstly the need for, and benefits of, a more customer centric approach to service innovation and secondly the need for better understanding of public services and the role of public-private partnerships in identifying and achieving innovation
В монографии рассматриваются исследования изменения ценностей и идентичностей на пост-коммунистическом пространстве.
The volume is dedicated to Boris Mirkin on the occasion of his 70th birthday. In addition to his startling PhD results in abstract automata theory, Mirkin’s ground breaking contributions in various fields of decision making and data analysis have marked the fourth quarter of the 20th century and beyond. Mirkin has done pioneering work in group choice, clustering, data mining and knowledge discovery aimed at finding and describing non-trivial or hidden structures—first of all, clusters, orderings, and hierarchies—in multivariate and/or network data.
This volume contains a collection of papers reflecting recent developments rooted in Mirkin's fundamental contribution to the state-of-the-art in group choice, ordering, clustering, data mining, and knowledge discovery. Researchers, students, and software engineers will benefit from new knowledge discovery techniques and application directions.
Vladimir Arnold is one of the great mathematical scientists of our time. He is famous for both the breadth and the depth of his work. At the same time he is one of the most prolific and outstanding mathematical authors. This first volume of his Collected Works focuses on representations of functions, celestial mechanics, and KAM theory.
The CCIS series is devoted to the publication of proceedings of computer science conferences. Its aim is to efficiently disseminate original research results in informatics in printed and electronic form. While the focus is on publication of peer-reviewed full papers presenting mature work, inclusion of reviewed short papers reporting on work in progress is welcome, too. Besides globally relevant meetings with internationally representative program committees guaranteeing a strict peer-reviewing and paper selection process, conferences run by societies or of high regional or national relevance are also considered for publication.
The present study generalizes the results of scientific research in the field of economic and mathematic simulation using elements of the theory of functions of complex variables (TFCV), which was conducted since 2004 under the author’s scientific supervision. Since the new results significantly extend the instrumental basis of scientific research in economics and possess their own theoretical base and logic, this section of economic and mathematic simulation was called “complex economics”. The study provides the fundamentals of this new scientific direction in economics and demonstrates how to use this theoretical base to build new economic and mathematic models that appear to be more adequate than models of real variables.
Most economists are absolutely unfamiliar or slightly familiar with the theory of functions complex variables. This is why, in this study, we would state briefly some provisions of this theory to get the reader acquainted with TFCV, and then formulate sequentially the principles of the theory of complex economy, its axiomatic core, basic conceptual positions of the theory, methods and models of the complex economics. Where necessary, theoretical provisions are verified by examples from the real economic practice.
The study is targeted at scientific workers, post-graduate students and doctors using economic and mathematic simulations in their activity.
This is the first textbook on attribute exploration, its theory, its algorithms for applications, and some of its many possible generalizations. Attribute exploration is useful for acquiring structured knowledge through an interactive process, by asking queries to an expert. Generalizations that handle incomplete, faulty, or imprecise data are discussed, but the focus lies on knowledge extraction from a reliable information source.
The method is based on Formal Concept Analysis, a mathematical theory of concepts and concept hierarchies, and uses its expressive diagrams. The presentation is self-contained. It provides an introduction to Formal Concept Analysis with emphasis on its ability to derive algebraic structures from qualitative data, which can be represented in meaningful and precise graphics.
This book constitutes the proceedings of the 20th International Conference on Conceptual Structures, ICCS 2013, held in Mumbai, India, in January 2013. The 22 full papers presented were carefully reviewed and selected from 43 submissions for inclusion in the book. The volume also contains 3 invited talks. ICCS focuses on the useful representation and analysis of conceptual knowledge with research and business applications. It advances the theory and practice in connecting the user's conceptual approach to problem solving with the formal structures that computer applications need to bring their productivity to bear. Conceptual structures (CS) represent a family of approaches that builds on the successes of artificial intelligence, business intelligence, computational linguistics, conceptual modeling, information and Web technologies, user modeling, and knowledge management.
This book constitutes the refereed proceedings of the 17th International Conference on Conceptual Structures, ICCS 2009, which took place in Moscow, Russia, on July 26-31, 2009.
The 18 papers presented together with 5 invited contributions were carefully reviewed and selected from approximately 50 submissions. Originally centered around research on knowledge representation and reasoning with conceptual graphs, over the years ICCS has broadened its scope to include innovations from a wider range of theories and related practices, among them other forms of graph-based formalisms like RDF or existential graphs, formal concept analysis, semantic Web technologies, ontologies, concept mapping and more.
This volume contains a collection of papers based on lectures and presentations delivered at the International Conference on Constructive Nonsmooth Analysis (CNSA) held in St. Petersburg (Russia) from June 18-23, 2012. This conference was organized to mark the 50th anniversary of the birth of nonsmooth analysis and nondifferentiable optimization and was dedicated to J.-J. Moreau and the late B.N. Pshenichnyi, A.M. Rubinov, and N.Z. Shor, whose contributions to NSA and NDO remain invaluable.
The first four chapters of the book are devoted to the theory of nonsmooth analysis. Chapters 5-8 contain new results in nonsmooth mechanics and calculus of variations. Chapters 9-13 are related to nondifferentiable optimization, and the volume concludes with four chapters containing interesting and important historical chapters, including tributes to three giants of nonsmooth analysis, convexity, and optimization: Alexandr Alexandrov, Leonid Kantorovich, and Alex Rubinov. The last chapter provides an overview and important snapshots of the 50-year history of convex analysis and optimization.
Control of Discrete-Time Descriptor Systems takes an anisotropy-based approach to the explanation of random input disturbance with an information-theoretic representation. It describes the random input signal more precisely, and the anisotropic norm minimization included in the book enables readers to tune their controllers better through the mathematical methods provided. The book contains numerous examples of practical applications of descriptor systems in various fields, from robotics to economics, and presents an information-theoretic approach to the mathematical description of coloured noise. Anisotropy-based analysis and design for descriptor systems is supplied along with proofs of basic statements, which help readers to understand the algorithms proposed, and to undertake their own numerical simulations. This book serves as a source of ideas for academic researchers and postgraduate students working in the control of discrete-time systems. The control design procedures outlined are numerically effective and easily implementable in MATLAB®
This is a textbook in data analysis. Its contents are heavily influenced by the idea that data analysis should help in enhancing and augmenting knowledge of the domain as represented by the concepts and statements of relation between them. According to this view, two main pathways for data analysis are summarization, for developing and augmenting concepts, and correlation, for enhancing and establishing relations. Visualization, in this context, is a way of presenting results in a cognitively comfortable way. The term summarization is understood quite broadly here to embrace not only simple summaries like totals and means, but also more complex summaries such as the principal components of a set of features or cluster structures in a set of entities.
The material presented in this perspective makes a unique mix of subjects from the fields of statistical data analysis, data mining, and computational intelligence, which follow different systems of presentation.