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The Wiley-Interscience Paperback Series consists of selected booksthat have been made more accessible to consumers in an effort toincrease global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese works by making them available to future generations ofstatisticians, mathematicians, and scientists. "The title of the book more or less sums up the contents. Itappears to me to represent a real breakthrough in the art ofdealing in ‘unconventional’ data. . . . I found thewhole book both readable and enjoyable. It is suitable for dataanalysts, academic statisticians, and professional softwarewriters." –Journal of the Royal Statistical Society "The book assumes a working knowledge of all of the principalresults and techniques used in least squares multiple regression,as expressed in vector and matrix notation. Given this background,the book is clear and easy to use. . . . The techniques areillustrated in great detail with practical data sets fromeconometrics." –Short Book Reviews, International Statistical Institute Regression Diagnostics: Identifying Influential Data and Sourcesof Collinearity provides practicing statisticians andeconometricians with new tools for assessing quality andreliability of regression estimates. Diagnostic techniques aredeveloped that aid in the systematic location of data points thatare unusual or inordinately influential; measure the presence andintensity of collinear relations among the regression data; andhelp to identify variables involved in each and pinpoint estimatedcoefficients potentially most adversely affected. The bookemphasizes diagnostics and includes suggestions for remedialaction
This book addresses a range of complex issues associated with condition monitoring (CM), fault diagnosis and detection (FDD) in smart buildings, wide area monitoring (WAM), wind energy conversion systems (WECSs), photovoltaic (PV) systems, structures, electrical systems, mechanical systems, smart grids, etc. The book’s goal is to develop and combine all advanced nonintrusive CMFD approaches on a common platform. To do so, it explores the main components of various systems used for CMFD purposes. The content is divided into three main parts, the first of which provides a brief introduction, before focusing on the state of the art and major research gaps in the area of CMFD. The second part covers the step-by-step implementation of novel soft computing applications in CMFD for electrical and mechanical systems. In the third and final part, the simulation codes for each chapter are included in an extensive appendix to support newcomers to the field.
Proceedings of COMADEM 90: the Second International Congress of Condition Monitoring and Diagnostic Engineering Management
This Proceedings contains the papers presented at the 14th International Conference on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2001), held in Manchester, UK, on 4-6 September 2001. COMADEM 2001 builds on the excellent reputation of previous conferences in this series, and is essential for anyone working in the field of condition monitoring and maintenance management.The scope of the conference is truly interdisciplinary. The Proceedings contains papers from six continents, written by experts in industry and academia the world over, bringing together the latest thoughts on topics including: Condition-based maintenance Reliability centred maintenance Asset management Industrial case studies Fault detection and diagnosis Prognostics Non-destructive evaluation Integrated diagnostics Vibration Oil and debris analysis Tribology Thermal techniques Risk assessment Structural health monitoring Sensor technology Advanced signal processing Neural networks Multivariate statistics Data compression and fusion This Proceedings also contains a wealth of industrial case studies, and the latest developments in education, training and certification. For more information on COMADEM's aims and scope, please visit http://www.comadem.com
Statistics and computing share many close relationships. Computing now permeates every aspect of statistics, from pure description to the development of statistical theory. At the same time, the computational methods used in statistical work span much of computer science. Elements of Statistical Computing covers the broad usage of computing in statistics. It provides a comprehensive account of the most important computational statistics. Included are discussions of numerical analysis, numerical integration, and smoothing. The author give special attention to floating point standards and numerical analysis; iterative methods for both linear and nonlinear equation, such as Gauss-Seidel method and successive over-relaxation; and computational methods for missing data, such as the EM algorithm. Also covered are new areas of interest, such as the Kalman filter, projection-pursuit methods, density estimation, and other computer-intensive techniques.
This innovative, intermediate-level statistics text fills an important gap by presenting the theory of linear statistical models at a level appropriate for senior undergraduate or first-year graduate students. With an innovative approach, the author's introduces students to the mathematical and statistical concepts and tools that form a foundation
Integrating the research from the author's previous work, Regression Diagnostics, and significant revision and updating, this monograph presents a self-contained treatment of the problems of ill-conditioning and data weaknesses as they affect the least-squares estimation of the linear model, along with extensions to nonlinear models and simultaneous-equations estimators. Also features a substantial amount of new information, including background material and data sets and numerous related elements previously scattered throughout the literature.
Plasma Diagnostics, Volume 1: Discharge Parameters and Chemistry covers seven chapters on the important diagnostic techniques for plasmas and details their use in particular applications. The book discusses optical diagnostic techniques for low pressure plasmas and plasma processing; plasma diagnostics for electrical discharge light sources; as well as Langmuir probes. The text also describes the mass spectroscopy of plasmas, microwave diagnostics, paramagnetic resonance diagnostics, and diagnostics in thermal plasma processing. Electrical engineers, nuclear engineers, microwave engineers, chemists, and technical personnel in universities, industry, and national laboratories will find the book invaluable.
This book focuses on food policy, and its relationship to public health, as an increasingly important issue in today’s society. Contributors highlight the lack of global regulation in the food supply chain and explore the common tendency to leave regulation to markets and to individual consumer decisions. In a period where there is growing concern about the sustainability of contemporary food systems, this book considers the inadequate response made to issues of food waste where solutions in high income countries are dependent on lifestyle and consumer behaviour. It offers an insight in to the importance of people’s everyday lives in relation to policies on public health, food and sustainability. The text demonstrates the corrosive impact of social inequality, and the futility of identifying lower income consumers as flawed when aiming for food policies that seek to achieve improvements in public health. Factors such as technological developments, ecological concerns and international trade are also taken in to account. This book was originally published as a special issue of Critical Public Health.
Process engineering spans industrial applications in the manufacturing sector from petrochemical to polymer to mineral production. From Plant Data to Process Control covers the most up-to-date techniques and algorithms in the area of process identification (PID) and process control, two key components of process engineering, essential for optimizing production systems. It examines both the theoretical advances in process design and control theory, and a wide variety of implementations. A wide variety of approaches are presented for building models of dynamical systems based on observed data (process identification) and for making the output of a system behave in a desired fashion by properly selecting the process input (process control).