Short: (250 characters max)This compelling biography of Arjun K. Gupta, an internationally known mathematician and scholar, covers the trajectory of his life from his childhood in India to his international career as researcher, mentor, and statistics professor. Dr. Arjun K. Gupta's accomplishments in the world of statistics and the scope of his international travels represent a story that needs to be shared. His journey from a small town in India to the world-stage of statistics demonstrates how much is possible with commitment and determination. His dedication to education and family are a light for future generations, for whom this book is written.
Sample surveys is the most important branch of statistics. Without sample surveys there is no data, and without data there is no statistics. This book is the culmination of the lecture notes developed by the authors. The approach is theoretical in the sense that it gives mathematical proofs of the results in sample surveys. Intended as a textbook for a one-semester course for undergraduate seniors or first-year graduate students, a prerequisite basic knowledge of algebra, calculus, and statistical theory is required to master the techniques described in this book.
Recently there has been a keen interest in the statistical analysis of change point detec tion and estimation. Mainly, it is because change point problems can be encountered in many disciplines such as economics, finance, medicine, psychology, geology, litera ture, etc. , and even in our daily lives. From the statistical point of view, a change point is a place or time point such that the observations follow one distribution up to that point and follow another distribution after that point. Multiple change points problem can also be defined similarly. So the change point(s) problem is two fold: one is to de cide if there is any change (often viewed as a hypothesis testing problem), another is to locate the change point when there is a change present (often viewed as an estimation problem). The earliest change point study can be traced back to the 1950s. During the fol lowing period of some forty years, numerous articles have been published in various journals and proceedings. Many of them cover the topic of single change point in the means of a sequence of independently normally distributed random variables. Another popularly covered topic is a change point in regression models such as linear regres sion and autoregression. The methods used are mainly likelihood ratio, nonparametric, and Bayesian. Few authors also considered the change point problem in other model settings such as the gamma and exponential.
Elliptically Contoured Models in Statistics and Portfolio Theory fully revises the first detailed introduction to the theory of matrix variate elliptically contoured distributions. There are two additional chapters, and all the original chapters of this classic text have been updated. Resources in this book will be valuable for researchers, practitioners, and graduate students in statistics and related fields of finance and engineering. Those interested in multivariate statistical analysis and its application to portfolio theory will find this text immediately useful. In multivariate statistical analysis, elliptical distributions have recently provided an alternative to the normal model. Elliptical distributions have also increased their popularity in finance because of the ability to model heavy tails usually observed in real data. Most of the work, however, is spread out in journals throughout the world and is not easily accessible to the investigators. A noteworthy function of this book is the collection of the most important results on the theory of matrix variate elliptically contoured distributions that were previously only available in the journal-based literature. The content is organized in a unified manner that can serve an a valuable introduction to the subject.
This volume is a collection of exercises with their solutions in Design and Analysis of Experiments. At present there is not a single book which collects such exercises. Theseexercises have been collected by the authors during the last four decadesduring their student and teaching years. They should prove useful to graduate students and research workers in Statistics. In Chapter I, theoretical results that are needed for understanding the material in this book, are given. Chapter 2 lists the exercises which have been collected by the authors. The solutions of these problems are given in Chapter 3. Finally an index is provided for quick reference. Grateful appreciation for financial support for Dr. Kabe's research at St. Mary's University is extended to National Research Council of Canada and St. May's Uni versity Senate Research Committee. For his visit to the Department ofMathematics and Statistics the authors are thankful to the Bowling Green State University.
With an emphasis on models and techniques, this textbook introduces many of the fundamental concepts of stochastic modeling that are now a vital component of almost every scientific investigation. In particular, emphasis is placed on laying the foundation for solving problems in reliability, insurance, finance, and credit risk. The material has been carefully selected to cover the basic concepts and techniques on each topic, making this an ideal introductory gateway to more advanced learning. With exercises and solutions to selected problems accompanying each chapter, this textbook is for a wide audience including advanced undergraduate and beginning-level graduate students, researchers, and practitioners in mathematics, statistics, engineering, and economics.
Useful in physics, economics, psychology, and other fields, random matrices play an important role in the study of multivariate statistical methods. Until now, however, most of the material on random matrices could only be found scattered in various statistical journals. Matrix Variate Distributions gathers and systematically presents most of the recent developments in continuous matrix variate distribution theory and includes new results. After a review of the essential background material, the authors investigate the range of matrix variate distributions, including: matrix variate normal distribution Wishart distribution Matrix variate t-distribution Matrix variate beta distribution F-distribution Matrix variate Dirichlet distribution Matrix quadratic forms With its inclusion of new results, Matrix Variate Distributions promises to stimulate further research and help advance the field of multivariate statistical analysis.
The design of experiments holds a central place in statistics. The aim of this book is to present in a readily accessible form certain theoretical results of this vast field. This is intended as a textbook for a one-semester or two-quarter course for undergraduate seniors or first-year graduate students, or as a supplementary resource. Basic knowledge of algebra, calculus and statistical theory is required to master the techniques presented in this book.To help the reader, basic statistical tools that are needed in the book are given in a separate chapter. Mathematical results from Modern Algebra which are needed for the construction of designs are also given. Wherever possible the proofs of the theoretical results are provided.
Information-Statistical Data Mining: Warehouse Integration with Examples of Oracle Basics is written to introduce basic concepts, advanced research techniques, and practical solutions of data warehousing and data mining for hosting large data sets and EDA. This book is unique because it is one of the few in the forefront that attempts to bridge statistics and information theory through a concept of patterns. Information-Statistical Data Mining: Warehouse Integration with Examples of Oracle Basics is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a secondary text for graduate-level students in computer science and engineering.
In multivariate statistical analysis, elliptical distributions have recently provided an alternative to the normal model. Most of the work, however, is spread out in journals throughout the world and is not easily accessible to the investigators. Fang, Kotz, and Ng presented a systematic study of multivariate elliptical distributions, however, they did not discuss the matrix variate case. Recently Fang and Zhang have summarized the results of generalized multivariate analysis which include vector as well as the matrix variate distributions. On the other hand, Fang and Anderson collected research papers on matrix variate elliptical distributions, many of them published for the first time in English. They published very rich material on the topic, but the results are given in paper form which does not provide a unified treatment of the theory. Therefore, it seemed appropriate to collect the most important results on the theory of matrix variate elliptically contoured distributions available in the literature and organize them in a unified manner that can serve as an introduction to the subject. The book will be useful for researchers, teachers, and graduate students in statistics and related fields whose interests involve multivariate statistical analysis. Parts of this book were presented by Arjun K Gupta as a one semester course at Bowling Green State University. Some new results have also been included which generalize the results in Fang and Zhang. Knowledge of matrix algebra and statistics at the level of Anderson is assumed. However, Chapter 1 summarizes some results of matrix algebra.
Why did the Rwandan genocide take place? How could parents feed their own children drinks laced with poison in Jonestown? As we see many parts of the world being engulfed in fratricidal frenzy, we wonder if it can happen in this country. Gupta examines contemporary cases of genocide and mass murder and seeks to explain why certain societies are more prone to these actions and others are relatively immune. Gupta sees a dialectical tension between our two identities: the self and the collective. The end of the medieval period was marked by the emergence of individualism in Europe. With time, the march of individualism engulfed the entire Western world and permeated every aspect of its culture, tradition, and academic paradigm. Neoclassical economics is the embodiment of this single-minded pursuit of the rationality of individualism. However, our psychobiological evolution has also imbued us with the irrepressible desire to form groups and to act upon its welfare. The reason for this eternal conflict lies in our own struggle with our two identities. When the pendulum swings to the extreme end of collectivism, genocide and other forms of social abnormalities--collective madness--occur. When we move too far into individualism, people tend to seek something greater beyond selfish pursuits. Through his panoramic view, Gupta provides an explanation for both social order and political pathology that will be of interest to students, scholars, and other researchers involved with ethnic conflict, collective behavior, and conflict resolution.
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. A GROUNDBREAKING GUIDE TO THE ART, SCIENCE, TOOLS, AND DEPLOYMENT OF INNOVATION "It has never been more important to educate people and organizations how to out-imagine, out-create, and out-innovate....The insight and experiences captured by [this book] make an important contribution toward reaching this goal." -- From the Foreword by Deborah Wince-Smith, President, Council on Competitiveness Developed by the editors of the International Journal of Innovation Science and featuring contributions from more than 40 innovation experts and thought leaders, Global Innovation Science Handbook presents a proven approach for understanding and implementing innovation in any industry. This pioneering work is based on a defined body of knowledge that includes intent, methodology, tools, and measurements. It challenges the popular paradigm that "learned" innovation is impossible, and lays out a systematic process for developing innovation skills. Each chapter can be independently read and utilized in the daily practice of innovation. Real-world case studies from financial, government, and education sectors illustrate the concepts discussed in this definitive resource. Global Innovation Science Handbook covers: Preparing for innovation--establishing a framework and creating a culture for innovation Key innovation concepts, such as creativity, neuroscience, biomimetics, benchmarking, and ethnography Creativity tools, including Kano analysis, storyboarding, absence thinking, Lotus Blossom, SCAMPER, and others Techniques essential to innovation science, such as Six Thinking Hats, mind mapping, social networks, market research, and lead user analysis Innovation radar, indices, and other measurements Idea management--the process of creating, screening, exploring, and evaluating ideas to bring those most valuable from concept to reality Innovation methodologies, including TRIZ, Brinnovation, crowdsourcing, Eureka, stage gate, and others Deployment--a life-cycle approach involving inspiration, strategy, organization, excellence, culture, measurement, protection of intellectual property, and launch Case studies featuring cutting-edge technological innovations in finance, government, and education
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