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.
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.
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.
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.
The present volume, The State of Local Governance: A Compendium of Deliberations - Local Governance 2020-2021, is a compilation of analytical and critical reflections and examination of the local governance policies adapted for guaranteed sustainable habitat and shelter, health, environment, education and employment. The compendium is a product of the conversation series, Local Governance, organised by IMPRI, Impact and Policy Research Institute, New Delhi. The series meditates upon existing policies, their execution, drawbacks and successive attempts for desired results in local governance. It explores the possible strategies adopted in the post-pandemic era for sustainable habitat and environment, the problems of housing in urban localities, and the role of local government in natural disaster-stricken areas. It contemplates initiatives for inclusive city planning, safe sanitation for all, disaster resilience plans and the role of people, such as the People Power Campaign (PPC) in development discourses.
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.
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.
This revised and expanded second edition is an in-depth study of the change point problem from a general point of view, as well as a further examination of change point analysis of the most commonly used statistical models. Change point problems are encountered in such disciplines as economics, finance, medicine, psychology, signal processing, and geology, to mention only several. More recently, change point analysis has been found in extensive applications related to analyzing biomedical imaging data and gene expression data. Extensive examples throughout the text emphasize key concepts and different methodologies used. New examples of change point analysis in modern molecular biology and other fields such as finance and air traffic control have been added to this second edition.
Nanoindentation of Natural Materials: Hierarchical and Functionally Graded Microstructures provides a systematic introduction and review of state-of-the-art statistical hierarchical and functionally graded structures found in bone, teeth, hair, and scales, from a nanoindentation perspective, including detailed microstructure and composition. It covers the basics of hierarchical and functionally graded structures and nanoindentation techniques and detailed discussion with correlation micro/nano mechanical-structures The book includes practical issues backed with experimental data
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.
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.
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.
This revised and expanded second edition is an in-depth study of the change point problem from a general point of view, as well as a further examination of change point analysis of the most commonly used statistical models. Change point problems are encountered in such disciplines as economics, finance, medicine, psychology, signal processing, and geology, to mention only several. More recently, change point analysis has been found in extensive applications related to analyzing biomedical imaging data and gene expression data. Extensive examples throughout the text emphasize key concepts and different methodologies used. New examples of change point analysis in modern molecular biology and other fields such as finance and air traffic control have been added to this second edition.
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.
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