Transforms In Sufficient Dimension Reduction And Their Applications In High Dimensional Data
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Sufficient Dimension Reduction
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Author : Bing Li
language : en
Publisher: CRC Press
Release Date : 2018-04-27
Sufficient Dimension Reduction written by Bing Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-27 with Mathematics categories.
Sufficient dimension reduction is a rapidly developing research field that has wide applications in regression diagnostics, data visualization, machine learning, genomics, image processing, pattern recognition, and medicine, because they are fields that produce large datasets with a large number of variables. Sufficient Dimension Reduction: Methods and Applications with R introduces the basic theories and the main methodologies, provides practical and easy-to-use algorithms and computer codes to implement these methodologies, and surveys the recent advances at the frontiers of this field. Features Provides comprehensive coverage of this emerging research field. Synthesizes a wide variety of dimension reduction methods under a few unifying principles such as projection in Hilbert spaces, kernel mapping, and von Mises expansion. Reflects most recent advances such as nonlinear sufficient dimension reduction, dimension folding for tensorial data, as well as sufficient dimension reduction for functional data. Includes a set of computer codes written in R that are easily implemented by the readers. Uses real data sets available online to illustrate the usage and power of the described methods. Sufficient dimension reduction has undergone momentous development in recent years, partly due to the increased demands for techniques to process high-dimensional data, a hallmark of our age of Big Data. This book will serve as the perfect entry into the field for the beginning researchers or a handy reference for the advanced ones. The author Bing Li obtained his Ph.D. from the University of Chicago. He is currently a Professor of Statistics at the Pennsylvania State University. His research interests cover sufficient dimension reduction, statistical graphical models, functional data analysis, machine learning, estimating equations and quasilikelihood, and robust statistics. He is a fellow of the Institute of Mathematical Statistics and the American Statistical Association. He is an Associate Editor for The Annals of Statistics and the Journal of the American Statistical Association.
Transforms In Sufficient Dimension Reduction And Their Applications In High Dimensional Data
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Author : Jiaying Weng
language : en
Publisher:
Release Date : 2019
Transforms In Sufficient Dimension Reduction And Their Applications In High Dimensional Data written by Jiaying Weng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Sufficient Dimension Reduction In High Dimensional Data
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Author : Lexin Li
language : en
Publisher:
Release Date : 2003
Sufficient Dimension Reduction In High Dimensional Data written by Lexin Li and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with categories.
Festschrift In Honor Of R Dennis Cook
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Author : Efstathia Bura
language : en
Publisher: Springer Nature
Release Date : 2021-04-27
Festschrift In Honor Of R Dennis Cook written by Efstathia Bura and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-27 with Mathematics categories.
In honor of professor and renowned statistician R. Dennis Cook, this festschrift explores his influential contributions to an array of statistical disciplines ranging from experimental design and population genetics, to statistical diagnostics and all areas of regression-related inference and analysis. Since the early 1990s, Prof. Cook has led the development of dimension reduction methodology in three distinct but related regression contexts: envelopes, sufficient dimension reduction (SDR), and regression graphics. In particular, he has made fundamental and pioneering contributions to SDR, inventing or co-inventing many popular dimension reduction methods, such as sliced average variance estimation, the minimum discrepancy approach, model-free variable selection, and sufficient dimension reduction subspaces. A prolific researcher and mentor, Prof. Cook is known for his ability to identify research problems in statistics that are both challenging and important, as well as his deep appreciation for the applied side of statistics. This collection of Prof. Cook's collaborators, colleagues, friends, and former students reflects the broad array of his contributions to the research and instructional arenas of statistics.
Handbook Of Medical Statistics
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Author : Ji-qian Fang
language : en
Publisher: #N/A
Release Date : 2017-07-28
Handbook Of Medical Statistics written by Ji-qian Fang and has been published by #N/A this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-28 with Medical categories.
This unique volume focuses on the 'tools' of medical statistics. It contains over 500 concepts or methods, all of which are explained very clearly and in detail.Each chapter focuses on a specific field and its applications. There are about 20 items in each chapter with each item independent of one another and explained within one page (plus references). The structure of the book makes it extremely handy for solving targeted problems in this area.As the goal of the book is to encourage students to learn more combinatorics, every effort has been made to provide them with a not only useful, but also enjoyable and engaging reading.This handbook plays the role of 'tutor' or 'advisor' for teaching and further learning. It can also be a useful source for 'MOOC-style teaching'.
Advanced Intelligent Computing Theories And Applications With Aspects Of Artificial Intelligence
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Author : De-Shuang Huang
language : en
Publisher: Springer
Release Date : 2008-09-08
Advanced Intelligent Computing Theories And Applications With Aspects Of Artificial Intelligence written by De-Shuang Huang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-08 with Computers categories.
The International Conference on Intelligent Computing (ICIC) was formed to p- vide an annual forum dedicated to the emerging and challenging topics in artificial intelligence, machine learning, bioinformatics, and computational biology, etc. It aims to bring together researchers and practitioners from both academia and ind- try to share ideas, problems and solutions related to the multifaceted aspects of intelligent computing. ICIC 2008, held in Shanghai, China, September 15–18, 2008, constituted the 4th International Conference on Intelligent Computing. It built upon the success of ICIC 2007, ICIC 2006 and ICIC 2005 held in Qingdao, Kunming and Hefei, China, 2007, 2006 and 2005, respectively. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was “Emerging Intelligent Computing Technology and Applications”. Papers focusing on this theme were solicited, addressing theories, methodologies, and applications in science and technology.
High Dimensional Data Analysis
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Author : Tony Cai;Xiaotong Shen
language : en
Publisher:
Release Date :
High Dimensional Data Analysis written by Tony Cai;Xiaotong Shen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Over the last few years, significant developments have been taking place in highdimensional data analysis, driven primarily by a wide range of applications in many fields such as genomics and signal processing. In particular, substantial advances have been made in the areas of feature selection, covariance estimation, classification and regression. This book intends to examine important issues arising from highdimensional data analysis to explore key ideas for statistical inference and prediction. It is structured around topics on multiple hypothesis testing, feature selection, regression, cla.
Models Of Computation For Big Data
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Author : Rajendra Akerkar
language : en
Publisher: Springer
Release Date : 2018-12-04
Models Of Computation For Big Data written by Rajendra Akerkar and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-04 with Computers categories.
The 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.
Handbook Of Big Data Analytics
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Author : Wolfgang Karl Härdle
language : en
Publisher: Springer
Release Date : 2018-07-20
Handbook Of Big Data Analytics written by Wolfgang Karl Härdle and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-20 with Computers categories.
Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.
Big Data Iot And Machine Learning
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Author : Rashmi Agrawal
language : en
Publisher: CRC Press
Release Date : 2020-07-29
Big Data Iot And Machine Learning written by Rashmi Agrawal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-29 with Computers categories.
The idea behind this book is to simplify the journey of aspiring readers and researchers to understand Big Data, IoT and Machine Learning. It also includes various real-time/offline applications and case studies in the fields of engineering, computer science, information security and cloud computing using modern tools. This book consists of two sections: Section I contains the topics related to Applications of Machine Learning, and Section II addresses issues about Big Data, the Cloud and the Internet of Things. This brings all the related technologies into a single source so that undergraduate and postgraduate students, researchers, academicians and people in industry can easily understand them. Features Addresses the complete data science technologies workflow Explores basic and high-level concepts and services as a manual for those in the industry and at the same time can help beginners to understand both basic and advanced aspects of machine learning Covers data processing and security solutions in IoT and Big Data applications Offers adaptive, robust, scalable and reliable applications to develop solutions for day-to-day problems Presents security issues and data migration techniques of NoSQL databases