Penalty, Shrinkage and Pretest Strategies
Penalty, Shrinkage and Pretest Strategies

Author: S. Ejaz Ahmed

Publisher: Springer Science & Business Media

Published: 2013-12-11

Total Pages: 122

ISBN-13: 331903149X

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The objective of this book is to compare the statistical properties of penalty and non-penalty estimation strategies for some popular models. Specifically, it considers the full model, submodel, penalty, pretest and shrinkage estimation techniques for three regression models before presenting the asymptotic properties of the non-penalty estimators and their asymptotic distributional efficiency comparisons. Further, the risk properties of the non-penalty estimators and penalty estimators are explored through a Monte Carlo simulation study. Showcasing examples based on real datasets, the book will be useful for students and applied researchers in a host of applied fields. The book’s level of presentation and style make it accessible to a broad audience. It offers clear, succinct expositions of each estimation strategy. More importantly, it clearly describes how to use each estimation strategy for the problem at hand. The book is largely self-contained, as are the individual chapters, so that anyone interested in a particular topic or area of application may read only that specific chapter. The book is specially designed for graduate students who want to understand the foundations and concepts underlying penalty and non-penalty estimation and its applications. It is well-suited as a textbook for senior undergraduate and graduate courses surveying penalty and non-penalty estimation strategies, and can also be used as a reference book for a host of related subjects, including courses on meta-analysis. Professional statisticians will find this book to be a valuable reference work, since nearly all chapters are self-contained.

Proceedings of the Tenth International Conference on Management Science and Engineering Management
Proceedings of the Tenth International Conference on Management Science and Engineering Management

Author: Jiuping Xu

Publisher: Springer

Published: 2016-08-23

Total Pages: 1697

ISBN-13: 9811018375

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This book presents the proceedings of the Tenth International Conference on Management Science and Engineering Management (ICMSEM2016) held from August 30 to September 02, 2016 at Baku, Azerbaijan and organized by the International Society of Management Science and Engineering Management, Sichuan University (Chengdu, China) and Ministry of Education of Azerbaijan. The aim of conference was to foster international research collaborations in management science and engineering management as well as to provide a forum to present current research findings. The presented papers were selected and reviewed by the Program Committee, made up of respected experts in the area of management science and engineering management from around the globe. The contributions focus on identifying management science problems in engineering, innovatively using management theory and methods to solve engineering problems effectively and establishing novel management theories and methods to address new engineering management issues.

Proceedings of the Thirteenth International Conference on Management Science and Engineering Management
Proceedings of the Thirteenth International Conference on Management Science and Engineering Management

Author: Jiuping Xu

Publisher: Springer

Published: 2019-06-19

Total Pages: 837

ISBN-13: 3030212483

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This book gathers the proceedings of the 13th International Conference on Management Science and Engineering Management (ICMSEM 2019), which was held at Brock University, Ontario, Canada on August 5–8, 2019. Exploring the latest ideas and pioneering research achievements in management science and engineering management, the respective contributions highlight both theoretical and practical studies on management science and computing methodologies, and present advanced management concepts and computing technologies for decision-making problems involving large, uncertain and unstructured data. Accordingly, the proceedings offer researchers and practitioners in related fields an essential update, as well as a source of new research directions.

Matrices, Statistics and Big Data
Matrices, Statistics and Big Data

Author: S. Ejaz Ahmed

Publisher: Springer

Published: 2019-08-02

Total Pages: 198

ISBN-13: 3030175197

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This volume features selected, refereed papers on various aspects of statistics, matrix theory and its applications to statistics, as well as related numerical linear algebra topics and numerical solution methods, which are relevant for problems arising in statistics and in big data. The contributions were originally presented at the 25th International Workshop on Matrices and Statistics (IWMS 2016), held in Funchal (Madeira), Portugal on June 6-9, 2016. The IWMS workshop series brings together statisticians, computer scientists, data scientists and mathematicians, helping them better understand each other’s tools, and fostering new collaborations at the interface of matrix theory and statistics.

Proceedings of the Eleventh International Conference on Management Science and Engineering Management
Proceedings of the Eleventh International Conference on Management Science and Engineering Management

Author: Jiuping Xu

Publisher: Springer

Published: 2017-06-27

Total Pages: 1808

ISBN-13: 3319592807

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This book is organized in 2 volumes and 6 parts. Part I is Big Data Analytics, which is about new advances of analysis, statistics, coordination and data mining of big data; Part II is Information Systems Management, which is about the development of big data information system or cloud platform. Part III is Computing Methodology with Big Data, which is about the improvements of traditional computation technologies in the background of big data; Part IV is Uncertainty Decision Making, which is about the decision making methods with various uncertain information, such as fuzzy, random, rough, gray, unascertained. Part V is Intelligence Algorithm. Part VI is Data Security, which is a particularly important aspect in the modern management environment.

Proceedings of the Twelfth International Conference on Management Science and Engineering Management
Proceedings of the Twelfth International Conference on Management Science and Engineering Management

Author: Jiuping Xu

Publisher: Springer

Published: 2018-06-25

Total Pages: 1752

ISBN-13: 3319933515

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This proceedings book is divided in 2 Volumes and 8 Parts. Part I is dedicated to Decision Support System, which is about the information system that supports business or organizational decision-making activities; Part II is on Computing Methodology, which is always used to provide the most effective algorithm for numerical solutions of various modeling problems; Part III presents Information Technology, which is the application of computers to store, study, retrieve, transmit and manipulate data, or information in the context of a business or other enterprise; Part IV is dedicated to Data Analysis, which is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making; Part V presents papers on Operational Management, which is about the plan, organization, implementation and control of the operation process; Part VI is on Project Management, which is about the initiating, planning, executing, controlling, and closing the work of a team to achieve specific goals and meet specific success criteria at the specified time in the field of engineering; Part VII presents Green Supply Chain, which is about the management of the flow of goods and services based on the concept of “low-carbon”; Part VIII is focused on Industry Strategy Management, which refers to the decision-making and management art of an industry or organization in a long-term and long-term development direction, objectives, tasks and policies, as well as resource allocation.

Proceedings of the Ninth International Conference on Management Science and Engineering Management
Proceedings of the Ninth International Conference on Management Science and Engineering Management

Author: Jiuping Xu

Publisher: Springer

Published: 2015-05-20

Total Pages: 1559

ISBN-13: 3662472414

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This is the Proceedings of the Ninth International Conference on Management Science and Engineering Management (ICMSEM) held from July 21-23, 2015 at Karlsruhe, Germany. The goals of the conference are to foster international research collaborations in Management Science and Engineering Management as well as to provide a forum to present current findings. These proceedings cover various areas in management science and engineering management. It focuses on the identification of management science problems in engineering and innovatively using management theory and methods to solve engineering problems effectively. It also establishes a new management theory and methods based on experience of new management issues in engineering. Readers interested in the fields of management science and engineering management will benefit from the latest cutting-edge innovations and research advances presented in these proceedings and will find new ideas and research directions. A total number of 132 papers from 15 countries are selected for the proceedings by the conference scientific committee through rigorous referee review. The selected papers in the first volume are focused on Intelligent System and Management Science covering areas of Intelligent Systems, Logistics Engineering, Information Technology and Risk Management. The selected papers in the second volume are focused on Computing and Engineering Management covering areas of Computing Methodology, Project Management, Industrial Engineering and Decision Making Systems.

Post-Shrinkage Strategies in Statistical and Machine Learning for High Dimensional Data
Post-Shrinkage Strategies in Statistical and Machine Learning for High Dimensional Data

Author: Syed Ejaz Ahmed

Publisher: CRC Press

Published: 2023-05-25

Total Pages: 409

ISBN-13: 1000876659

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This book presents some post-estimation and predictions strategies for the host of useful statistical models with applications in data science. It combines statistical learning and machine learning techniques in a unique and optimal way. It is well-known that machine learning methods are subject to many issues relating to bias, and consequently the mean squared error and prediction error may explode. For this reason, we suggest shrinkage strategies to control the bias by combining a submodel selected by a penalized method with a model with many features. Further, the suggested shrinkage methodology can be successfully implemented for high dimensional data analysis. Many researchers in statistics and medical sciences work with big data. They need to analyse this data through statistical modelling. Estimating the model parameters accurately is an important part of the data analysis. This book may be a repository for developing improve estimation strategies for statisticians. This book will help researchers and practitioners for their teaching and advanced research, and is an excellent textbook for advanced undergraduate and graduate courses involving shrinkage, statistical, and machine learning. The book succinctly reveals the bias inherited in machine learning method and successfully provides tools, tricks and tips to deal with the bias issue. Expertly sheds light on the fundamental reasoning for model selection and post estimation using shrinkage and related strategies. This presentation is fundamental, because shrinkage and other methods appropriate for model selection and estimation problems and there is a growing interest in this area to fill the gap between competitive strategies. Application of these strategies to real life data set from many walks of life. Analytical results are fully corroborated by numerical work and numerous worked examples are included in each chapter with numerous graphs for data visualization. The presentation and style of the book clearly makes it accessible to a broad audience. It offers rich, concise expositions of each strategy and clearly describes how to use each estimation strategy for the problem at hand. This book emphasizes that statistics/statisticians can play a dominant role in solving Big Data problems, and will put them on the precipice of scientific discovery. The book contributes novel methodologies for HDDA and will open a door for continued research in this hot area. The practical impact of the proposed work stems from wide applications. The developed computational packages will aid in analyzing a broad range of applications in many walks of life.

Big Data and Information Theory
Big Data and Information Theory

Author: Jiuping Xu

Publisher: Routledge

Published: 2022-06-02

Total Pages: 128

ISBN-13: 1000591719

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Big Data and Information Theory are a binding force between various areas of knowledge that allow for societal advancement. Rapid development of data analytic and information theory allows companies to store vast amounts of information about production, inventory, service, and consumer activities. More powerful CPUs and cloud computing make it possible to do complex optimization instead of using heuristic algorithms, as well as instant rather than offline decision-making. The era of "big data" challenges includes analysis, capture, curation, search, sharing, storage, transfer, visualization, and privacy violations. Big data calls for better integration of optimization, statistics, and data mining. In response to these challenges this book brings together leading researchers and engineers to exchange and share their experiences and research results about big data and information theory applications in various areas. This book covers a broad range of topics including statistics, data mining, data warehouse implementation, engineering management in large-scale infrastructure systems, data-driven sustainable supply chain network, information technology service offshoring project issues, online rumors governance, preliminary cost estimation, and information system project selection. The chapters in this book were originally published in the journal, International Journal of Management Science and Engineering Management.