Multivariate Statistical Analysis in the Real and Complex Domains PDF Download
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Author: Arak M. Mathai
Publisher: Springer Nature
ISBN: 3030958647
Category : Mathematics
Languages : en
Pages : 939
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Book Description
This book explores topics in multivariate statistical analysis, relevant in the real and complex domains. It utilizes simplified and unified notations to render the complex subject matter both accessible and enjoyable, drawing from clear exposition and numerous illustrative examples. The book features an in-depth treatment of theory with a fair balance of applied coverage, and a classroom lecture style so that the learning process feels organic. It also contains original results, with the goal of driving research conversations forward. This will be particularly useful for researchers working in machine learning, biomedical signal processing, and other fields that increasingly rely on complex random variables to model complex-valued data. It can also be used in advanced courses on multivariate analysis. Numerous exercises are included throughout.
Author: Arak M. Mathai
Publisher: Springer Nature
ISBN: 3030958647
Category : Mathematics
Languages : en
Pages : 939
Get Book Here
Book Description
This book explores topics in multivariate statistical analysis, relevant in the real and complex domains. It utilizes simplified and unified notations to render the complex subject matter both accessible and enjoyable, drawing from clear exposition and numerous illustrative examples. The book features an in-depth treatment of theory with a fair balance of applied coverage, and a classroom lecture style so that the learning process feels organic. It also contains original results, with the goal of driving research conversations forward. This will be particularly useful for researchers working in machine learning, biomedical signal processing, and other fields that increasingly rely on complex random variables to model complex-valued data. It can also be used in advanced courses on multivariate analysis. Numerous exercises are included throughout.
Author: Alan J. Izenman
Publisher: Springer Science & Business Media
ISBN: 0387781897
Category : Mathematics
Languages : en
Pages : 757
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Book Description
This is the first book on multivariate analysis to look at large data sets which describes the state of the art in analyzing such data. Material such as database management systems is included that has never appeared in statistics books before.
Author: Arakaparampil M. Mathai
Publisher:
ISBN: 9783030958657
Category : Mathematical statistics
Languages : en
Pages : 0
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Book Description
This book serves as a practical resource for start-ups looking for innovating their business models in domestic and global markets. It describes the innovative business practices adopted by start-ups during the COVID-19 pandemic, with a special emphasis on value proposition innovation and business model innovation more generally. The BMI-Pandemic 2.15 model, which is an expanded version of the Odyssey 3.14 model, is presented to highlight 15 guidelines for innovating business models during pandemics. In order to promote open innovation, this book emphasizes the value of strategic alliances with academic libraries, peer start-ups, and freelancers. Additionally, using actual start-up case studies, it demonstrates how important technological innovation is for gathering feedback, prototyping, and conducting both secondary as well as primary market research. The need of regularly experimenting with new approaches, learning from mistakes, and enhancing current processes are also emphasized in this book. Theoretical insights are linked with practical experiences of start-ups amid the pandemic. With a perfect balance of empirical research and assessment study types, this book is a source of quick knowledge for entrepreneurs, academics and researchers on how to enhance a company's innovative capacities and success rates.
Author: Joseph Hair
Publisher: Pearson Higher Ed
ISBN: 0133792684
Category : Business & Economics
Languages : en
Pages : 816
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Book Description
This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. For graduate and upper-level undergraduate marketing research courses. For over 30 years, Multivariate Data Analysis has provided readers with the information they need to understand and apply multivariate data analysis. Hair et. al provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to readers how to understand and make use of the results of specific statistical techniques. In this Seventh Edition, the organization of the chapters has been greatly simplified. New chapters have been added on structural equations modeling, and all sections have been updated to reflect advances in technology, capability, and mathematical techniques.
Author: Bipin Kumar Tripathi
Publisher: Springer
ISBN: 8132220749
Category : Technology & Engineering
Languages : en
Pages : 179
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Book Description
The book presents a coherent understanding of computational intelligence from the perspective of what is known as "intelligent computing" with high-dimensional parameters. It critically discusses the central issue of high-dimensional neurocomputing, such as quantitative representation of signals, extending the dimensionality of neuron, supervised and unsupervised learning and design of higher order neurons. The strong point of the book is its clarity and ability of the underlying theory to unify our understanding of high-dimensional computing where conventional methods fail. The plenty of application oriented problems are presented for evaluating, monitoring and maintaining the stability of adaptive learning machine. Author has taken care to cover the breadth and depth of the subject, both in the qualitative as well as quantitative way. The book is intended to enlighten the scientific community, ranging from advanced undergraduates to engineers, scientists and seasoned researchers in computational intelligence.
Author: Mohammed Al Maqbali
Publisher: Springer Nature
ISBN: 3031782984
Category :
Languages : en
Pages : 163
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Book Description
Author: Praveen Agarwal
Publisher: Elsevier
ISBN: 0443185069
Category : Science
Languages : en
Pages : 302
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Book Description
Recent Trends in Fractional Calculus and Its Applications addresses the answer to this very basic question: "Why is Fractional Calculus important?" Until recent times, Fractional Calculus was considered as a rather esoteric mathematical theory without applications, but in the last few decades there has been an explosion of research activities on the application of Fractional Calculus to very diverse scientific fields ranging from the physics of diffusion and advection phenomena, to control systems to finance and economics. An important part of mathematical modelling of objects and processes is a description of their dynamics.The term Fractional Calculus is more than 300 years old. It is a generalization of the ordinary differentiation and integration to noninteger (arbitrary) order. The subject is as old as the calculus of differentiation and goes back to times when Leibniz, Gauss, and Newton invented this kind of calculation. Several mathematicians contributed to this subject over the years. People like Liouville, Riemann, and Weyl made major contributions to the theory of Fractional Calculus. In recent decades the field of Fractional Calculus has attracted the interest of researchers in several areas, including mathematics, physics, chemistry, engineering, finance, and social sciences. - Provides the most recent and up-to-date developments in the Fractional Calculus and its application areas - Presents pre-preparation ideas to help researchers/scientists/clinicians face the new challenges in the application of fractional differential equations - Helps researchers and scientists understand the importance of the Fractional Calculus to solve many problems in Biomedical Engineering and applied sciences
Author: Matteo Grigoletto
Publisher: Springer Science & Business Media
ISBN: 884702871X
Category : Mathematics
Languages : en
Pages : 228
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Book Description
The use of computational methods in statistics to face complex problems and highly dimensional data, as well as the widespread availability of computer technology, is no news. The range of applications, instead, is unprecedented. As often occurs, new and complex data types require new strategies, demanding for the development of novel statistical methods and suggesting stimulating mathematical problems. This book is addressed to researchers working at the forefront of the statistical analysis of complex systems and using computationally intensive statistical methods.
Author: Ken Yale
Publisher: Elsevier
ISBN: 0124166458
Category : Mathematics
Languages : en
Pages : 824
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Book Description
Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. - Includes input by practitioners for practitioners - Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models - Contains practical advice from successful real-world implementations - Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions - Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications
Author: Jing Wang
Publisher: Springer Nature
ISBN: 9811680442
Category : Technology & Engineering
Languages : en
Pages : 277
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Book Description
This open access book assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and scientists from various fields such as control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a basic framework for this topic and implements various statistical analysis methods for process monitoring. This book is intended for senior undergraduate and graduate students who are interested in fault diagnosis technology, researchers investigating automation and industrial security, professional practitioners and engineers working on engineering modeling and data processing applications. This is an open access book.
