Classification : Methods for the Exploratory Analysis of Multivariate Data PDF Download
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Author: A. D. Gordon
Publisher: Chapman and Hall/CRC
ISBN:
Category : Computers
Languages : en
Pages : 218
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Book Description
Author: A. D. Gordon
Publisher: Chapman and Hall/CRC
ISBN:
Category : Computers
Languages : en
Pages : 218
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Book Description
Author: Michel Jambu
Publisher: Elsevier
ISBN: 0080923674
Category : Mathematics
Languages : en
Pages : 489
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Book Description
With a useful index of notations at the beginning, this book explains and illustrates the theory and application of data analysis methods from univariate to multidimensional and how to learn and use them efficiently. This book is well illustrated and is a useful and well-documented review of the most important data analysis techniques. - Describes, in detail, exploratory data analysis techniques from the univariate to the multivariate ones - Features a complete description of correspondence analysis and factor analysis techniques as multidimensional statistical data analysis techniques, illustrated with concrete and understandable examples - Includes a modern and up-to-date description of clustering algorithms with many properties which gives a new role of clustering in data analysis techniques
Author: A. D. Gordon
Publisher: Chapman and Hall/CRC
ISBN:
Category : Computers
Languages : en
Pages : 210
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Book Description
Author: Chikio Hayashi
Publisher: Springer Science & Business Media
ISBN: 4431659501
Category : Mathematics
Languages : en
Pages : 786
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Book Description
This volume contains selected papers covering a wide range of topics, including theoretical and methodological advances relating to data gathering, classification and clustering, exploratory and multivariate data analysis, and knowledge seeking and discovery. The result is a broad view of the state of the art, making this an essential work not only for data analysts, mathematicians, and statisticians, but also for researchers involved in data processing at all stages from data gathering to decision making.
Author: Hans-Hermann Bock
Publisher: Springer Science & Business Media
ISBN: 3642763073
Category : Business & Economics
Languages : en
Pages : 404
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Book Description
In science, industry, public administration and documentation centers large amounts of data and information are collected which must be analyzed, ordered, visualized, classified and stored efficiently in order to be useful for practical applications. This volume contains 50 selected theoretical and applied papers presenting a wealth of new and innovative ideas, methods, models and systems which can be used for this purpose. It combines papers and strategies from two main streams of research in an interdisciplinary, dynamic and exciting way: On the one hand, mathematical and statistical methods are described which allow a quantitative analysis of data, provide strategies for classifying objects or making exploratory searches for interesting structures, and give ways to make comprehensive graphical displays of large arrays of data. On the other hand, papers related to information sciences, informatics and data bank systems provide powerful tools for representing, modelling, storing and retrieving facts, data and knowledge characterized by qualitative descriptors, semantic relations, or linguistic concepts. The integration of both fields and a special part on applied problems from biology, medicine, archeology, industry and administration assure that this volume will be informative and useful for theory and practice.
Author: MIT Critical Data
Publisher: Springer
ISBN: 3319437429
Category : Medical
Languages : en
Pages : 435
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Book Description
This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.
Author: Tadashi Imaizumi
Publisher: Springer Nature
ISBN: 9811533113
Category : Mathematics
Languages : en
Pages : 506
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Book Description
This edited volume focuses on the latest developments in classification and data science and covers a wide range of topics in the context of data analysis and related areas, e.g. the analysis of complex data, analysis of qualitative data, methods for high-dimensional data, dimensionality reduction, data visualization, multivariate statistical methods, and various applications to real data in the social sciences, medical sciences, and other disciplines. In addition to sharing theoretical and methodological findings, the book shows how to apply the proposed methods to a variety of problems — e.g. in consumer behavior, decision-making, marketing data and social network structures. Both methodological aspects and applications to a wide range of areas such as economics, behavioral science, marketing science, management science and the social sciences are covered. The book is chiefly intended for researchers and practitioners who are interested in the latest developments and practical applications in these fields, as well as applied statisticians and data analysts. Its combination of methodological advances with a wide range of real-world applications gathered from several fields makes it of unique value in helping readers solve their research problems.
Author: Raghu Nandan Sengupta
Publisher: CRC Press
ISBN: 1482282569
Category : Business & Economics
Languages : en
Pages : 1042
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Book Description
This handbook is an endeavour to cover many current, relevant, and essential topics related to decision sciences in a scientific manner. Using this handbook, graduate students, researchers, as well as practitioners from engineering, statistics, sociology, economics, etc. will find a new and refreshing paradigm shift as to how these topics can be put to use beneficially. Starting from the basics to advanced concepts, authors hope to make the readers well aware of the different theoretical and practical ideas, which are the focus of study in decision sciences nowadays. It includes an excellent bibliography/reference/journal list, information about a variety of datasets, illustrated pseudo-codes, and discussion of future trends in research. Covering topics ranging from optimization, networks and games, multi-objective optimization, inventory theory, statistical methods, artificial neural networks, times series analysis, simulation modeling, decision support system, data envelopment analysis, queueing theory, etc., this reference book is an attempt to make this area more meaningful for varied readers. Noteworthy features of this handbook are in-depth coverage of different topics, solved practical examples, unique datasets for a variety of examples in the areas of decision sciences, in-depth analysis of problems through colored charts, 3D diagrams, and discussions about software.
Author: E. C. Pielou
Publisher: John Wiley & Sons
ISBN: 9780471889502
Category : Science
Languages : en
Pages : 278
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Book Description
A detailed introduction to the methods used by ecologists--classification and ordination--to clarify and interpret large, unwieldy masses of multivariate field data. Permits ecologists to understand, not just mechanically use, pre-packaged programs for multivariate analysis. Demonstrates these techniques using artificial data simple enough for every analytical step to be understood.
Author: Alvin C. Rencher
Publisher: John Wiley & Sons
ISBN: 0471461725
Category : Mathematics
Languages : en
Pages : 739
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Book Description
Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Methods of Multivariate Analysis was among those chosen. When measuring several variables on a complex experimental unit, it is often necessary to analyze the variables simultaneously, rather than isolate them and consider them individually. Multivariate analysis enables researchers to explore the joint performance of such variables and to determine the effect of each variable in the presence of the others. The Second Edition of Alvin Rencher's Methods of Multivariate Analysis provides students of all statistical backgrounds with both the fundamental and more sophisticated skills necessary to master the discipline. To illustrate multivariate applications, the author provides examples and exercises based on fifty-nine real data sets from a wide variety of scientific fields. Rencher takes a "methods" approach to his subject, with an emphasis on how students and practitioners can employ multivariate analysis in real-life situations. The Second Edition contains revised and updated chapters from the critically acclaimed First Edition as well as brand-new chapters on: Cluster analysis Multidimensional scaling Correspondence analysis Biplots Each chapter contains exercises, with corresponding answers and hints in the appendix, providing students the opportunity to test and extend their understanding of the subject. Methods of Multivariate Analysis provides an authoritative reference for statistics students as well as for practicing scientists and clinicians.
