Multivariate Statistical Modeling And Data Analysis

Author : H. Bozdogan,Arjun K. Gupta
Publisher : Springer Science & Business Media
Page : 193 pages
File Size : 40,6 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9789400939776

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Multivariate Statistical Modeling and Data Analysis by H. Bozdogan,Arjun K. Gupta Pdf

This volume contains the Proceedings of the Advanced Symposium on Multivariate Modeling and Data Analysis held at the 64th Annual Heeting of the Virginia Academy of Sciences (VAS)--American Statistical Association's Vir ginia Chapter at James Madison University in Harrisonburg. Virginia during Hay 15-16. 1986. This symposium was sponsored by financial support from the Center for Advanced Studies at the University of Virginia to promote new and modern information-theoretic statist ical modeling procedures and to blend these new techniques within the classical theory. Multivariate statistical analysis has come a long way and currently it is in an evolutionary stage in the era of high-speed computation and computer technology. The Advanced Symposium was the first to address the new innovative approaches in multi variate analysis to develop modern analytical and yet practical procedures to meet the needs of researchers and the societal need of statistics. vii viii PREFACE Papers presented at the Symposium by e1l11lJinent researchers in the field were geared not Just for specialists in statistics, but an attempt has been made to achieve a well balanced and uniform coverage of different areas in multi variate modeling and data analysis. The areas covered included topics in the analysis of repeated measurements, cluster analysis, discriminant analysis, canonical cor relations, distribution theory and testing, bivariate densi ty estimation, factor analysis, principle component analysis, multidimensional scaling, multivariate linear models, nonparametric regression, etc.

Author : Jhareswar Maiti
Publisher : CRC Press
Page : 421 pages
File Size : 40,5 Mb
Release : 2022-10-25
Category : Business & Economics
ISBN : 9781000618426

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Multivariate Statistical Modeling in Engineering and Management by Jhareswar Maiti Pdf

The book focuses on problem solving for practitioners and model building for academicians under multivariate situations. This book helps readers in understanding the issues, such as knowing variability, extracting patterns, building relationships, and making objective decisions. A large number of multivariate statistical models are covered in the book. The readers will learn how a practical problem can be converted to a statistical problem and how the statistical solution can be interpreted as a practical solution. Key features: Links data generation process with statistical distributions in multivariate domain Provides step by step procedure for estimating parameters of developed models Provides blueprint for data driven decision making Includes practical examples and case studies relevant for intended audiences The book will help everyone involved in data driven problem solving, modeling and decision making.

Author : Ludwig Fahrmeir,Gerhard Tutz
Publisher : Springer Science & Business Media
Page : 440 pages
File Size : 54,7 Mb
Release : 2013-11-11
Category : Mathematics
ISBN : 9781489900104

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Multivariate Statistical Modelling Based on Generalized Linear Models by Ludwig Fahrmeir,Gerhard Tutz Pdf

Concerned with the use of generalised linear models for univariate and multivariate regression analysis, this is a detailed introductory survey of the subject, based on the analysis of real data drawn from a variety of subjects such as the biological sciences, economics, and the social sciences. Where possible, technical details and proofs are deferred to an appendix in order to provide an accessible account for non-experts. Topics covered include: models for multi-categorical responses, model checking, time series and longitudinal data, random effects models, and state-space models. Throughout, the authors have taken great pains to discuss the underlying theoretical ideas in ways that relate well to the data at hand. As a result, numerous researchers whose work relies on the use of these models will find this an invaluable account.

Author : Michel Jambu
Publisher : Elsevier
Page : 489 pages
File Size : 41,8 Mb
Release : 1991-09-09
Category : Mathematics
ISBN : 9780080923673

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Exploratory and Multivariate Data Analysis by Michel Jambu Pdf

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 : Howard E.A. Tinsley,Steven D. Brown
Publisher : Academic Press
Page : 721 pages
File Size : 46,7 Mb
Release : 2000-05-22
Category : Mathematics
ISBN : 0080533566

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Handbook of Applied Multivariate Statistics and Mathematical Modeling by Howard E.A. Tinsley,Steven D. Brown Pdf

Multivariate statistics and mathematical models provide flexible and powerful tools essential in most disciplines. Nevertheless, many practicing researchers lack an adequate knowledge of these techniques, or did once know the techniques, but have not been able to keep abreast of new developments. The Handbook of Applied Multivariate Statistics and Mathematical Modeling explains the appropriate uses of multivariate procedures and mathematical modeling techniques, and prescribe practices that enable applied researchers to use these procedures effectively without needing to concern themselves with the mathematical basis. The Handbook emphasizes using models and statistics as tools. The objective of the book is to inform readers about which tool to use to accomplish which task. Each chapter begins with a discussion of what kinds of questions a particular technique can and cannot answer. As multivariate statistics and modeling techniques are useful across disciplines, these examples include issues of concern in biological and social sciences as well as the humanities.

Author : Isabella Morlini,Tommaso Minerva,Maurizio Vichi
Publisher : Springer
Page : 268 pages
File Size : 45,8 Mb
Release : 2015-09-04
Category : Mathematics
ISBN : 9783319173771

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Advances in Statistical Models for Data Analysis by Isabella Morlini,Tommaso Minerva,Maurizio Vichi Pdf

This edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis. The volume provides both methodological developments and contributions to a wide range of application areas such as economics, marketing, education, social sciences and environment. The papers in this volume were first presented at the 9th biannual meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in September 2013 at the University of Modena and Reggio Emilia, Italy.

Author : Andriëtte Bekker,Johannes T. Ferreira,Mohammad Arashi,Ding-Geng Chen
Publisher : Springer Nature
Page : 434 pages
File Size : 53,6 Mb
Release : 2022-12-15
Category : Mathematics
ISBN : 9783031139710

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Innovations in Multivariate Statistical Modeling by Andriëtte Bekker,Johannes T. Ferreira,Mohammad Arashi,Ding-Geng Chen Pdf

Multivariate statistical analysis has undergone a rich and varied evolution during the latter half of the 20th century. Academics and practitioners have produced much literature with diverse interests and with varying multidisciplinary knowledge on different topics within the multivariate domain. Due to multivariate algebra being of sustained interest and being a continuously developing field, its appeal breaches laterally across multiple disciplines to act as a catalyst for contemporary advances, with its core inferential genesis remaining in that of statistics. It is exactly this varied evolution caused by an influx in data production, diffusion, and understanding in scientific fields that has blurred many lines between disciplines. The cross-pollination between statistics and biology, engineering, medical science, computer science, and even art, has accelerated the vast amount of questions that statistical methodology has to answer and report on. These questions are often multivariate in nature, hoping to elucidate uncertainty on more than one aspect at the same time, and it is here where statistical thinking merges mathematical design with real life interpretation for understanding this uncertainty. Statistical advances benefit from these algebraic inventions and expansions in the multivariate paradigm. This contributed volume aims to usher novel research emanating from a multivariate statistical foundation into the spotlight, with particular significance in multidisciplinary settings. The overarching spirit of this volume is to highlight current trends, stimulate a focus on, and connect multidisciplinary dots from and within multivariate statistical analysis. Guided by these thoughts, a collection of research at the forefront of multivariate statistical thinking is presented here which has been authored by globally recognized subject matter experts.

Author : Daniel J. Denis
Publisher : John Wiley & Sons
Page : 760 pages
File Size : 47,5 Mb
Release : 2015-12-14
Category : Mathematics
ISBN : 9781118632338

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Applied Univariate, Bivariate, and Multivariate Statistics by Daniel J. Denis Pdf

A clear and efficient balance between theory and application of statistical modeling techniques in the social and behavioral sciences Written as a general and accessible introduction, Applied Univariate, Bivariate, and Multivariate Statistics provides an overview of statistical modeling techniques used in fields in the social and behavioral sciences. Blending statistical theory and methodology, the book surveys both the technical and theoretical aspects of good data analysis. Featuring applied resources at various levels, the book includes statistical techniques such as t-tests and correlation as well as more advanced procedures such as MANOVA, factor analysis, and structural equation modeling. To promote a more in-depth interpretation of statistical techniques across the sciences, the book surveys some of the technical arguments underlying formulas and equations. Applied Univariate, Bivariate, and Multivariate Statistics also features Demonstrations of statistical techniques using software packages such as R and SPSS® Examples of hypothetical and real data with subsequent statistical analyses Historical and philosophical insights into many of the techniques used in modern social science A companion website that includes further instructional details, additional data sets, solutions to selected exercises, and multiple programming options An ideal textbook for courses in statistics and methodology at the upper- undergraduate and graduate-levels in psychology, political science, biology, sociology, education, economics, communications, law, and survey research, Applied Univariate, Bivariate, and Multivariate Statistics is also a useful reference for practitioners and researchers in their field of application. DANIEL J. DENIS, PhD, is Associate Professor of Quantitative Psychology at the University of Montana where he teaches courses in univariate and multivariate statistics. He has published a number of articles in peer-reviewed journals and has served as consultant to researchers and practitioners in a variety of fields.

Author : Brian S. Everitt,Graham Dunn
Publisher : Wiley
Page : 342 pages
File Size : 40,6 Mb
Release : 2009-04-20
Category : Mathematics
ISBN : 0340741228

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Applied Multivariate Data Analysis by Brian S. Everitt,Graham Dunn Pdf

Multivariate analysis plays an important role in the understanding of complex data sets requiring simultaneous examination of all variables. Breaking through the apparent disorder of the information, it provides the means for both describing and exploring data, aiming to extract the underlying patterns and structure. This intermediate-level textbook introduces the reader to the variety of methods by which multivariate statistical analysis may be undertaken. Now in its 2nd edition, 'Applied Multivariate Data Analysis' has been fully expanded and updated, including major chapter revisions as well as new sections on neural networks and random effects models for longitudinal data. Maintaining the easy-going style of the first edition, the authors provide clear explanations of each technique, as well as supporting figures and examples, and minimal technical jargon. With extensive exercises following every chapter, 'Applied Multivariate Data Analysis' is a valuable resource for students on applied statistics courses and applied researchers in many disciplines.

Author : H. Bozdogan
Publisher : Springer Science & Business Media
Page : 421 pages
File Size : 40,8 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9789401108003

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Proceedings of the First US/Japan Conference on the Frontiers of Statistical Modeling: An Informational Approach by H. Bozdogan Pdf

Often a statistical analysis involves use of a set of alternative models for the data. A "model-selection criterion" is a formula which provides a figure-of merit for the alternative models. Generally the alternative models will involve different numhers of parameters. Model-selection criteria take into account hoth the goodness-or-fit of a model and the numher of parameters used to achieve that fit. 1.1. SETS OF ALTERNATIVE MODELS Thus the focus in this paper is on data-analytic situations ill which there is consideration of a set of alternative models. Choice of a suhset of explanatory variahles in regression, the degree of a polynomial regression, the number of factors in factor analysis, or the numher of dusters in duster analysis are examples of such situations. 1.2. MODEL SELECTION VERSUS HYPOTHESIS TESTING In exploratory data analysis or in a preliminary phase of inference an approach hased on model-selection criteria can offer advantages over tests of hypotheses. The model-selection approach avoids the prohlem of specifying error rates for the tests. With model selection the focus can he on simultaneous competition between a hroad dass of competing models rather than on consideration of a sequence of simpler and simpler models.

Author : Richard A. Johnson,Dean W. Wichern
Publisher : Pearson
Page : 808 pages
File Size : 42,7 Mb
Release : 2018-03-18
Category : Multivariate analysis
ISBN : 0134995392

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Applied Multivariate Statistical Analysis (Classic Version) by Richard A. Johnson,Dean W. Wichern Pdf

This title is part of the Pearson Modern Classics series. Pearson Modern Classics are acclaimed titles at a value price. Please visit www.pearsonhighered.com/math-classics-series for a complete list of titles. For courses in Multivariate Statistics, Marketing Research, Intermediate Business Statistics, Statistics in Education, and graduate-level courses in Experimental Design and Statistics. Appropriate for experimental scientists in a variety of disciplines, this market-leading text offers a readable introduction to the statistical analysis of multivariate observations. Its primary goal is to impart the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Ideal for a junior/senior or graduate level course that explores the statistical methods for describing and analyzing multivariate data, the text assumes two or more statistics courses as a prerequisite.

Author : Salvatore Ingrassia,Roberto Rocci,Maurizio Vichi
Publisher : Springer Science & Business Media
Page : 576 pages
File Size : 48,8 Mb
Release : 2011-06-29
Category : Mathematics
ISBN : 9783642113635

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New Perspectives in Statistical Modeling and Data Analysis by Salvatore Ingrassia,Roberto Rocci,Maurizio Vichi Pdf

This volume provides recent research results in data analysis, classification and multivariate statistics and highlights perspectives for new scientific developments within these areas. Particular attention is devoted to methodological issues in clustering, statistical modeling and data mining. The volume also contains significant contributions to a wide range of applications such as finance, marketing, and social sciences. The papers in this volume were first presented at the 7th Conference of the Classification and Data Analysis Group (ClaDAG) of the Italian Statistical Society, held at the University of Catania, Italy.

Author : Simona Balzano,Giovanni C. Porzio,Renato Salvatore,Domenico Vistocco,Maurizio Vichi
Publisher : Springer Nature
Page : 182 pages
File Size : 53,8 Mb
Release : 2021-07-13
Category : Mathematics
ISBN : 9783030699444

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Statistical Learning and Modeling in Data Analysis by Simona Balzano,Giovanni C. Porzio,Renato Salvatore,Domenico Vistocco,Maurizio Vichi Pdf

The contributions gathered in this book focus on modern methods for statistical learning and modeling in data analysis and present a series of engaging real-world applications. The book covers numerous research topics, ranging from statistical inference and modeling to clustering and factorial methods, from directional data analysis to time series analysis and small area estimation. The applications reflect new analyses in a variety of fields, including medicine, finance, engineering, marketing and cyber risk. The book gathers selected and peer-reviewed contributions presented at the 12th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2019), held in Cassino, Italy, on September 11–13, 2019. CLADAG promotes advanced methodological research in multivariate statistics with a special focus on data analysis and classification, and supports the exchange and dissemination of ideas, methodological concepts, numerical methods, algorithms, and computational and applied results. This book, true to CLADAG’s goals, is intended for researchers and practitioners who are interested in the latest developments and applications in the field of data analysis and classification.

Author : Sadanori Konishi
Publisher : CRC Press
Page : 340 pages
File Size : 40,9 Mb
Release : 2014-06-06
Category : Mathematics
ISBN : 9781466567283

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Introduction to Multivariate Analysis by Sadanori Konishi Pdf

Select the Optimal Model for Interpreting Multivariate Data Introduction to Multivariate Analysis: Linear and Nonlinear Modeling shows how multivariate analysis is widely used for extracting useful information and patterns from multivariate data and for understanding the structure of random phenomena. Along with the basic concepts of various procedures in traditional multivariate analysis, the book covers nonlinear techniques for clarifying phenomena behind observed multivariate data. It primarily focuses on regression modeling, classification and discrimination, dimension reduction, and clustering. The text thoroughly explains the concepts and derivations of the AIC, BIC, and related criteria and includes a wide range of practical examples of model selection and evaluation criteria. To estimate and evaluate models with a large number of predictor variables, the author presents regularization methods, including the L1 norm regularization that gives simultaneous model estimation and variable selection. For advanced undergraduate and graduate students in statistical science, this text provides a systematic description of both traditional and newer techniques in multivariate analysis and machine learning. It also introduces linear and nonlinear statistical modeling for researchers and practitioners in industrial and systems engineering, information science, life science, and other areas.

Author : Ronald Christensen,Ronald A. Christensen
Publisher : Entropy, Limited
Page : 814 pages
File Size : 46,5 Mb
Release : 1983
Category : Mathematical statistics
ISBN : UCAL:B3844631

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Multivariate Statistical Modeling by Ronald Christensen,Ronald A. Christensen Pdf