Discriminant Analysis And Applications

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Discriminant Analysis and Applications

Author : T. Cacoullos
Publisher : Academic Press
ISBN 13 : 1483268713
Total Pages : 455 pages
Book Rating : 4.4/5 (832 download)

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Book Synopsis Discriminant Analysis and Applications by : T. Cacoullos

Download or read book Discriminant Analysis and Applications written by T. Cacoullos and published by Academic Press. This book was released on 2014-05-10 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discriminant Analysis and Applications comprises the proceedings of the NATO Advanced Study Institute on Discriminant Analysis and Applications held in Kifissia, Athens, Greece in June 1972. The book presents the theory and applications of Discriminant analysis, one of the most important areas of multivariate statistical analysis. This volume contains chapters that cover the historical development of discriminant analysis methods; logistic and quasi-linear discrimination; and distance functions. Medical and biological applications, and computer graphical analysis and graphical techniques for multidimensional data are likewise discussed. Statisticians, mathematicians, and biomathematicians will find the book very interesting.

Applied MANOVA and Discriminant Analysis

Author : Carl J. Huberty
Publisher : John Wiley & Sons
ISBN 13 : 0471789461
Total Pages : 524 pages
Book Rating : 4.4/5 (717 download)

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Book Synopsis Applied MANOVA and Discriminant Analysis by : Carl J. Huberty

Download or read book Applied MANOVA and Discriminant Analysis written by Carl J. Huberty and published by John Wiley & Sons. This book was released on 2006-05-12 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete introduction to discriminant analysis--extensively revised, expanded, and updated This Second Edition of the classic book, Applied Discriminant Analysis, reflects and references current usage with its new title, Applied MANOVA and Discriminant Analysis. Thoroughly updated and revised, this book continues to be essential for any researcher or student needing to learn to speak, read, and write about discriminant analysis as well as develop a philosophy of empirical research and data analysis. Its thorough introduction to the application of discriminant analysis is unparalleled. Offering the most up-to-date computer applications, references, terms, and real-life research examples, the Second Edition also includes new discussions of MANOVA, descriptive discriminant analysis, and predictive discriminant analysis. Newer SAS macros are included, and graphical software with data sets and programs are provided on the book's related Web site. The book features: Detailed discussions of multivariate analysis of variance and covariance An increased number of chapter exercises along with selected answers Analyses of data obtained via a repeated measures design A new chapter on analyses related to predictive discriminant analysis Basic SPSS(r) and SAS(r) computer syntax and output integrated throughout the book Applied MANOVA and Discriminant Analysis enables the reader to become aware of various types of research questions using MANOVA and discriminant analysis; to learn the meaning of this field's concepts and terms; and to be able to design a study that uses discriminant analysis through topics such as one-factor MANOVA/DDA, assessing and describing MANOVA effects, and deleting and ordering variables.

Discriminant Analysis

Author : William R. Klecka
Publisher : SAGE
ISBN 13 : 9780803914919
Total Pages : 76 pages
Book Rating : 4.9/5 (149 download)

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Book Synopsis Discriminant Analysis by : William R. Klecka

Download or read book Discriminant Analysis written by William R. Klecka and published by SAGE. This book was released on 1980-08 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: Background. Deriving the canonical discriminant functions. Interpreting the canonical discriminant functions. Classification procedures. Stepwise inclusion of variables. Concluding remarks.

Applied Discriminant Analysis

Author : Carl J. Huberty
Publisher : Wiley-Interscience
ISBN 13 :
Total Pages : 504 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Applied Discriminant Analysis by : Carl J. Huberty

Download or read book Applied Discriminant Analysis written by Carl J. Huberty and published by Wiley-Interscience. This book was released on 1994-08-11 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most books on discriminant analysis focus on statistical theory. But properly applied, discriminant analysis methods can be enormously useful in the interpretation of data. This book is the first ever to offer a complete introduction to discriminant analysis that focuses on applications. It provides numerous examples, explained in great detail, using current statistical discriminant analysis algorithms. It also develops several themes that will be useful to researchers and students regardless of the analytical methods they employ. They are the careful examination of data prior to final analysis; the application of critical judgment and common sense to all analyses and interpretations; and conducting multiple analyses as a matter of routine. To encourage and enable readers to conduct multiple analyses of their data, the accompanying diskette contains the four complete data sets and five special computer programs that are referred to repeatedly in the text and are the subjects of numerous exercise problems. This enables the reader to carry out package analyses on the data sets using a variety of procedural options both within and across computer packages. The term "discriminant analysis" means different things to different people. For statisticians and researchers in the physical sciences, it usually denotes the process through which group membership is predicted on the basis of multiple predictor variables. Behavioral scientists, on the other hand, often use discriminant analysis to describe group differences across multiple response variables. Though closely related, predictive discriminant analysis (PDA) and descriptive discriminant analysis (DDA) are used for different purposes and should be approached in different ways. To accentuate these differences and distinguish clearly between the two, Applied Discriminant Analysis presents these topics separately. For graduate students, this book will expand your background in multivariate data analysis methods and facilitate both the reading and the conducting of applied empirical research. It will also be of great use to experienced researchers who wish to enhance or update their quantitative background, and to methodologists who want to learn more about the details of applied discriminant data analysis, and some still unresolved problems, as well.

Biometric Image Discrimination Technologies

Author : David Zhang
Publisher : IGI Global
ISBN 13 : 159140830X
Total Pages : 375 pages
Book Rating : 4.5/5 (914 download)

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Book Synopsis Biometric Image Discrimination Technologies by : David Zhang

Download or read book Biometric Image Discrimination Technologies written by David Zhang and published by IGI Global. This book was released on 2006-01-01 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The book gives an introduction to basic biometric image discrimination technologies including theories that are the foundations of those technologies and new algorithms for biometrics authentication"--Provided by publisher.

Statistics

Author : Thomas Hill
Publisher : StatSoft, Inc.
ISBN 13 : 9781884233593
Total Pages : 854 pages
Book Rating : 4.2/5 (335 download)

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Book Synopsis Statistics by : Thomas Hill

Download or read book Statistics written by Thomas Hill and published by StatSoft, Inc.. This book was released on 2006 with total page 854 pages. Available in PDF, EPUB and Kindle. Book excerpt: This - one of a kind - book offers a comprehensive, almost encyclopedic presentation of statistical methods and analytic approaches used in science, industry, business, and data mining, written from the perspective of the real-life practitioner ("consumer") of these methods.

Multi- and Megavariate Data Analysis Basic Principles and Applications

Author : L. Eriksson
Publisher : Umetrics Academy
ISBN 13 : 9197373052
Total Pages : 509 pages
Book Rating : 4.1/5 (973 download)

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Book Synopsis Multi- and Megavariate Data Analysis Basic Principles and Applications by : L. Eriksson

Download or read book Multi- and Megavariate Data Analysis Basic Principles and Applications written by L. Eriksson and published by Umetrics Academy. This book was released on 2013-07-01 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: To understand the world around us, as well as ourselves, we need to measure many things, many variables, many properties of the systems and processes we investigate. Hence, data collected in science, technology, and almost everywhere else are multivariate, a data table with multiple variables measured on multiple observations (cases, samples, items, process time points, experiments). This book describes a remarkably simple minimalistic and practical approach to the analysis of data tables (multivariate data). The approach is based on projection methods, which are PCA (principal components analysis), and PLS (projection to latent structures) and the book shows how this works in science and technology for a wide variety of applications. In particular, it is shown how the great information content in well collected multivariate data can be expressed in terms of simple but illuminating plots, facilitating the understanding and interpretation of the data. The projection approach applies to a variety of data-analytical objectives, i.e., (i) summarizing and visualizing a data set, (ii) multivariate classification and discriminant analysis, and (iii) finding quantitative relationships among the variables. This works with any shape of data table, with many or few variables (columns), many or few observations (rows), and complete or incomplete data tables (missing data). In particular, projections handle data matrices with more variables than observations very well, and the data can be noisy and highly collinear. Authors: The five authors are all connected to the Umetrics company (www.umetrics.com) which has developed and sold software for multivariate analysis since 1987, as well as supports customers with training and consultations. Umetrics' customers include most large and medium sized companies in the pharmaceutical, biopharm, chemical, and semiconductor sectors.

Topics in Applied Multivariate Analysis

Author : D. M. Hawkins
Publisher : Cambridge University Press
ISBN 13 : 9780521243681
Total Pages : 384 pages
Book Rating : 4.2/5 (436 download)

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Book Synopsis Topics in Applied Multivariate Analysis by : D. M. Hawkins

Download or read book Topics in Applied Multivariate Analysis written by D. M. Hawkins and published by Cambridge University Press. This book was released on 1982-04-22 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate methods are employed widely in the analysis of experimental data but are poorly understood by those users who are not statisticians. This is because of the wide divergence between the theory and practice of multivariate methods. This book provides concise yet thorough surveys of developments in multivariate statistical analysis and gives statistically sound coverage of the subject. The contributors are all experienced in the theory and practice of multivariate methods and their aim has been to emphasize the major features from the point of view of applicability and to indicate the limitations and conditions of the techniques. Professional statisticians wanting to improve their background in applicable methods, users of high-level statistical methods wanting to improve their background in fundamentals, and graduate students of statistics will all find this volume of value and use.

Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes)

Author : Cheng Few Lee
Publisher : World Scientific
ISBN 13 : 9811202400
Total Pages : 5053 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes) by : Cheng Few Lee

Download or read book Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes) written by Cheng Few Lee and published by World Scientific. This book was released on 2020-07-30 with total page 5053 pages. Available in PDF, EPUB and Kindle. Book excerpt: This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience.

An Introduction to Applied Multivariate Analysis with R

Author : Brian Everitt
Publisher : Springer Science & Business Media
ISBN 13 : 1441996508
Total Pages : 284 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis An Introduction to Applied Multivariate Analysis with R by : Brian Everitt

Download or read book An Introduction to Applied Multivariate Analysis with R written by Brian Everitt and published by Springer Science & Business Media. This book was released on 2011-04-23 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos. An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.

Data Analysis in Management with SPSS Software

Author : J.P. Verma
Publisher : Springer Science & Business Media
ISBN 13 : 8132207866
Total Pages : 499 pages
Book Rating : 4.1/5 (322 download)

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Book Synopsis Data Analysis in Management with SPSS Software by : J.P. Verma

Download or read book Data Analysis in Management with SPSS Software written by J.P. Verma and published by Springer Science & Business Media. This book was released on 2012-12-13 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with a greater understanding of a variety of statistical techniques along with the procedure to use the most popular statistical software package SPSS. It strengthens the intuitive understanding of the material, thereby increasing the ability to successfully analyze data in the future. The book provides more control in the analysis of data so that readers can apply the techniques to a broader spectrum of research problems. This book focuses on providing readers with the knowledge and skills needed to carry out research in management, humanities, social and behavioural sciences by using SPSS.

Systems, Decision and Control in Energy III

Author : Artur Zaporozhets
Publisher : Springer Nature
ISBN 13 : 3030876756
Total Pages : 382 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Systems, Decision and Control in Energy III by : Artur Zaporozhets

Download or read book Systems, Decision and Control in Energy III written by Artur Zaporozhets and published by Springer Nature. This book was released on 2021-11-30 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes new energy saving methods and technologies for heat power engineering. The book is devoted to topical issues of energy and related industries. Leading Ukrainian scientists from both scientific institutes and educational universities took part in its creation. The research results are presented in 6 parts: electrical engineering, heat power engineering, nuclear power engineering, fossil fuels, cybersecurity and computer science, environmental safety. Results of regulating of operating modes and applicability of model checking technique in power systems are showed. Separate block of questions regarding the functioning of nuclear power plants, their waste and preventive measures of protection against negative effects on living organisms (including, for example, the Chernobyl nuclear power plant) is considered. The results of the peculiarities of the extraction, purification and use of fossil fuels are presented. In some chapters, presented the results on improving the cybersecurity of energy systems and its resilience to various threats, including the use of 5G technology. Traditionally for this series, issues of ecological safety, the impact of different energy systems on the environment and its protection are considered. A book is for researchers, engineers, as well as lecturers and postgraduates of higher education institutions dealing with energy sector, power systems, ecological safety, etc.

Feature Learning and Understanding

Author : Haitao Zhao
Publisher : Springer Nature
ISBN 13 : 3030407942
Total Pages : 299 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Feature Learning and Understanding by : Haitao Zhao

Download or read book Feature Learning and Understanding written by Haitao Zhao and published by Springer Nature. This book was released on 2020-04-03 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the essential concepts and strategies within traditional and cutting-edge feature learning methods thru both theoretical analysis and case studies. Good features give good models and it is usually not classifiers but features that determine the effectiveness of a model. In this book, readers can find not only traditional feature learning methods, such as principal component analysis, linear discriminant analysis, and geometrical-structure-based methods, but also advanced feature learning methods, such as sparse learning, low-rank decomposition, tensor-based feature extraction, and deep-learning-based feature learning. Each feature learning method has its own dedicated chapter that explains how it is theoretically derived and shows how it is implemented for real-world applications. Detailed illustrated figures are included for better understanding. This book can be used by students, researchers, and engineers looking for a reference guide for popular methods of feature learning and machine intelligence.

Statistical Pattern Recognition

Author : Andrew R. Webb
Publisher : John Wiley & Sons
ISBN 13 : 0470854782
Total Pages : 516 pages
Book Rating : 4.4/5 (78 download)

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Book Synopsis Statistical Pattern Recognition by : Andrew R. Webb

Download or read book Statistical Pattern Recognition written by Andrew R. Webb and published by John Wiley & Sons. This book was released on 2003-07-25 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical pattern recognition is a very active area of study andresearch, which has seen many advances in recent years. New andemerging applications - such as data mining, web searching,multimedia data retrieval, face recognition, and cursivehandwriting recognition - require robust and efficient patternrecognition techniques. Statistical decision making and estimationare regarded as fundamental to the study of pattern recognition. Statistical Pattern Recognition, Second Edition has been fullyupdated with new methods, applications and references. It providesa comprehensive introduction to this vibrant area - with materialdrawn from engineering, statistics, computer science and the socialsciences - and covers many application areas, such as databasedesign, artificial neural networks, and decision supportsystems. * Provides a self-contained introduction to statistical patternrecognition. * Each technique described is illustrated by real examples. * Covers Bayesian methods, neural networks, support vectormachines, and unsupervised classification. * Each section concludes with a description of the applicationsthat have been addressed and with further developments of thetheory. * Includes background material on dissimilarity, parameterestimation, data, linear algebra and probability. * Features a variety of exercises, from 'open-book' questions tomore lengthy projects. The book is aimed primarily at senior undergraduate and graduatestudents studying statistical pattern recognition, patternprocessing, neural networks, and data mining, in both statisticsand engineering departments. It is also an excellent source ofreference for technical professionals working in advancedinformation development environments. For further information on the techniques and applicationsdiscussed in this book please visit ahref="http://www.statistical-pattern-recognition.net/"www.statistical-pattern-recognition.net/a

Multivariate Statistics for Wildlife and Ecology Research

Author : Kevin McGarigal
Publisher : Springer Science & Business Media
ISBN 13 : 146121288X
Total Pages : 293 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Multivariate Statistics for Wildlife and Ecology Research by : Kevin McGarigal

Download or read book Multivariate Statistics for Wildlife and Ecology Research written by Kevin McGarigal and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: With its focus on the practical application of the techniques of multivariate statistics, this book shapes the powerful tools of statistics for the specific needs of ecologists and makes statistics more applicable to their course of study. It gives readers a solid conceptual understanding of the role of multivariate statistics in ecological applications and the relationships among various techniques, while avoiding detailed mathematics and the underlying theory. More importantly, the reader will gain insight into the type of research questions best handled by each technique and the important considerations in applying them. Whether used as a textbook for specialised courses or as a supplement to general statistics texts, the book emphasises those techniques that students of ecology and natural resources most need to understand and employ in their research. While targeted for upper-division and graduate students in wildlife biology, forestry, and ecology, and for professional wildlife scientists and natural resource managers, this book will also be valuable to researchers in any of the biological sciences.

Applied Statistics: From Bivariate Through Multivariate Techniques

Author : Rebecca M. Warner
Publisher : SAGE
ISBN 13 : 141299134X
Total Pages : 1209 pages
Book Rating : 4.4/5 (129 download)

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Book Synopsis Applied Statistics: From Bivariate Through Multivariate Techniques by : Rebecca M. Warner

Download or read book Applied Statistics: From Bivariate Through Multivariate Techniques written by Rebecca M. Warner and published by SAGE. This book was released on 2013 with total page 1209 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rebecca M. Warner's Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked to think about the meaning of equations. Each chapter presents a complete empirical research example to illustrate the application of a specific method. Although SPSS examples are used throughout the book, the conceptual material will be helpful for users of different programs. Each chapter has a glossary and comprehension questions.

Hyperspectral Imaging Analysis and Applications for Food Quality

Author : N.C. Basantia
Publisher : CRC Press
ISBN 13 : 1351805940
Total Pages : 482 pages
Book Rating : 4.3/5 (518 download)

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Book Synopsis Hyperspectral Imaging Analysis and Applications for Food Quality by : N.C. Basantia

Download or read book Hyperspectral Imaging Analysis and Applications for Food Quality written by N.C. Basantia and published by CRC Press. This book was released on 2018-11-16 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: In processing food, hyperspectral imaging, combined with intelligent software, enables digital sorters (or optical sorters) to identify and remove defects and foreign material that are invisible to traditional camera and laser sorters. Hyperspectral Imaging Analysis and Applications for Food Quality explores the theoretical and practical issues associated with the development, analysis, and application of essential image processing algorithms in order to exploit hyperspectral imaging for food quality evaluations. It outlines strategies and essential image processing routines that are necessary for making the appropriate decision during detection, classification, identification, quantification, and/or prediction processes. Features Covers practical issues associated with the development, analysis, and application of essential image processing for food quality applications Surveys the breadth of different image processing approaches adopted over the years in attempting to implement hyperspectral imaging for food quality monitoring Explains the working principles of hyperspectral systems as well as the basic concept and structure of hyperspectral data Describes the different approaches used during image acquisition, data collection, and visualization The book is divided into three sections. Section I discusses the fundamentals of Imaging Systems: How can hyperspectral image cube acquisition be optimized? Also, two chapters deal with image segmentation, data extraction, and treatment. Seven chapters comprise Section II, which deals with Chemometrics. One explains the fundamentals of multivariate analysis and techniques while in six other chapters the reader will find information on and applications of a number of chemometric techniques: principal component analysis, partial least squares analysis, linear discriminant model, support vector machines, decision trees, and artificial neural networks. In the last section, Applications, numerous examples are given of applications of hyperspectral imaging systems in fish, meat, fruits, vegetables, medicinal herbs, dairy products, beverages, and food additives.