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Author : Jos M. F. ten Berge
Publisher :
ISBN 13 : 9789066950832
Total Pages : 88 pages
Book Rating : 4.9/5 (58 download)
Download or read book Least Squares Optimization in Multivariate Analysis written by Jos M. F. ten Berge and published by . This book was released on 1993 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ian Cox
Publisher : SAS Institute
ISBN 13 : 1629590924
Total Pages : 308 pages
Book Rating : 4.6/5 (295 download)
Download or read book Discovering Partial Least Squares with JMP written by Ian Cox and published by SAS Institute. This book was released on 2013-10 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using JMP statistical discovery software from SAS, Discovering Partial Least Squares with JMP explores Partial Least Squares and positions it within the more general context of multivariate analysis. This book motivates current and potential users of JMP to extend their analytical repertoire by embracing PLS. Dynamically interacting with JMP, you will develop confidence as you explore underlying concepts and work through the examples. The authors provide background and guidance to support and empower you on this journey.
Author : Sadanori Konishi
Publisher : CRC Press
ISBN 13 : 1466567295
Total Pages : 338 pages
Book Rating : 4.4/5 (665 download)
Download or read book Introduction to Multivariate Analysis written by Sadanori Konishi and published by CRC Press. This book was released on 2014-06-06 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Select the Optimal Model for Interpreting Multivariate DataIntroduction 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 procedu
Author : Christiaan Heij
Publisher : OUP Oxford
ISBN 13 : 0191608408
Total Pages : 816 pages
Book Rating : 4.1/5 (916 download)
Download or read book Econometric Methods with Applications in Business and Economics written by Christiaan Heij and published by OUP Oxford. This book was released on 2004-03-25 with total page 816 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays applied work in business and economics requires a solid understanding of econometric methods to support decision-making. Combining a solid exposition of econometric methods with an application-oriented approach, this rigorous textbook provides students with a working understanding and hands-on experience of current econometrics. Taking a 'learning by doing' approach, it covers basic econometric methods (statistics, simple and multiple regression, nonlinear regression, maximum likelihood, and generalized method of moments), and addresses the creative process of model building with due attention to diagnostic testing and model improvement. Its last part is devoted to two major application areas: the econometrics of choice data (logit and probit, multinomial and ordered choice, truncated and censored data, and duration data) and the econometrics of time series data (univariate time series, trends, volatility, vector autoregressions, and a brief discussion of SUR models, panel data, and simultaneous equations). · Real-world text examples and practical exercise questions stimulate active learning and show how econometrics can solve practical questions in modern business and economic management. · Focuses on the core of econometrics, regression, and covers two major advanced topics, choice data with applications in marketing and micro-economics, and time series data with applications in finance and macro-economics. · Learning-support features include concise, manageable sections of text, frequent cross-references to related and background material, summaries, computational schemes, keyword lists, suggested further reading, exercise sets, and online data sets and solutions. · Derivations and theory exercises are clearly marked for students in advanced courses. This textbook is perfect for advanced undergraduate students, new graduate students, and applied researchers in econometrics, business, and economics, and for researchers in other fields that draw on modern applied econometrics.
Author : Fouad Sabry
Publisher : One Billion Knowledgeable
ISBN 13 :
Total Pages : 133 pages
Book Rating : 4.:/5 (661 download)
Download or read book Least Squares written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2024-05-11 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is Least Squares The method of least squares is a parameter estimation method in regression analysis based on minimizing the sum of the squares of the residuals made in the results of each individual equation. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Least squares Chapter 2: Gauss-Markov theorem Chapter 3: Regression analysis Chapter 4: Ridge regression Chapter 5: Total least squares Chapter 6: Ordinary least squares Chapter 7: Weighted least squares Chapter 8: Simple linear regression Chapter 9: Generalized least squares Chapter 10: Linear least squares (II) Answering the public top questions about least squares. (III) Real world examples for the usage of least squares in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Least Squares.
Author : Sabine Van Huffel
Publisher : SIAM
ISBN 13 : 0898712750
Total Pages : 302 pages
Book Rating : 4.8/5 (987 download)
Download or read book The Total Least Squares Problem written by Sabine Van Huffel and published by SIAM. This book was released on 1991-01-01 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book devoted entirely to total least squares. The authors give a unified presentation of the TLS problem. A description of its basic principles are given, the various algebraic, statistical and sensitivity properties of the problem are discussed, and generalizations are presented. Applications are surveyed to facilitate uses in an even wider range of applications. Whenever possible, comparison is made with the well-known least squares methods. A basic knowledge of numerical linear algebra, matrix computations, and some notion of elementary statistics is required of the reader; however, some background material is included to make the book reasonably self-contained.
Author : R. Dennis Cook
Publisher : CRC Press
ISBN 13 : 1040051324
Total Pages : 448 pages
Book Rating : 4.0/5 (4 download)
Download or read book Partial Least Squares Regression written by R. Dennis Cook and published by CRC Press. This book was released on 2024-07-17 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Partial least squares (PLS) regression is, at its historical core, a black-box algorithmic method for dimension reduction and prediction based on an underlying linear relationship between a possibly vector-valued response and a number of predictors. Through envelopes, much more has been learned about PLS regression, resulting in a mass of information that allows an envelope bridge that takes PLS regression from a black-box algorithm to a core statistical paradigm based on objective function optimization and, more generally, connects the applied sciences and statistics in the context of PLS. This book focuses on developing this bridge. It also covers uses of PLS outside of linear regression, including discriminant analysis, non-linear regression, generalized linear models and dimension reduction generally. Key Features: • Showcases the first serviceable method for studying high-dimensional regressions. • Provides necessary background on PLS and its origin. • R and Python programs are available for nearly all methods discussed in the book. This book can be used as a reference and as a course supplement at the Master's level in Statistics and beyond. It will be of interest to both statisticians and applied scientists.
Author : J. Arthur Woodward
Publisher :
ISBN 13 :
Total Pages : 28 pages
Book Rating : 4.:/5 (955 download)
Download or read book Least Squares Multivariate Analysis of Variance in Hierarchical Experimental Designs written by J. Arthur Woodward and published by . This book was released on 1974 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Craig Saunders
Publisher : Springer Science & Business Media
ISBN 13 : 3540341374
Total Pages : 218 pages
Book Rating : 4.5/5 (43 download)
Download or read book Subspace, Latent Structure and Feature Selection written by Craig Saunders and published by Springer Science & Business Media. This book was released on 2006-05-16 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many of the papers in this proceedings volume were presented at the PASCAL Workshop entitled Subspace, Latent Structure and Feature Selection Techniques: Statistical and Optimization Perspectives which took place in Bohinj, Slovenia during February, 23–25 2005.
Author : Calyampudi Radhakrishna Rao
Publisher : Springer Science & Business Media
ISBN 13 : 0387988483
Total Pages : 439 pages
Book Rating : 4.3/5 (879 download)
Download or read book Linear Models written by Calyampudi Radhakrishna Rao and published by Springer Science & Business Media. This book was released on 1999 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an up-to-date account of the theory and applications of linear models. It can be used as a text for courses in statistics at the graduate level as well as an accompanying text for other courses in which linear models play a part. The authors present a unified theory of inference from linear models with minimal assumptions, not only through least squares theory, but also using alternative methods of estimation and testing based on convex loss functions and general estimating equations. The bookincludes a discussion of: -- sensitivity analysis and model selection -- incomplete data sets including regression diagnostics to identify Non-MCAR-processes -- the analysis of categorical data based on a unified presentation of generalized linear models including GEE-methods for correlated response. An extensive appendix on matrix theory will be useful to researchers in econometrics, engineering, and optimization theory.
Author : Howard Mark
Publisher : Academic Press
ISBN 13 : 0128053305
Total Pages : 1090 pages
Book Rating : 4.1/5 (28 download)
Download or read book Chemometrics in Spectroscopy written by Howard Mark and published by Academic Press. This book was released on 2018-07-13 with total page 1090 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chemometrics in Spectroscopy, Second Edition, provides the reader with the methodology crucial to apply chemometrics to real world data. It allows scientists using spectroscopic instruments to find explanations and solutions to their problems when they are confronted with unexpected and unexplained results. Unlike other books on these topics, it explains the root causes of the phenomena that lead to these results. While books on NIR spectroscopy sometimes cover basic chemometrics, they do not mention many of the advanced topics this book discusses. In addition, traditional chemometrics books do not cover spectroscopy to the point of understanding the basis for the underlying phenomena. The second edition has been expanded with 50% more content covering advances in the field that have occurred in the last 10 years, including calibration transfer, units of measure in spectroscopy, principal components, clinical data reporting, classical least squares, regression models, spectral transfer, and more. Written in the column format of the authors’ online magazine Presents topical and important chapters for those involved in analysis work, both research and routine Focuses on practical issues in the implementation of chemometrics for NIR Spectroscopy Includes a companion website with 350 additional color figures that illustrate CLS concepts
Author : David Birkes
Publisher : John Wiley & Sons
ISBN 13 : 1118150244
Total Pages : 248 pages
Book Rating : 4.1/5 (181 download)
Download or read book Alternative Methods of Regression written by David Birkes and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Of related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald G. Watts ".an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models.highly recommend[ed].for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models." --Technometrics This book provides a balance between theory and practice supported by extensive displays of instructive geometrical constructs. Numerous in-depth case studies illustrate the use of nonlinear regression analysis--with all data sets real. Topics include: multi-response parameter estimation; models defined by systems of differential equations; and improved methods for presenting inferential results of nonlinear analysis. 1988 (0-471-81643-4) 365 pp. Nonlinear Regression G. A. F. Seber and C. J. Wild ".[a] comprehensive and scholarly work.impressively thorough with attention given to every aspect of the modeling process." --Short Book Reviews of the International Statistical Institute In this introduction to nonlinear modeling, the authors examine a wide range of estimation techniques including least squares, quasi-likelihood, and Bayesian methods, and discuss some of the problems associated with estimation. The book presents new and important material relating to the concept of curvature and its growing role in statistical inference. It also covers three useful classes of models --growth, compartmental, and multiphase --and emphasizes the limitations involved in fitting these models. Packed with examples and graphs, it offers statisticians, statistical consultants, and statistically oriented research scientists up-to-date access to their fields. 1989 (0-471-61760-1) 768 pp. Mathematical Programming in Statistics T. S. Arthanari and Yadolah Dodge "The authors have achieved their stated intention.in an outstanding and useful manner for both students and researchers.Contains a superb synthesis of references linked to the special topics and formulations by a succinct set of bibliographical notes.Should be in the hands of all system analysts and computer system architects." --Computing Reviews This unique book brings together most of the available results on applications of mathematical programming in statistics, and also develops the necessary statistical and programming theory and methods. 1981 (0-471-08073-X) 413 pp.
Author : Kohei Adachi
Publisher : Springer Nature
ISBN 13 : 9811541035
Total Pages : 457 pages
Book Rating : 4.8/5 (115 download)
Download or read book Matrix-Based Introduction to Multivariate Data Analysis written by Kohei Adachi and published by Springer Nature. This book was released on 2020-05-20 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first textbook that allows readers who may be unfamiliar with matrices to understand a variety of multivariate analysis procedures in matrix forms. By explaining which models underlie particular procedures and what objective function is optimized to fit the model to the data, it enables readers to rapidly comprehend multivariate data analysis. Arranged so that readers can intuitively grasp the purposes for which multivariate analysis procedures are used, the book also offers clear explanations of those purposes, with numerical examples preceding the mathematical descriptions. Supporting the modern matrix formulations by highlighting singular value decomposition among theorems in matrix algebra, this book is useful for undergraduate students who have already learned introductory statistics, as well as for graduate students and researchers who are not familiar with matrix-intensive formulations of multivariate data analysis. The book begins by explaining fundamental matrix operations and the matrix expressions of elementary statistics. Then, it offers an introduction to popular multivariate procedures, with each chapter featuring increasing advanced levels of matrix algebra. Further the book includes in six chapters on advanced procedures, covering advanced matrix operations and recently proposed multivariate procedures, such as sparse estimation, together with a clear explication of the differences between principal components and factor analyses solutions. In a nutshell, this book allows readers to gain an understanding of the latest developments in multivariate data science.
Author : M. R. Osborne
Publisher :
ISBN 13 :
Total Pages : 408 pages
Book Rating : 4.3/5 (91 download)
Download or read book Finite Algorithms in Optimization and Data Analysis written by M. R. Osborne and published by . This book was released on 1985-12-23 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significance and originality of this book derive from its novel approach to those optimization problems in which an active set strategy leads to a finite algorithm, such as linear and quadratic programming or l1 and l approximations.
Author : Debasis Sengupta
Publisher : World Scientific
ISBN 13 : 9789812564900
Total Pages : 652 pages
Book Rating : 4.5/5 (649 download)
Download or read book Linear Models written by Debasis Sengupta and published by World Scientific. This book was released on 2003 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear Models: An Integrated Approach aims to provide a clearand deep understanding of the general linear model using simplestatistical ideas. Elegant geometric arguments are also invoked asneeded and a review of vector spaces and matrices is provided to makethe treatment self-contained.
Author : Nickolay Trendafilov
Publisher : Springer Nature
ISBN 13 : 3030769747
Total Pages : 467 pages
Book Rating : 4.0/5 (37 download)
Download or read book Multivariate Data Analysis on Matrix Manifolds written by Nickolay Trendafilov and published by Springer Nature. This book was released on 2021-09-15 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: This graduate-level textbook aims to give a unified presentation and solution of several commonly used techniques for multivariate data analysis (MDA). Unlike similar texts, it treats the MDA problems as optimization problems on matrix manifolds defined by the MDA model parameters, allowing them to be solved using (free) optimization software Manopt. The book includes numerous in-text examples as well as Manopt codes and software guides, which can be applied directly or used as templates for solving similar and new problems. The first two chapters provide an overview and essential background for studying MDA, giving basic information and notations. Next, it considers several sets of matrices routinely used in MDA as parameter spaces, along with their basic topological properties. A brief introduction to matrix (Riemannian) manifolds and optimization methods on them with Manopt complete the MDA prerequisite. The remaining chapters study individual MDA techniques in depth. The number of exercises complement the main text with additional information and occasionally involve open and/or challenging research questions. Suitable fields include computational statistics, data analysis, data mining and data science, as well as theoretical computer science, machine learning and optimization. It is assumed that the readers have some familiarity with MDA and some experience with matrix analysis, computing, and optimization.
Author : Ana Patricia Ferreira
Publisher : Academic Press
ISBN 13 : 012811066X
Total Pages : 465 pages
Book Rating : 4.1/5 (281 download)
Download or read book Multivariate Analysis in the Pharmaceutical Industry written by Ana Patricia Ferreira and published by Academic Press. This book was released on 2018-04-24 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate Analysis in the Pharmaceutical Industry provides industry practitioners with guidance on multivariate data methods and their applications over the lifecycle of a pharmaceutical product, from process development, to routine manufacturing, focusing on the challenges specific to each step. It includes an overview of regulatory guidance specific to the use of these methods, along with perspectives on the applications of these methods that allow for testing, monitoring and controlling products and processes. The book seeks to put multivariate analysis into a pharmaceutical context for the benefit of pharmaceutical practitioners, potential practitioners, managers and regulators. Users will find a resources that addresses an unmet need on how pharmaceutical industry professionals can extract value from data that is routinely collected on products and processes, especially as these techniques become more widely used, and ultimately, expected by regulators. Targets pharmaceutical industry practitioners and regulatory staff by addressing industry specific challenges Includes case studies from different pharmaceutical companies and across product lifecycle of to introduce readers to the breadth of applications Contains information on the current regulatory framework which will shape how multivariate analysis (MVA) is used in years to come
