Introduction to Multivariate Analysis, Konishi, Sadanori
Автор: Beh Название: An Introduction to Correspondence Analysis ISBN: 1119041945 ISBN-13(EAN): 9781119041948 Издательство: Wiley Рейтинг: Цена: 54860.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Master the fundamentals of correspondence analysis with this illuminating resource
An Introduction to Correspondence Analysis assists researchers in improving their familiarity with the concepts, terminology, and application of several variants of correspondence analysis. The accomplished academics and authors deliver a comprehensive and insightful treatment of the fundamentals of correspondence analysis, including the statistical and visual aspects of the subject.
Written in three parts, the book begins by offering readers a description of two variants of correspondence analysis that can be applied to two-way contingency tables for nominal categories of variables. Part Two shifts the discussion to categories of ordinal variables and demonstrates how the ordered structure of these variables can be incorporated into a correspondence analysis. Part Three describes the analysis of multiple nominal categorical variables, including both multiple correspondence analysis and multi-way correspondence analysis.
Readers will benefit from explanations of a wide variety of specific topics, for example:
Simple correspondence analysis, including how to reduce multidimensional space, measuring symmetric associations with the Pearson Ratio, constructing low-dimensional displays, and detecting statistically significant points
Non-symmetrical correspondence analysis, including quantifying asymmetric associations
Simple ordinal correspondence analysis, including how to decompose the Pearson Residual for ordinal variables
Multiple correspondence analysis, including crisp coding and the indicator matrix, the Burt Matrix, and stacking
Multi-way correspondence analysis, including symmetric multi-way analysis
Perfect for researchers who seek to improve their understanding of key concepts in the graphical analysis of categorical data, An Introduction to Correspondence Analysis will also assist readers already familiar with correspondence analysis who wish to review the theoretical and foundational underpinnings of crucial concepts.
Автор: Adachi Kohei Название: Matrix-Based Introduction to Multivariate Data Analysis ISBN: 9811541027 ISBN-13(EAN): 9789811541025 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Elementary matrix operations.- Intravariable statistics.- Inter-variable statistics.- Regression analysis.- Principal component analysis.- Principal component.
Автор: Keith Название: Multiple Regression and Beyond ISBN: 1138061441 ISBN-13(EAN): 9781138061446 Издательство: Taylor&Francis Рейтинг: Цена: 86760.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Multiple Regression and Beyond offers a conceptually oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods.
Автор: MacKinnon, David Название: Introduction to Statistical Mediation Analysis ISBN: 0805839747 ISBN-13(EAN): 9780805839746 Издательство: Taylor&Francis Рейтинг: Цена: 142910.00 T Наличие на складе: Нет в наличии.
Автор: Chatfield, Chris Название: Introduction to Multivariate Analysis ISBN: 0412160404 ISBN-13(EAN): 9780412160400 Издательство: Taylor&Francis Рейтинг: Цена: 102080.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Adachi Kohei Название: Matrix-Based Introduction to Multivariate Data Analysis ISBN: 9811095957 ISBN-13(EAN): 9789811095955 Издательство: Springer Рейтинг: Цена: 74530.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Part 1. Elementary Statistics with Matrices.- 1 Introduction to Matrix Operations.- 2 Intra-variable Statistics.- 3 Inter-variable Statistics.- Part 2. Least Squares Procedures.- 4 Regression Analysis.- 5 Principal Component Analysis (Part 1).- 6 Principal Component Analysis 2 (Part 2).- 7 Cluster Analysis.- Part 3. Maximum Likelihood Procedures.- 8 Maximum Likelihood and Normal Distributions.- 9 Path Analysis.- 10 Confirmatory Factor Analysis.- 11 Structural Equation Modeling.- 12 Exploratory Factor Analysis.- Part 4. Miscellaneous Procedures.- 13 Rotation Techniques.- 14 Canonical Correlation and Multiple Correspondence Analyses.- 15 Discriminant Analysis.- 16 Multidimensional Scaling.- Appendices.- A1 Geometric Understanding of Matrices and Vectors.- A2 Decomposition of Sums of Squares.- A3 Singular Value Decomposition (SVD).- A4 Matrix Computation Using SVD.- A5 Supplements for Probability Densities and Likelihoods.- A6 Iterative Algorithms.- References.- Index.
Автор: Dugard, Pat Название: Approaching Multivariate Analysis, 2nd Edition ISBN: 0415478286 ISBN-13(EAN): 9780415478281 Издательство: Taylor&Francis Рейтинг: Цена: 148010.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: MacKinnon, David Название: Introduction to Statistical Mediation Analysis ISBN: 0805864296 ISBN-13(EAN): 9780805864298 Издательство: Taylor&Francis Рейтинг: Цена: 51030.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Adachi Kohei Название: Matrix-Based Introduction to Multivariate Data Analysis ISBN: 9811541051 ISBN-13(EAN): 9789811541056 Издательство: Springer Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
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.
Автор: Backhaus, Klaus Erichson, Bernd Gensler, Sonja Weiber, Rolf Weiber, Thomas Название: Multivariate Analysis ISBN: 3658325887 ISBN-13(EAN): 9783658325886 Издательство: Springer Рейтинг: Цена: 78360.00 T Наличие на складе: Невозможна поставка. Описание: Based on historical corpora, the book is a comprehensive study of the demise of five preterite-present verbs in English. It offers a detailed description of the forms and uses of these verbs in Old and Middle English, which, when compared, allow the author to suggest the reasons for their elimination from the language.
Автор: Konishi, Sadanori Название: Introduction to Multivariate Analysis ISBN: 1466567287 ISBN-13(EAN): 9781466567283 Издательство: Taylor&Francis Рейтинг: Цена: 102080.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Keith Название: Multiple Regression and Beyond ISBN: 1138061425 ISBN-13(EAN): 9781138061422 Издательство: Taylor&Francis Рейтинг: Цена: 224570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Multiple Regression and Beyond offers a conceptually oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods.
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