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Factor Analysis and Dimension Reduction in R, Garson, G. David


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Автор: Garson, G. David
Название:  Factor Analysis and Dimension Reduction in R
ISBN: 9781032246680
Издательство: Taylor&Francis
Классификация:





ISBN-10: 1032246685
Обложка/Формат: Hardback
Страницы: 564
Вес: 1.27 кг.
Дата издания: 16.12.2022
Иллюстрации: 1 tables, black and white; 129 line drawings, color; 16 line drawings, black and white; 129 illustrations, color; 16 illustrations, black and white
Размер: 181 x 253 x 34
Читательская аудитория: Tertiary education (us: college)
Подзаголовок: A social scientist`s toolkit
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Поставляется из: Европейский союз


Risk and Uncertainty Reduction by Using Algebraic Inequalities

Автор: Todinov, Michael T.
Название: Risk and Uncertainty Reduction by Using Algebraic Inequalities
ISBN: 0367898004 ISBN-13(EAN): 9780367898007
Издательство: Taylor&Francis
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Цена: 17609.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book provides the reader with a domain-independent method for reducing risk through maximizing reliability, reducing epistemic uncertainty, reducing aleatory uncertainty, ranking the reliabilities of systems and processes, minimizing the risk of faulty assemblies, and ranking decision-making alternatives in the presence of deep uncertainty.

Data Reduction And Error Analysis For The Physical Sciences

Автор: Bevington; Robinson
Название: Data Reduction And Error Analysis For The Physical Sciences
ISBN: 0071199268 ISBN-13(EAN): 9780071199261
Издательство: McGraw-Hill
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Цена: 7377.00 р.
Наличие на складе: Поставка под заказ.

Описание: Provides an introduction to the concepts of statistical analysis of data for students at undergraduate and graduate level. This text also provides tools for data reduction and error analysis commonly required in the physical sciences. It features a variety of numerical and graphical techniques, and emphasizes methods of handling data than theory.

Making Sense of Factor Analysis

Автор: Pett M et al
Название: Making Sense of Factor Analysis
ISBN: 0761919503 ISBN-13(EAN): 9780761919506
Издательство: Sage Publications
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Цена: 13306.00 р.
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Описание: This text offers a practical method for developing tests, validating instruments, and reporting outcomes through the use of factor analysis. Ideal for graduate level nursing students, this book is also an invaluable resource for health care researchers.

Multiple Factor Analysis by Example Using R

Автор: Pages
Название: Multiple Factor Analysis by Example Using R
ISBN: 1482205475 ISBN-13(EAN): 9781482205473
Издательство: Taylor&Francis
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Цена: 13014.00 р.
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Описание: Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also includes examples of applications and details of how to implement MFA using an R package (FactoMineR). The first two chapters cover the basic factorial analysis methods of principal component analysis (PCA) and multiple correspondence analysis (MCA). The next chapter discusses factor analysis for mixed data (FAMD), a little-known method for simultaneously analyzing quantitative and qualitative variables without group distinction. Focusing on MFA, subsequent chapters examine the key points of MFA in the context of quantitative variables as well as qualitative and mixed data. The author also compares MFA and Procrustes analysis and presents a natural extension of MFA: hierarchical MFA (HMFA). The final chapter explores several elements of matrix calculation and metric spaces used in the book.

Factor analysis and dimension reduction in r

Автор: Garson, G. David (north Carolina State University, Raleigh, Usa)
Название: Factor analysis and dimension reduction in r
ISBN: 1032246693 ISBN-13(EAN): 9781032246697
Издательство: Taylor&Francis
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Цена: 11023.00 р.
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Описание: Factor Analysis and Dimension Reduction in R provides coverage, with worked examples, of a large number of dimension reduction procedures along with model performance metrics to compare them. Factor analysis in the form of principal components analysis (PCA) or principal factor analysis (PFA) is familiar to most social scientists. However, what is less familiar is understanding that factor analysis is a subset of the more general statistical family of dimension reduction methods.The social scientist's toolkit for factor analysis problems can be expanded to include the range of solutions this book presents. In addition to covering FA and PCA with orthogonal and oblique rotation, this book’s coverage includes higher-order factor models, bifactor models, models based on binary and ordinal data, models based on mixed data, generalized low-rank models, cluster analysis with GLRM, models involving supplemental variables or observations, Bayesian factor analysis, regularized factor analysis, testing for unidimensionality, and prediction with factor scores. The second half of the book deals with other procedures for dimension reduction. These include coverage of kernel PCA, factor analysis with multidimensional scaling, locally linear embedding models, Laplacian eigenmaps, diffusion maps, force directed methods, t-distributed stochastic neighbor embedding, independent component analysis (ICA), dimensionality reduction via regression (DRR), non-negative matrix factorization (NNMF), Isomap, Autoencoder, uniform manifold approximation and projection (UMAP) models, neural network models, and longitudinal factor analysis models. In addition, a special chapter covers metrics for comparing model performance.Features of this book include:Numerous worked examples with replicable R codeExplicit comprehensive coverage of data assumptionsAdaptation of factor methods to binary, ordinal, and categorical dataRe

Modern Dimension Reduction

Автор: Waggoner Philip D.
Название: Modern Dimension Reduction
ISBN: 1108986897 ISBN-13(EAN): 9781108986892
Издательство: Cambridge University Press
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Цена: 4495.00 р.
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Описание: Dimension reduction offers researchers and scholars the ability to make complex, high dimensional data spaces simpler and more manageable. This Element offers readers a suite of modern unsupervised dimension reduction techniques to efficiently represent the original high dimensional data space in a simplified, lower dimensional subspace.

Multidimensional stationary time series

Автор: Bolla, Marianna (budapest University Of Technology And Economics) Szabados, Tamas (budapest University Of Technology And Economics, Hungary)
Название: Multidimensional stationary time series
ISBN: 0367569329 ISBN-13(EAN): 9780367569327
Издательство: Taylor&Francis
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Цена: 19906.00 р.
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Описание: This book gives a brief survey of the theory of multidimensional (multivariate), weakly stationary time series, with emphasis on dimension reduction and prediction.

Multidimensional Stationary Time Series

Автор: Bolla, Marianna
Название: Multidimensional Stationary Time Series
ISBN: 0367619709 ISBN-13(EAN): 9780367619701
Издательство: Taylor&Francis
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Цена: 7042.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Sufficient Dimension Reduction

Автор: Li, Bing
Название: Sufficient Dimension Reduction
ISBN: 0367734729 ISBN-13(EAN): 9780367734725
Издательство: Taylor&Francis
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Цена: 7501.00 р.
Наличие на складе: Нет в наличии.

Statistical Analysis of Observations of Increasing Dimension

Автор: V.L. Girko
Название: Statistical Analysis of Observations of Increasing Dimension
ISBN: 0792328868 ISBN-13(EAN): 9780792328865
Издательство: Springer
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Цена: 23058.00 р.
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Описание: An investigation of the limit distribution of the empirical generalized variance, covariance matrices, their eigenvalues and solutions of the system of linear algebraic equations with random coefficients, which are an important function of observations in multidimensional statistical analysis.

The Analysis of Biological Data

Автор: Michael C. Whitlock, Dolph Schluter
Название: The Analysis of Biological Data
ISBN: 1319325343 ISBN-13(EAN): 9781319325343
Издательство: Macmillan Learning
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Цена: 13858.00 р.
Наличие на складе: Поставка под заказ.

Описание: The evolution of a classicThe new 12th edition of Introduction to Genetic Analysis takes this cornerstone textbook to the next level.

Confirmatory Factor Analysis for Applied Research, Second Edition

Автор: Brown, Timothy A.,
Название: Confirmatory Factor Analysis for Applied Research, Second Edition
ISBN: 1462515363 ISBN-13(EAN): 9781462515363
Издательство: Taylor&Francis
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Цена: 9186.00 р.
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Описание: With its emphasis on practical and conceptual aspects, rather than mathematics or formulas, this accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA). Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities and differences between CFA and exploratory factor analysis (EFA); and report results from a CFA study. It is filled with useful advice and tables that outline the procedures. The companion website (www.guilford.com/brown3-materials) offers data and program syntax files for most of the research examples, as well as links to CFA-related resources.

New to This Edition
*Updated throughout to incorporate important developments in latent variable modeling.
*Chapter on Bayesian CFA and multilevel measurement models.
*Addresses new topics (with examples): exploratory structural equation modeling, bifactor analysis, measurement invariance evaluation with categorical indicators, and a new method for scaling latent variables.
*Utilizes the latest versions of major latent variable software packages.


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