Multiple Factor Analysis By Example Using R
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Multiple Factor Analysis By Example Using R
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Author : Jérôme Pagès
language : en
Publisher:
Release Date : 2015
Multiple Factor Analysis By Example Using R written by Jérôme Pagès and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Factor analysis categories.
Multiple Factor Analysis By Example Using R
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Author : Jérôme Pagès
language : en
Publisher: CRC Press
Release Date : 2014-11-20
Multiple Factor Analysis By Example Using R written by Jérôme Pagès and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-20 with Mathematics categories.
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 inc
Exploratory Multivariate Analysis By Example Using R
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Author : Francois Husson
language : en
Publisher: CRC Press
Release Date : 2017-04-25
Exploratory Multivariate Analysis By Example Using R written by Francois Husson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-25 with Mathematics categories.
Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) a
Practical Guide To Principal Component Methods In R
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Author : Alboukadel KASSAMBARA
language : en
Publisher: STHDA
Release Date : 2017-08-23
Practical Guide To Principal Component Methods In R written by Alboukadel KASSAMBARA and has been published by STHDA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-23 with categories.
Although there are several good books on principal component methods (PCMs) and related topics, we felt that many of them are either too theoretical or too advanced. This book provides a solid practical guidance to summarize, visualize and interpret the most important information in a large multivariate data sets, using principal component methods in R. The visualization is based on the factoextra R package that we developed for creating easily beautiful ggplot2-based graphs from the output of PCMs. This book contains 4 parts. Part I provides a quick introduction to R and presents the key features of FactoMineR and factoextra. Part II describes classical principal component methods to analyze data sets containing, predominantly, either continuous or categorical variables. These methods include: Principal Component Analysis (PCA, for continuous variables), simple correspondence analysis (CA, for large contingency tables formed by two categorical variables) and Multiple CA (MCA, for a data set with more than 2 categorical variables). In Part III, you'll learn advanced methods for analyzing a data set containing a mix of variables (continuous and categorical) structured or not into groups: Factor Analysis of Mixed Data (FAMD) and Multiple Factor Analysis (MFA). Part IV covers hierarchical clustering on principal components (HCPC), which is useful for performing clustering with a data set containing only categorical variables or with a mixed data of categorical and continuous variables.
Textual Data Science With R
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Author : Mónica Bécue-Bertaut
language : en
Publisher: CRC Press
Release Date : 2019-03-11
Textual Data Science With R written by Mónica Bécue-Bertaut and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-11 with Mathematics categories.
Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Methods discussed include correspondence analysis, clustering, and multiple factor analysis for contigency tables. Each method is illuminated by applications. The book is aimed at researchers and students in statistics, social sciences, hiistory, literature and linguistics. The book will be of interest to anyone from practitioners needing to extract information from texts to students in the field of massive data, where the ability to process textual data is becoming essential.
Multiple Factor Analysis
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Author : Louis Leon Thurstone
language : en
Publisher:
Release Date : 1947
Multiple Factor Analysis written by Louis Leon Thurstone and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1947 with Educational tests and measurements categories.
An Introduction To Applied Multivariate Analysis With R
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Author : Brian Everitt
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-04-23
An Introduction To Applied Multivariate Analysis With R written by Brian Everitt and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-23 with Mathematics categories.
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.
Factor Analysis
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Author : Richard L. Gorsuch
language : en
Publisher: Routledge
Release Date : 2014-11-27
Factor Analysis written by Richard L. Gorsuch and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-27 with Psychology categories.
Comprehensive and comprehensible, this classic text covers the basic and advanced topics essential for using factor analysis as a scientific tool in psychology, education, sociology, and related areas. Emphasizing the usefulness of the techniques, it presents sufficient mathematical background for understanding and applying its use. This includes the theory as well as the empirical evaluations. The overall goal is to show readers how to use factor analysis in their substantive research by highlighting when the differences in mathematical procedures have a major impact on the substantive conclusions, when the differences are not relevant, and when factor analysis might not be the best procedure to use. Although the original version was written years ago, the book maintains its relevance today by providing readers with a thorough understanding of the basic mathematical models so they can easily apply these models to their own research. Readers are presented with a very complete picture of the "inner workings" of these methods. The new Introduction highlights the remarkably few changes that the author would make if he were writing the book today. An ideal text for courses on factor analysis or as a supplement for multivariate analysis, structural equation modeling, or advanced quantitative techniques taught in psychology, education, and other social and behavioral sciences, researchers who use these techniques also appreciate this book’s thorough review of the basic models. Prerequisites include a graduate level course on statistics and a basic understanding of algebra. Sections with an asterisk can be skipped entirely if preferred.
Multiple Factor Analysis
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Author : Louis Leon Thurstone
language : en
Publisher:
Release Date : 1947
Multiple Factor Analysis written by Louis Leon Thurstone and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1947 with Mathematics categories.
Exploratory Multivariate Analysis By Example Using R
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Author : François Husson
language : en
Publisher:
Release Date : 2017
Exploratory Multivariate Analysis By Example Using R written by François Husson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with MATHEMATICS categories.