Author: Brigitte Le Roux
Edition: 2004
Publisher: Springer
Binding: Hardcover
ISBN: 1402022352
Geometric Data Analysis: From Correspondence Analysis to Structured Data Analysis
Geometric Data Analysis (GDA) is the name suggested by P. Medical books Geometric Data Analysis. Suppes (Stanford University) to designate the approach to Multivariate Statistics initiated by Benzécri as Correspondence Analysis, an approach that has become more and more used and appreciated over the years. This book presents the full formalization of GDA in terms of linear algebra - the most original and far-reaching consequential feature of the approach - and shows also how to integrate the standard statistical tools such as Analysis of Variance, including Bayesian methods. Chapter 9, Research Case Studies, is nearly a book in itself; it presents the methodology in action on three extensive applications, one for medicine, one from political science, and one from education (data borrowed from the Stanford computer-based Educational Program for Gifted Youth ). Thus the readership of the book concerns both mathematicians interested in the applications of mathematics, and researchers willing to master an exceptionally powerful approach of statistical data analysis Medical books Geometric Data Analysis: From Correspondence Analysis to Structured Data Analysis (Paperback). Geometric Data Analysis (GDA) is the name suggested by P. Suppes (Stanford University) to designate the approach to Multivariate Statistics initiated by Benzcri as Correspondence Analysis, an approach that has become more and more used and appreciated over the years. This book presents the full formalization of GDA in terms of linear algebra - the most original and far-reaching consequential feature of the approach - and shows also how to integrate the standard statistical tools such as Analysis of Variance, including Bayesian methods. Chapter 9, Research Case Studies, is nearly a book in itself; it presents the methodology in action on three extensive applications, one for medicine, one from political science, and one from education (data borrowed from the Stanford computer-based Educational Program for Gifted Youth ). Thus the readership of the book concerns both mathematicians interested in the applications of mathematics, and researchers willing to master an exceptionally powerful approach of statistical data analysis.
Download link for Geometric Data Analysis: From Correspondence Analysis to Structured Data Analysis
Geometric Data Analysis (GDA) is the name suggested by P. Suppes (Stanford University) to designate the approach to Multivariate Statistics initiated by Benzcri as Correspondence Analysis, an approach that has become more and more used and appreciated over the years. This book presents the full formalization of GDA in terms of linear algebra - the most original and far-reaching consequential feature of the approach - and shows also how to integrate the standard statistical tools such as Analysis of Variance, including Bayesian methods. Chapter 9, Research Case Studies, is nearly a book in itse
Springer. Hardcover. 1402022352 Hardcover; 2004 Springer; 475 pages; "Geometric Data Analysis: From Correspondence Analysis to Structured Data Analysis" by Brigitte Le Roux et al. . Good.
Geometric Data Analysis: From Correspondence Analysis to Structured Data Analysis Springer 9789048166190 09789048166190
author michael kirby format hardback language english publication year 29 01 2001 subject mathematics sciences subject 2 mathematics title geometric data analysis an empirical approach to dimensionality reduction and the study of patterns author kirby michael publisher wiley interscience publication date dec 01 2000 pages 361 binding hardcover edition 1 st dimensions 6 00 wx 9 50 hx 1 00 d isbn 0471239291 subject computers data processing general description this book addresses the most effici
Medical Book Geometric Data Analysis
Suppes (Stanford University) to designate the approach to Multivariate Statistics initiated by Benzécri as Correspondence Analysis, an approach that has become more and more used and appreciated over the years. This book presents the full formalization of GDA in terms of linear algebra - the most original and far-reaching consequential feature of the approach - and shows also how to integrate the standard statistical tools such as Analysis of Variance, including Bayesian methods. Chapter 9, Research Case Studies, is nearly a book in itself; it presents the methodology in action on three extensive applications, one for medicine, one from political science, and one from education (data borrowed from the Stanford computer-based Educational Program for Gifted Youth ). Thus the readership of the book concerns both mathematicians interested in the applications of mathematics, and researchers willing to master an exceptionally powerful approach of statistical data analysis.
