GIFI NONLINEAR MULTIVARIATE ANALYSIS PDF

The Gifi system of analyzing categorical data through nonlinear varieties of classical multivariate analysis techniques is reviewed. The system is characterized by the optimal scaling of categorical variables which is implemented through alternating least squares algorithms. The main technique of homogeneity analysis is presented, along with its extensions and generalizations leading to nonmetric principal components analysis and canonical correlation analysis. A brief account of stability issues and areas of applications of the techniques is also given. Skip to main content. Email Facebook Twitter.

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Albert Gifi. Table of contents Conventions and Controversies in Multivariate Analysis. Coding of Categorical Data. Homogeneity Analysis. Nonlinear Principal Components Analysis. Nonlinear Generalized Canonical Analysis. Nonlinear Canonical Correlation Analysis. Multidimensional Scaling and Correspondence Analysis.

Models as Gauges for the Analysis of Binary Data. Reflections on Restrictions. Nonlinear Multivariate Analysis: Principles andPossibilities.

The Study of Stability. The Proof of the Pudding. Author Index. Subject Index. Series Wiley Series in Probability and Statistics. Undetected location. NO YES. Nonlinear Multivariate Analysis. Selected type: Hardcover. Added to Your Shopping Cart. This is a dummy description. Presents a system of multivariate analysis techniques in cases where statistical data may be of different measurement levels such as nominal, ordinal or interval.

It covers methods of studying the stability of these techniques, including resampling by the bootstrap and jackknife and discusses sensitivity analysis through first-order approximations. The alternating least squares algorithm is used as a general model and treated in detail for the most important special cases.

Among techniques covered are correspondence analysis, principal components analysis, canonical correlation analysis and various ordination techniques. The exposition also includes historical overviews, basic theoretical results, algorithmic efficiency and applications.

Emphasis is placed on graphical display and nonlinear transformation of variables is used to obtain simple displays. Wiley Series in Probability and Statistics.

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The Gifi System for Nonlinear Multivariate Analysis

The Gifi system of analyzing categorical data through nonlinear varieties of classical multivariate analysis techniques is reviewed. The system is characterized by the optimal scaling of categorical variables which is implemented through alternating least squares algorithms. The main technique of homogeneity analysis is presented, along with its extensions and generalizations leading to nonmetric principal components analysis and canonical correlation analysis. Several examples are used to illustrate the methods. A brief account of stability issues and areas of applications of the techniques is also given.

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Department of Statistics, UCLA

Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. The Gifi system of analyzing categorical data through nonlinear varieties of classical multivariate analysis techniques is reviewed. The system is characterized by the optimal scaling of categorical variables which is implemented through alternating least squares algorithms. The main technique of homogeneity analysis is presented, along with its extensions and generalizations leading to nonmetric principal components analysis and canonical correlation analysis.

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