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The contributions in this volume, made by distinguished statisticians in several frontier areas of research in multivariate analysis, cover a broad field and indicate future directions of research. The topics covered include discriminant analysis, multidimensional scaling, categorical data analysis, correspondence analysis and biplots, association analysis, latent variable models, bootstrap distributions, differential geometry applications and others. Most of the papers propose generalizations or new applications of multivariate analysis. This volume should be of interest to statisticians, probabilists, data analysts and scientists working in the disciplines such as biology, biometry, ecology, medicine, econometry, psychometry and marketing. It will be a guide to professors, researchers and graduate students seeking new and promising lines of statistical research
Preface
List of contributors
Discriminant analysis for mixed variables: Integrating trees and regression models
A strong Lagrangian look at profile log likelihood with applications to linear discrimination
Continuous metric scaling and prediction
A comparison of techniques for finding components with simple structure
Antedependence modelling in discriminant analysis of high-dimensional spectroscopic data
On scaling of ordinal categorical data
Instrumental variable estimation for nonlinear factor analysis
The analysis of panel data with mean and covariance structure models for non-metric dependent variables
The geometry of mean or covariance structure models in multivariate normal distributions: A unified approach
Structured latent curve models
Latent variable modeling of growth with missing data and multilevel data
Asymptotic robust inferences in multi-sample analysis of augmented-moment structures
Multiple Correspondence Analysis on panel data
Analysing dependence in large contingency tables: Dimensionality and patterns in scatter-plots
Correspondence analysis, association analysis, and generalized nonindependence analysis of contingency tables: Saturated and unsaturated models, and appropriate graphical displays
Recent advances in biplot methodology
Multivariate generalisations of correspondence analysis
Correspondence analysis and classification
Some generalizations of correspondence analysis
Differential geometry of estimating functions
Statistical inference and differential geometry — Some recent developments
Random variables, integral curves and estimation of probabilities
Sufficient geometrical conditions for Cramér–Rao inequality
On an intrinsic analysis of statistical estimation
Conditionally specified models: Structure and inference
Multivariate analysis in the computer age
New parametric measures of information based on generalized R-divergences