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cuadras c multivariate analysis future directions 2 1993

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Textbook in PDF format 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

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cuadras c multivariate analysis future directions 2 1993