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 will be of great 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 valuable guide to professors, researchers and graduate students seeking new and promising lines of statistical research.
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Elsevier Science & Technology
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978-0-444-81531-6 (9780444815316)
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book "Ancient Inhabitants of Jebel Moya? published by the Cambridge Press under the joint authorship of Rao and two anthropologists. On the basis of work done at CU during the two year period, 1946-1948, Rao earned a Ph.D. degree and a few years later Sc.D. degree of CU and the rare honor of life fellowship of Kings College, Cambridge.
He retired from ISI in 1980 at the mandatory age of 60 after working for 40 years during which period he developed ISI as an international center for statistical education and research. He also took an active part in establishing state statistical bureaus to collect local statistics and transmitting them to Central Statistical Organization in New Delhi. Rao played a pivitol role in launching undergraduate and postgraduate courses at ISI. He is the author of 475 research publications and several breakthrough papers contributing to statistical theory and methodology for applications to problems in all areas of human endeavor. There are a number of classical statistical terms named after him, the most popular of which are Cramer-Rao inequality, Rao-Blackwellization, Rao's Orthogonal arrays used in quality control, Rao's score test, Rao's Quadratic Entropy used in ecological work, Rao's metric and distance which are incorporated in most statistical books.
He is the author of 10 books, of which two important books are, Linear Statistical Inference which is translated into German, Russian, Czec, Polish and Japanese languages,and Statistics and Truth which is translated into, French, German, Japanese, Mainland Chinese, Taiwan Chinese, Turkish and Korean languages.
He directed the research work of 50 students for the Ph.D. degrees who in turn produced 500 Ph.D.'s. Rao received 38 hon. Doctorate degree from universities in 19 countries spanning 6 continents. He received the highest awards in statistics in USA,UK and India: National Medal of Science awarded by the president of USA, Indian National Medal of Science awarded by the Prime Minister of India and the Guy Medal in Gold awarded by the Royal Statistical Society, UK. Rao was a recipient of the first batch of Bhatnagar awards in 1959 for mathematical sciences and and numerous medals in India and abroad from Science Academies. He is a Fellow of Royal Society (FRS),UK, and member of National Academy of Sciences, USA, Lithuania and Europe. In his honor a research Institute named as CRRAO ADVANCED INSTITUTE OF MATHEMATICS, STATISTICS AND COMPUTER SCIENCE was established in the campus of Hyderabad University.
Herausgeber*in
University of Barcelona, Spain
University of Hyderabad Campus, India
Discriminant Analysis and Scaling. Discriminant analysis for mixed variables: Integrating trees and regression models (A. Ciampi, L. Hendricks, Z. Lou). A strong Lagrangian look at profile log-likelihood with applications to linear discrimination (F. Critchley, I. Ford, D. Hirst). Continuous metric scaling and prediction (C.M. Cuadras, J. Fortiana). A comparison of techniques for finding components with simple structure (H.A.L. Kiers). Antedependence modeling in discriminant analysis of high-dimensional spectrometric data (W.J. Krzanowski). On scaling of ordinal categorical data (C.R. Rao, P.M. Caligiuri). Latent Variable Models. Instrumental variable estimation for nonlinear factor analysis (Y. Amemiya). The analysis of panel data with mean and covariance structure models for non metric dependent variables (G. Arminger). The geometry of mean or covariance structure models in multivariate normal distributions: A unified approach (M. Berkane, P.M. Bentler). Structured latent curve models (M.W. Browne). Latent variable modeling of growth with missing data and multilevel data (B.O. Muthen). Asymptotic robust inferences in multi-sample analysis of augmented-moment structures (A. Satorra). Correspondence Analysis and Related Topics. Multiple correspondence analysis on panel data (T. Aluja-Banet, R. Nonell-Torrent). Analysing dependence in large contingency tables: dimensionality and patterns in scatter-plots (A. Baccini, H. Caussinus, A. de Falguerolles). Correspondence analysis, association analysis, and generalized non-independence analysis of contingency tables: Saturated and unsaturated models, and appropriate graphical displays (L.A. Goodman). Recent advances in biplot methodology (J.C. Gower). Multivariate generalisations of correspondence analysis (M.J. Greenacre). Correspondence analysis and classification (L. Lebart, B.G. Mirkin). Some generalizations of correspondence analysis (J. de Leeuw). Differential Geometry Applications. Differential geometry of estimating functions (S. Amari). Statistical inference and differential geometry - some recent developments (O.E. Barndorff-Nielsen, P.E. Jupp). Random variables, integral curves and estimation of probabilities (L.L. Campbell). Sufficient geometrical conditions to Cramer-Rao inequality (J. del Castillo). On an intrinsic analysis of statistical estimation (J.M. Oller). Bootstrap, Conditional Models and Divergences. Conditionally specified models: Structure and inference (B.C. Arnold, E. Castillo, J.M. Sarabia). Multivariate analysis in the computer age (B. Efron). New parametric measures of information based on generalized R-divergences (D. Morales et al.).
