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.).
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.
- No. of pages:
- © North Holland 1993
- 26th November 1993
- North Holland
- eBook ISBN:
University of Barcelona, Spain
Professor C. R. Rao, born in India, is one of this century's foremost statisticians, and received his education in statistics at the Indian Statistical Institute (ISI), Calcutta. He is Emeritus Holder of the Eberly Family Chair in Statistics at Penn State and Director of the Center for Multivariate Analysis. He has long been recognized as one of the world's top statisticians, and has been awarded 34 honorary doctorates from universities in 19 countries spanning 6 continents. His research has influenced not only statistics, but also the physical, social and natural sciences and engineering.
In 2011 he was recipient of the Royal Statistical Society's Guy Medal in Gold which is awarded triennially to those "who are judged to have merited a signal mark of distinction by reason of their innovative contributions to the theory or application of statistics". It can be awarded both to fellows (members) of the Society and to non-fellows. Since its inception 120 years ago the Gold Medal has been awarded to 34 distinguished statisticians. The first medal was awarded to Charles Booth in 1892. Only two statisticians, H. Cramer (Norwegian) and J. Neyman (Polish), outside Great Britain were awarded the Gold medal and C. R. Rao is the first non-European and non-American to receive the award.
Other awards he has received are the Gold Medal of Calcutta University, Wilks Medal of the American Statistical Association, Wilks Army Medal, Guy Medal in Silver of the Royal Statistical Society (UK), Megnadh Saha Medal and Srinivasa Ramanujan Medal of the Indian National Science Academy, J.C.Bose Gold Medal of Bose Institute and Mahalanobis Centenary Gold Medal of the Indian Science Congress, the Bhatnagar award of the Council of Scientific and Industrial Research, India and the Government of India honored him with the second highest civilian award, Padma Vibhushan, for “outstanding contributions to Science and Engineering / Statistics”, and also instituted a cash award in honor of C R Rao, “to be given once in two years to a young statistician for work done during the preceding 3 years in any field of statistics”.
For his outstanding achievements Rao has been honored with the establishment of an institute named after him, C.R.Rao Advanced Institute for Mathematics, Statistics and Computer Science, in the campus of the University of Hyderabad, India.
The Pennsylvania State University, University Park, PA, USA