Multivariate statistics and matrices in statistics : proceedings of the 5th Tartu Conference, Tartu - Pühajärve, Estonia, 23-28 May 1994
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Bibliographic Information
Multivariate statistics and matrices in statistics : proceedings of the 5th Tartu Conference, Tartu - Pühajärve, Estonia, 23-28 May 1994
（New trends in probability and statistics, v. 3）
VSP , TEV, 1995
- : VSP
- : TEV
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Includes bibliographical references
Description and Table of Contents
Description
01/07 This title is now available from Walter de Gruyter. Please see www.degruyter.com for more information.
Table of Contents
- Part 1 Asymptotic distrubtions and expansions: error bounds for asymptotic expansions of the distributions of the classification statistic W and related statistics, Y. Fujikoshi
- some results on the empirical spacings process and its bootstrapped version, S. Rao Jammalamadaka and Jing Qin
- on the Cornish-Fisher expansion in finite population, I. Traat. Part 2 General linear regression models: on proportionality of regression co-efficients in misspecified general lineal regression models, U. Poetter
- more on the partitioned possibly restricted linear regression, H.J. Werner and C. Yapar
- simpler tests of linear inequality constraints in the standard linear model, R.W. Farebrother
- increasing the correlations with the response variable may not increase the co-efficient of determination - a PCA interpretation, C.M. Cuadras
- discussion on the paper of C.M. Cuadras - increasing the correlations with the response variable maty not increase the co-efficient of determination - a PCA interpretation, E.-M. Tiit
- testing lack of fit in mixed-effect models for longitudinal data, M. Palta and R.P. Qu. Part 3 Tests in multivariate statistics: a projection NT-type test for spherical symmetry of a multivariate distribution, Li-Xing Zhu et al
- Some applictions of directional statistics to astronomy, P.E. Jupp
- simple methods for fitting circles or points to spherical data, R.W. Farebrother. Part 4 Multivariate nonparametric models and their applications. Part 5 Discrimination and classification. Part 6 Matrices in statistics. (Part contents)
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