Statistical Tables for Multivariate Analysis. A Handbook with References to Applications. Springer Series in Statistics

Kres, Heinz, Wadsack, Peter

ISBN 10: 0387909095 / ISBN 13: 9780387909097

Editore: Springer, 1983

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Codice articolo ZB1297274

Dati bibliografici

• Titolo: Statistical Tables for Multivariate Analysis. A Handbook with References to Applications. Springer Series in Statistics
• Editore: Springer
• Data di pubblicazione: 1983
• Lingua: Inglese
• ISBN 10: 0387909095
• ISBN 13: 9780387909097
• Rilegatura: Rilegato
• Condizione: Fine

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Contenuti

I: The Primary Tables for Testing Multivariate Statistical Hypotheses.- Preliminary Remarks.- 0: A Brief Summary of the Test Criteria for the Multivariate General Linear Hypothesis.- Table 1: The Likelihood Ratio Criterion ? of S. S. Wilks: Tables of F. J. Wall.- Table 2: The ?max — Criterion of K. C. S. Pillai: A Version of the Maximum Root Criterion of S. N. Roy.- Table 3: The Generalized F-Criterion of R. D. Bock: A Version of the Maximal Root Criterion of S. N. Roy.- Table 4: The Nomograms of D. L. Heck for the Distribution of the ?max — Criterion of S. N. Roy.- Table 5: The ?max — Criterion of F. G. Foster and D. H. Rees: A Version of the Maximum Root Criterion of S. N. Roy.- Table 6: The Trace Criterion To2 of H. Hotelling and D. N. Lawley in the Version of K. C. S. Pillai.- Table 7: The Trace Criterion of H. Hotelling and D. N. Lawley in the Version V(s) of K. C. S. Pillai.- Table 8: The T2-Criterion of H. Hotelling: Tables of D. R. Jensen and R. B. Howe.- II: Tables Related to the Multivariate Normal Distribution.- Preliminary Remarks.- Table 9: The Multivariate Normal Distribution with Equal Correlations: Tables of S. S. Gupta.- Table 10: The Distribution of the Maximum of N Equally Correlated Normal Standardised Random Variables: Tables of S. S. Gupta, K. Nagel, and S. Panchapakesan.- Table 11: The Sphericity Test of J. W. Mauchly: Tables of B. N. Nagarsenker and K. C. S. Pillai.- Table 12: The Test Criteria Lmvc, Lvc and Lm of S. S. Wilks: Tables of S. S. Wilks and also of J. Roy and V. K. Murthy.- Table 13: The Multivariate Outlier Criteria of S. S. Wilks.- Table 14: Multivariate Tolerance Regions with ?-Expectation (Type 2): Tables of D. A. S. Fraser and I. Guttman.- Table 15: Multivariate Tolerance Regions with ?-Content (Type 1): Tables of V. Chew.- Table 16: Testing a Single Covariance Matrix: Tables of B. P. Korin.- Table 17: Testing the Equality of k Covariance Matrices: Tables of B. P. Korin.- Table 18: Distribution of the Extreme Roots of a WISHART Matrix: Tables of R. Ch. Hanumara and W. A. Thompson.- Table 19: The Multivariate t-Distribution: Tables of P. R. Krishnaiah and J. V. Armitage.- III: Further Tables for Multivariate Problems.- Preliminary Remarks.- Table 20: The Gamma Distribution: Tables of M. B. Wilk, R. Gnanadesikan, and M. J. Huyette.- Table 21: The BARGMANN Test for Simple Structure of a Factor Pattern: Tables of R. Bargmann.- Table 22: Upper Percentage Points of the BONFERRONI Chi-Square Statistic: Tables of G. B. Beus and D. R. Jensen.- Table 23: Lower Percentage Points of the BONFERRONI Chi-Square Statistic: Tables of G. B. Beus and D. R. Jensen.- Table 24: The Sequential Chi-Square Criterion for Multivariate Comparisons of Means: Tables of R. J. Freund and J. E. Jackson.- Table 25: The Sequential T2 -Criterion for Multivariate Testing for Means: Tables of R. J. Freund and J. E. Jackson.- IV (Appendix): Supplement.- Preliminary Remarks.- Table 26: The MARDIA-Test for Multivariate Normality, Skewness, and Kurtosis: Tables by K. V. Mardia.- Table 27: Sample Size Requirements for the T2-Test of MANOVA in One-Way Classifications: Tables of J. Läuter.- Table 28: Critical Values for Simultaneous and Sequential BONFERRONI z-Tests: Tables of G. A. Lienert, O. Ludwig, and K. Rockenfeller.- Table 29: Upper Percentage Points of the BONFERRONI t-Statistic: Tables of B. J. R. Bailey.- Table 30: Upper Percentage Points of Statistics for Testing Covariance Matrices: Tables of J. C. Lee, T. C. Chang, and P. R. Krishnaiah.- Final Remarks: Univariate Test Distributions as a Special Case of Their Multivariate Analogs.