Simultaneous Statistical Inference

Simultaneous Statistical Inference

by Rupert G. Jr. Miller

Paperback(2nd ed. 1981. Softcover reprint of the original 2nd ed. 1981)

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Product Details

ISBN-13: 9781461381242
Publisher: Springer New York
Publication date: 10/14/2011
Series: Springer Series in Statistics
Edition description: 2nd ed. 1981. Softcover reprint of the original 2nd ed. 1981
Pages: 299
Product dimensions: 6.10(w) x 9.25(h) x 0.03(d)

Table of Contents

1 Introduction.- 1 Case of two means.- 2 Error rates.- 2.1 Probability of a nonzero family error rate.- 2.2 Expected family error rate.- 2.3 Allocation of error.- 3 Basic techniques.- 3.1 Repeated normal statistics.- 3.2 Maximum modulus (Tukey).- 3.3 Bonferroni normal statistics.- 3.4—2 projections (Scheffé).- 3.5 Allocation.- 3.6 Multiple modulus tests (Duncan).- 3.7 Least significant difference test (Fisher).- 4 p-mean significance levels.- 5 Families.- 2 Normal Univariate Techniques.- 1 Studentized range (Tukey).- 1.1 Method.- 1.2 Applications.- 1.3 Comparison.- 1.4 Derivation.- 1.5 Distributions and tables.- 2 F projections (Scheffé)48.- 2.1 Method.- 2.2 Applications.- 2.3 Comparison.- 2.4 Derivation.- 2.5 Distributions and tables.- 3 Bonferroni t statistics.- 3.1 Method.- 3.2 Applications.- 3.3 Comparison.- 3.4 Derivation.- 3.5 Distributions and tables.- 4 Studentized maximum modulus.- 4.1 Method.- 4.2 Applications.- 4.3 Comparison.- 4.4 Derivation.- 4.5 Distributions and tables.- 5 Many-one t statistics76.- 5.1 Method.- 5.2 Applications.- 5.3 Comparison.- 5.4 Derivation.- 5.5 Distributions and tables.- 6 Multiple range tests (Duncan).- 6.1 Method.- 6.2 Applications.- 6.3 Comparison.- 6.4 Derivation.- 6.5 Distributions and tables.- 7 Least significant difference test (Fisher).- 7.1 Method.- 7.2 Applications.- 7.3 Comparison.- 7.4 Derivation.- 7.5 Distributions and tables.- 8 Other techniques.- 8.1 Tukey’s gap-straggler-variance test.- 8.2 Shortcut methods.- 8.3 Multiple F tests.- 8.4 Two-sample confidence intervals of predetermined length.- 8.5 An improved Bonferroni inequality.- 9 Power.- 10 Robustness.- 3 Regression Techniques.- 1 Regression surface confidence bands.- 1.1 Method.- 1.2 Comparison.- 1.3 Derivation.- 2 Prediction.- 2.1 Method.- 2.2 Comparison.- 2.3 Derivation.- 3 Discrimination.- 3.1 Method.- 3.2 Comparison.- 3.3 Derivation.- 4 Other techniques.- 4.1 Linear confidence bands.- 4.2 Tolerance intervals.- 4.3 Unlimited discrimination intervals.- 4 Nonparametric Techniques.- 1 Many-one sign statistics (Steel).- 1.1 Method.- 1.2 Applications.- 1.3 Comparison.- 1.4 Derivation.- 1.5 Distributions and tables.- 2 k-sample sign statistics.- 2.1 Method.- 2.2 Applications.- 2.3 Comparison.- 2.4 Derivation.- 2.5 Distributions and tables.- 3 Many-one rank statistics (Steel).- 3.1 Method.- 3.2 Applications.- 3.3 Comparison.- 3.4 Derivation.- 3.5 Distributions and tables.- 4 k-sample rank statistics.- 4.1 Method.- 4.2 Applications.- 4.3 Comparison.- 4.4 Derivation.- 4.5 Distributions and tables.- 5 Signed-rank statistics.- 6 Kruskal-Wallis rank statistics (Nemenyi).- 6.1 Method.- 6.2 Applications.- 6.3 Comparison.- 6.4 Derivation.- 6.5 Distributions and tables.- 7 Friedman rank statistics (Nemenyi).- 7.1 Method.- 7.2 Applications.- 7.3 Comparison.- 7.4 Derivation.- 7.5 Distributions and tables.- 8 Other techniques.- 8.1 Permutation tests.- 8.2 Median tests (Nemenyi).- 8.3 Kolmogorov-Smirnov statistics.- 5 Multivariate Techniques.- 1 Single population; covariance scalar unknown.- 1.1 Method.- 1.2 Applications.- 1.3 Comparison.- 1.4 Derivation.- 1.5 Distributions and tables.- 2 Single population; covariance matrix unknown.- 2.1 Method.- 2.2 Applications.- 2.3 Comparison.- 2.4 Derivation.- 2.5 Distributions and tables.- 3 k populations; covariance matrix unknown.- 3.1 Method.- 3.2 Applications.- 3.3 Comparison.- 3.4 Derivation.- 3.5 Distributions and tables.- 4 Other techniques.- 4.1 Variances known; covariances unknown.- 4.2 Variance-covariance intervals.- 4.3 Two-sample confidence intervals of predetermined length.- 6 Miscellaneous Techniques.- 1 Outlier detection.- 2 Multinomial populations.- 2.1 Single population.- 2.2 Several populations.- 2.3 Cross-product ratios.- 2.4 Logistic response curves.- 3 Equality of variances.- 4 Periodogram analysis.- 5 Alternative approaches: selection, ranking, slippage.- A Strong Law For The Expected Error Rate.- B TABLES.- I Percentage points of the studentized range.- II Percentage points of the Bonferroni t statistic.- III Percentage points of the studentized maximum modulus.- IV Percentage points of the many-one t statistics.- V Percentage points of the Duncan multiple range test.- VI Percentage points of the many-one sign statistics.- VIII Percentage points of the many-one rank statistics.- IX Percentage points of the k-sample rank statistics.- Developments in Multiple Comparisons 1966–1976.- 1 Introduction.- 2 Papers of special interest.- 2.1 Probability inequalities.- 2.2 Methods for unbalanced ANOVA.- 2.3 Conditional confidence levels.- 2.4 Empirical Bayes approach.- 2.5 Confidence bands in regression.- 3 References.- 4 Bibliography 1966–1976.- 4.1 Survey articles.- 4.2 Probability inequalities.- 4.3 Tables.- 4.4 Normal multifactor methods.- 4.5 Regression.- 4.6 Categorical data.- 4.7 Nonparametric techniques.- 4.8 Multivariate methods.- 4.9 Miscellaneous.- 4.10 Pre-1966 articles missed in [6].- 4.11 Late additions.- 5 List of journals scanned.- Addendum New Table of the Studentized Maximum Modulus.- Table IIIA Percentage points of the studentized maximum modulus.- Author Index.

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