Simultaneous statistical inference / Rupert G. Miller, Jr.

Por: Miller, Rupert GSeries Springer series in statisticsEditor: New York : Springer-Verlag, c1981Edición: 2nd edDescripción: xvi, 299 p. : il. ; 24 cmISBN: 0387905480Tema(s): Mathematical statisticsOtra clasificación: 62F15 (62G05 62J10)
Contenidos:
Preface to the Second Edition vi Preface to the First Edition vii
1 INTRODUCTION [1]
1 Case of two means [2]
2 Error rates [5]
2.1 Probability of a nonzero family error rate [6]
2.2 Expected family error rate [8]
2.3 Allocation of error [10]
3 Basic techniques [12]
3.1 Repeated normal statistics [12]
3.2 Maximum modulus (Tukey) [14]
3.3 Bonferroni normal statistics [15]
3.4 x2 projections (Scheffe) [16]
3.5 Allocation [22]
3.6 Multiple modulus tests (Duncan) [24]
3.7 Least significant difference test (Fisher) [26]
4 p-mean significance levels [28]
5 Families [31]
2 NORMAL UNIVARIATE TECHNIQUES [37]
1 Studentized range (Tukey) [37]
1.1 Method [37]
1.2 Applications [42]
1.3 Comparison [43]
14 Derivation [44]
1,6 Distributions and tables [47]
F projections (Scheffé) [48]
8.1 Method [48]
8.8 Applications [64]
8.8 Comparison [68]
84 Derivation [68]
8.6 Distributions and tables [87]
Bonferroni t statistics [67]
8.1 Method [67]
8.8 Applications [68]
8.8 Comparison [68]
84 Derivation [69]
8.6 Distributions and tables [70]
Studentized maximum modulus [70]
44 Method [71]
44 Applications [71]
4'8 Comparison [78]
44 Derivation [74]
44 Distributions and tables [76]
Many-one t statistics [76]
6.1 Method [76]
6.8 Applications [78]
6.8 Comparison [78]
6.4 Derivation [78]
6.6 Distributions and tables [79]
Multiple range tests (Duncan) [81]
6.1 Method [88]
6.8 Applications [86]
6.3 Comparison [87]
84 Derivation [88]
6.6 Distributions and tables [89]
Least significant difference test (Fisher) [90]
7.1 Method [90]
7.8 Applications [98]
7.8 Comparison [98]
74 Derivation [98]
7.6 Distributions and tables [94]
Other techniques [94]
8.1 Tukey’s gap-straggler-variance test [94]
8.8 Shortcut methods [96]
8.8 Multiple F tests [97]
8.4 Two-sample confidence intervals of predetermined length [98]
8.6 An improved Bonferroni inequality 101 Power [108]
Robustness [107]
3 REGRESSION TECHNIQUES [109]
1 Regression surface confidence bands [110]
1.1 Method [111]
1.2 Comparison [112]
1.8 Derivation [112]
2 Prediction [114]
2.1 Method [115]
2.2 Comparison [116]
2.3 Derivation [116]
3 Discrimination [117]
3.1 Method [117]
3.2 Comparison [120]
3.3 Derivation [120]
4 Other techniques [121]
4.1 Linear confidence bands [121]
4-2 Tolerance intervals [123]
4-3 Unlimited discrimination intervals [125]
4 NONPARAMETRIC TECHNIQUES [129]
1 Many-one sign statistics (Steel) [130]
1.1 Method [131]
1.2 Applications [133]
1.3 Comparison [133]
1.4 Derivation [134]
1.5 Distributions and tables [135]
2 A:-sample sign statistics [138]
2.1 Method [138]
2.2 Applications [139]
2.3 Comparison [140]
3.4 Derivation [140]
2.5 Distributions and tables [141]
Many-one rank statistics (Steel) [143]
3.1 Method [143]
3.2 Applications [146]
3.3 Comparison [147]
3.4 Derivation [147]
3.5 Distributions and tables [149]
4 k:-sample rank statistics [153]
4-1 Method [153]
4-3 Applications [155]
4.3 Comparison [155]
4-4 Derivation [155]
4.5 Distributions and tables [156]
Signed-rank statistics [157]
Kruskal-Wallis rank statistics (Nemenyi) [165]
6.1 Method [165]
6.2 Applications [167]
6.3 Comparison [168]
6.4 Derivation [169]
6.5 Distributions and tables [170]
7 Friedman rank statistics (Nemenyi) [172]
7.1 Method [173]
7.2 Applications [174]
7.3 Comparison [175]
7.4 Derivation [176]
7.5 Distributions and tables [176]
8 Other techniques [179]
8.1 Permutation tests [179]
8.2 Median tests (Nemenyi) [182]
8.3 Kolmogorov-Smirnov statistics [185]
5 MULTIVARIATE TECHNIQUES [189]
1 Single population; covariance scalar unknown [190]
1.1 Method [190]
1.2 Applications [192]
1.3 Comparison [193]
1-4 Derivation [193]
1.5 Distributions and tables [195]
2 Single population; covariance matrix unknown [195]
2.1 Method [196]
2.2 Applications [197]
2.3 Comparison [200]
2.4 Derivation [200]
2.5 Distributions and tables [201]
3 k populations; covariance matrix unknown [202]
3.1 Method [202]
3.2 Applications [204]
3.3 Comparison [205]
8-4 Derivation [205]
3.5 Distributions and tables [206]
4 Other techniques [208]
4.1 Variances known; covariances unknown [208]
4-2 Variance-covariance intervals [209]
4-3 Two-sample confidence intervals of predetermined length [209]
6 MISCELLANEOUS TECHNIQUES [211]
1 Outlier detection [211]
2 Multinomial populations [215]
2.1 Single population [215]
2.2 Several populations [218]
2.3 Cross-product ratios [220]
2.4 Logistic response curves [220]
3 Equality of variances [221]
4 Periodogram analysis [223]
5 Alternative approaches: selection, ranking, slippage [226]
A STRONG LAW FOR THE EXPECTED ERROR RATE [231]
B TABLES [233]
I Percentage points of the studentized range [234]
II Percentage points of the Bonferroni t statistic [238]
III Percentage points of the studentized maximum modulus [239]
IV Percentage points of the many-one t statistics [240]
V Percentage points of the Duncan multiple range test [243]
VI Percentage points of the many-one sign statistics [247]
VII Percentage points of the k-sample sign statistics [249]
VIII Percentage points of the many-one rank statistics [250]
IX Percentage points of the k-sample rank statistics [252]
DEVELOPMENTS IN MULTIPLE COMPARISONS
1966-1976 [253]
1 Introduction [253]
2 Papers of special interest [254]
2.1 Probability inequalities [254]
2.2 Methods for unbalanced ANOVA [255]
2.3 Conditional confidence levels [256]
2.4 Empirical Bayes approach [257]
2.5 Confidence bands in regression [259]
3 References [261]
4 Bibliography 1966-1976 [261]
4.1 Survey articles [261]
4.2 Probability inequalities [261]
4.3 Tables [262]
4.4 Normal multifactor methods [263]
4.5 Regression [267]
4.6 Categorical data [269]
4.7 Nonparametric techniques [270]
4.8 Multivariate methods [270]
4.9 Miscellaneous [271]
4.10 Pre-1966 articles missed in [6] [273]
4.11 Late additions [273]
5 List of journals scanned [274]
ADDENDUM NEW TABLE OF THE STUDENTIZED MAXIMUM MODULUS [277]
Table IIIA Percentage points of the studentized maximum modulus [278]
BIBLIOGRAPHY [279]
AUTHOR INDEX [295]
SUBJECT INDEX [297]
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Libros Libros Instituto de Matemática, CONICET-UNS
Libros ordenados por tema 62 M647-2 (Browse shelf) Available A-5820

DISEÑO EXPERIMENTAL


Incluye índices.

Bibliografía: p. 279-293.

Preface to the Second Edition vi Preface to the First Edition vii --
1 INTRODUCTION [1] --
1 Case of two means [2] --
2 Error rates [5] --
2.1 Probability of a nonzero family error rate [6] --
2.2 Expected family error rate [8] --
2.3 Allocation of error [10] --
3 Basic techniques [12] --
3.1 Repeated normal statistics [12] --
3.2 Maximum modulus (Tukey) [14] --
3.3 Bonferroni normal statistics [15] --
3.4 x2 projections (Scheffe) [16] --
3.5 Allocation [22] --
3.6 Multiple modulus tests (Duncan) [24] --
3.7 Least significant difference test (Fisher) [26] --
4 p-mean significance levels [28] --
5 Families [31] --
2 NORMAL UNIVARIATE TECHNIQUES [37] --
1 Studentized range (Tukey) [37] --
1.1 Method [37] --
1.2 Applications [42] --
1.3 Comparison [43] --
14 Derivation [44] --
1,6 Distributions and tables [47] --
F projections (Scheffé) [48] --
8.1 Method [48] --
8.8 Applications [64] --
8.8 Comparison [68] --
84 Derivation [68] --
8.6 Distributions and tables [87] --
Bonferroni t statistics [67] --
8.1 Method [67] --
8.8 Applications [68] --
8.8 Comparison [68] --
84 Derivation [69] --
8.6 Distributions and tables [70] --
Studentized maximum modulus [70] --
44 Method [71] --
44 Applications [71] --
4'8 Comparison [78] --
44 Derivation [74] --
44 Distributions and tables [76] --
Many-one t statistics [76] --
6.1 Method [76] --
6.8 Applications [78] --
6.8 Comparison [78] --
6.4 Derivation [78] --
6.6 Distributions and tables [79] --
Multiple range tests (Duncan) [81] --
6.1 Method [88] --
6.8 Applications [86] --
6.3 Comparison [87] --
84 Derivation [88] --
6.6 Distributions and tables [89] --
Least significant difference test (Fisher) [90] --
7.1 Method [90] --
7.8 Applications [98] --
7.8 Comparison [98] --
74 Derivation [98] --
7.6 Distributions and tables [94] --
Other techniques [94] --
8.1 Tukey’s gap-straggler-variance test [94] --
8.8 Shortcut methods [96] --
8.8 Multiple F tests [97] --
8.4 Two-sample confidence intervals of predetermined length [98] --
8.6 An improved Bonferroni inequality 101 Power [108] --
Robustness [107] --
3 REGRESSION TECHNIQUES [109] --
1 Regression surface confidence bands [110] --
1.1 Method [111] --
1.2 Comparison [112] --
1.8 Derivation [112] --
2 Prediction [114] --
2.1 Method [115] --
2.2 Comparison [116] --
2.3 Derivation [116] --
3 Discrimination [117] --
3.1 Method [117] --
3.2 Comparison [120] --
3.3 Derivation [120] --
4 Other techniques [121] --
4.1 Linear confidence bands [121] --
4-2 Tolerance intervals [123] --
4-3 Unlimited discrimination intervals [125] --
4 NONPARAMETRIC TECHNIQUES [129] --
1 Many-one sign statistics (Steel) [130] --
1.1 Method [131] --
1.2 Applications [133] --
1.3 Comparison [133] --
1.4 Derivation [134] --
1.5 Distributions and tables [135] --
2 A:-sample sign statistics [138] --
2.1 Method [138] --
2.2 Applications [139] --
2.3 Comparison [140] --
3.4 Derivation [140] --
2.5 Distributions and tables [141] --
Many-one rank statistics (Steel) [143] --
3.1 Method [143] --
3.2 Applications [146] --
3.3 Comparison [147] --
3.4 Derivation [147] --
3.5 Distributions and tables [149] --
4 k:-sample rank statistics [153] --
4-1 Method [153] --
4-3 Applications [155] --
4.3 Comparison [155] --
4-4 Derivation [155] --
4.5 Distributions and tables [156] --
Signed-rank statistics [157] --
Kruskal-Wallis rank statistics (Nemenyi) [165] --
6.1 Method [165] --
6.2 Applications [167] --
6.3 Comparison [168] --
6.4 Derivation [169] --
6.5 Distributions and tables [170] --
7 Friedman rank statistics (Nemenyi) [172] --
7.1 Method [173] --
7.2 Applications [174] --
7.3 Comparison [175] --
7.4 Derivation [176] --
7.5 Distributions and tables [176] --
8 Other techniques [179] --
8.1 Permutation tests [179] --
8.2 Median tests (Nemenyi) [182] --
8.3 Kolmogorov-Smirnov statistics [185] --
5 MULTIVARIATE TECHNIQUES [189] --
1 Single population; covariance scalar unknown [190] --
1.1 Method [190] --
1.2 Applications [192] --
1.3 Comparison [193] --
1-4 Derivation [193] --
1.5 Distributions and tables [195] --
2 Single population; covariance matrix unknown [195] --
2.1 Method [196] --
2.2 Applications [197] --
2.3 Comparison [200] --
2.4 Derivation [200] --
2.5 Distributions and tables [201] --
3 k populations; covariance matrix unknown [202] --
3.1 Method [202] --
3.2 Applications [204] --
3.3 Comparison [205] --
8-4 Derivation [205] --
3.5 Distributions and tables [206] --
4 Other techniques [208] --
4.1 Variances known; covariances unknown [208] --
4-2 Variance-covariance intervals [209] --
4-3 Two-sample confidence intervals of predetermined length [209] --
6 MISCELLANEOUS TECHNIQUES [211] --
1 Outlier detection [211] --
2 Multinomial populations [215] --
2.1 Single population [215] --
2.2 Several populations [218] --
2.3 Cross-product ratios [220] --
2.4 Logistic response curves [220] --
3 Equality of variances [221] --
4 Periodogram analysis [223] --
5 Alternative approaches: selection, ranking, slippage [226] --
A STRONG LAW FOR THE EXPECTED ERROR RATE [231] --
B TABLES [233] --
I Percentage points of the studentized range [234] --
II Percentage points of the Bonferroni t statistic [238] --
III Percentage points of the studentized maximum modulus [239] --
IV Percentage points of the many-one t statistics [240] --
V Percentage points of the Duncan multiple range test [243] --
VI Percentage points of the many-one sign statistics [247] --
VII Percentage points of the k-sample sign statistics [249] --
VIII Percentage points of the many-one rank statistics [250] --
IX Percentage points of the k-sample rank statistics [252] --
DEVELOPMENTS IN MULTIPLE COMPARISONS --
1966-1976 [253] --
1 Introduction [253] --
2 Papers of special interest [254] --
2.1 Probability inequalities [254] --
2.2 Methods for unbalanced ANOVA [255] --
2.3 Conditional confidence levels [256] --
2.4 Empirical Bayes approach [257] --
2.5 Confidence bands in regression [259] --
3 References [261] --
4 Bibliography 1966-1976 [261] --
4.1 Survey articles [261] --
4.2 Probability inequalities [261] --
4.3 Tables [262] --
4.4 Normal multifactor methods [263] --
4.5 Regression [267] --
4.6 Categorical data [269] --
4.7 Nonparametric techniques [270] --
4.8 Multivariate methods [270] --
4.9 Miscellaneous [271] --
4.10 Pre-1966 articles missed in [6] [273] --
4.11 Late additions [273] --
5 List of journals scanned [274] --
ADDENDUM NEW TABLE OF THE STUDENTIZED MAXIMUM MODULUS [277] --
Table IIIA Percentage points of the studentized maximum modulus [278] --
BIBLIOGRAPHY [279] --
AUTHOR INDEX [295] --
SUBJECT INDEX [297] --

MR, 82c:62048

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