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Preface VI
Statistical Models 1
Exponential Families 2
Priors and Conjugate Priors for Exponential Families 16
Divergences in Binary Models 31
Information in Bayes Models 52
L[subscript 2]-Differentiability, Fisher Information 58
Solutions to Selected Problems 67
Tests in Models with Monotonicity Properties 75
Stochastic Ordering and Monotone Likelihood Ratio 75
Tests in Binary Models and Models with MLR 83
Solutions to Selected Problems 100
Statistical Decision Theory 104
Decisions in Statistical Models 104
Convergence of Decisions 114
Continuity Properties of the Risk 118
Minimum Average Risk, Bayes Risk, Posterior Risk 121
Bayes and Minimax Decisions 133
[Gamma]-Minimax Decisions 141
Minimax Theorem 146
Complete Classes 149
Solutions to Selected Problems 153
Comparison of Models, Reduction by Sufficiency 156
Comparison and Randomization of Models 156
Comparison of Finite Models by Standard Distributions 166
Sufficiency in Dominated Models 177
Completeness, Ancillarity, and Minimal Sufficiency 188
Solutions to Selected Problems 194
Invariant Statistical Decision Models 198
Invariant Models and Invariant Statistics 198
Invariant Decision Problems 204
Hunt-Stein Theorem 213
Equivariant Estimators, Girshick-Savage Theorem 222
Solutions to Selected Problems 232
Large Sample Approximations of Models and Decisions 235
Distances of Statistical Models 235
Convergence of Models 241
Weak Convergence of Binary Models 248
Asymptotically Normal Models 265
Gaussian Models 266
The LAN and ULAN Property 269
Asymptotic Lower Risk Bounds, Hajek-LeCam Bound 281
Solutions to Selected Problems 287
Estimation 293
Lower Information Bounds in Estimation Problems 293
Unbiased Estimators with Minimal Risk 301
Bayes and Generalized Bayes Estimators 309
Admissibility of Estimators, Shrinkage Estimators 315
Consistency of Estimators 319
Consistency of M-Estimators and MLEs 319
Consistency in Bayes Models 347
Asymptotic Distributions of Estimators 359
Asymptotic Distributions of M-Estimators 359
Asymptotic Distributions of MLEs 374
Asymptotic Normality of the Posterior 379
Local Asymptotic Optimality of MLEs 386
Solutions to Selected Problems 400
Testing 406
Best Tests for Exponential Families 406
Tests for One-Parameter Exponential Families 406
Tests in Multivariate Normal Distributions 417
Tests for d-Parameter Exponential Families 420
Confidence Regions and Confidence Bounds 431
Bayes Tests 437
Uniformly Best Invariant Tests 443
Exponential Rates of Error Probabilities 450
U-Statistics and Rank Statistics 454
Statistics with Estimated Parameters 470
Asymptotic Null Distribution 473
Locally Asymptotically Optimal Tests 485
Testing of Univariate Parameters 485
Testing of Multivariate Parameters 503
Solutions to Selected Problems 510
Selection 516
The Selection Models 516
Optimal Point Selections 520
Point Selections, Loss, and Risk 520
Point Selections in Balanced Models 528
Point Selections in Unbalanced Models 536
Point Selections with Estimation 542
Optimal Subset Selections 547
Subset Selections, Loss, and Risk 547
[Gamma]-Minimax Subset Selections 556
Optimal Multistage Selections 561
Common Sample Size per Stage and Hard Elimination 561
Bayes Sampling Designs for Adaptive Sampling 582
Asymptotically Optimal Point Selections 587
Exponential Rate of Error Probabilities 587
Locally Asymptotically Optimal Point Selections 592
Rank Selection Rules 607
Solutions to Selected Problems 609
Appendix: Topics from Analysis, Measure Theory, and Probability Theory 615
Topics from Analysis 615
Topics from Measure Theory 617
Topics from Probability Theory 623
Appendix: Common Notation and Distributions 631
Common Notation 631
Common Distributions 635
References 640
Author Index 663
Subject Index 668
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