Preface -- Contents -- Statistical Models -- Exponential Families -- Priors and Conjugate Priors for Exponential Families -- Divergences in Binary Models -- Information in Bayes Models -- L2-Differentiability, Fisher Information -- Solutions to Selected Problems -- Tests in Models with Monotonicity Properties -- Stochastic Ordering and Monotone Likelihood Ratio -- Tests in Binary Models and Models with MLR -- Solutions to Selected Problems -- Statistical Decision Theory -- Decisions in Statistical Models -- Convergence of Decisions -- Continuity Properties of the Risk -- Minimum Average Risk, Bayes Risk, Posterior Risk -- Bayes and Minimax Decisions -- -Minimax Decisions -- Minimax Theorem -- Complete Classes -- Solutions to Selected Problems -- Comparison of Models, Reduction by Sufficiency -- Comparison and Randomization of Models -- Comparison of Finite Models by Standard Distributions -- Sufficiency in Dominated Models -- Completeness, Ancillarity, and Minimal Sufficiency -- Solutions to Selected Problems -- Invariant Statistical Decision Models -- Invariant Models and Invariant Statistics -- Invariant Decision Problems -- Hunt--Stein Theorem -- Equivariant Estimators, Girshick--Savage Theorem -- Solutions to Selected Problems -- Large Sample Approximations of Models and Decisions -- Distances of Statistical Models -- Convergence of Models -- Weak Convergence of Binary Models -- Asymptotically Normal Models -- Gaussian Models -- The LAN and ULAN Property -- Asymptotic Lower Risk Bounds, Hájek--LeCam Bound -- Solutions to Selected Problems -- Estimation -- Lower Information Bounds in Estimation Problems -- Unbiased Estimators with Minimal Risk -- Bayes and Generalized Bayes Estimators -- Admissibility of Estimators, Shrinkage Estimators -- Consistency of Estimators -- Consistency of M-Estimators and MLEs -- Consistency in Bayes Models.

Asymptotic Distributions of Estimators -- Asymptotic Distributions of M-Estimators -- Asymptotic Distributions of MLEs -- Asymptotic Normality of the Posterior -- Local Asymptotic Optimality of MLEs -- Solutions to Selected Problems -- Testing -- Best Tests for Exponential Families -- Tests for One--Parameter Exponential Families -- Tests in Multivariate Normal Distributions -- Tests for d-Parameter Exponential Families -- Confidence Regions and Confidence Bounds -- Bayes Tests -- Uniformly Best Invariant Tests -- Exponential Rates of Error Probabilities -- U-Statistics and Rank Statistics -- Statistics with Estimated Parameters -- Asymptotic Null Distribution -- Locally Asymptotically Optimal Tests -- Testing of Univariate Parameters -- Testing of Multivariate Parameters -- Solutions to Selected Problems -- Selection -- The Selection Models -- Optimal Point Selections -- Point Selections, Loss, and Risk -- Point Selections in Balanced Models -- Point Selections in Unbalanced Models -- Point Selections with Estimation -- Optimal Subset Selections -- Subset Selections, Loss, and Risk -- -Minimax Subset Selections -- Optimal Multistage Selections -- Common Sample Size per Stage and Hard Elimination -- Bayes Sampling Designs for Adaptive Sampling -- Asymptotically Optimal Point Selections -- Exponential Rate of Error Probabilities -- Locally Asymptotically Optimal Point Selections -- Rank Selection Rules -- Solutions to Selected Problems -- Appendix: Topics from Analysis, Measure Theory, and Probability Theory -- Topics from Analysis -- Topics from Measure Theory -- Topics from Probability Theory -- Appendix: Common Notation and Distributions -- Common Notation -- Common Distributions -- References -- Author Index -- Subject Index.