This brilliant volume is a one-stop shop that presents the main ideas of decision theory in an organized, balanced, and mathematically rigorous manner, while observing statistical relevance. All of the major topics are introduced at an elementary level, then developed incrementally to higher levels.

This book presents the main ideas of decision theory in an organized, balanced, and mathematically rigorous manner, while observing statistical relevance. It is written for advanced graduate students, Ph.D. students, and researchers in mathematical statistics and decision theory. All major topics are introduced on a fairly elementary level and then developed gradually to higher levels. The book is self-contained as it provides full proofs, worked-out examples, and problems. It can be used as a basis for graduate courses, seminars, Ph.D. programs, self-studies, and as a reference book. With its broad coverage of decision theory that includes results from other more specialized books as well as new material, this book is one of a kind and fills the gap between standard graduate texts in mathematical statistics and advanced monographs on modern asymptotic theory.

Inhalt
Statistical Models.- Tests in Models with Monotonicity Properties.- Statistical Decision Theory.- Comparison of Models, Reduction by.- Invariant Statistical Decision Models.- Large Sample Approximations of Models and Decisions.- Estimation.- Testing.- Selection.