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This book acquaints readers with the concepts of classical finite sample size decision theory and modern asymptotic decision theory in the sense of LeCam. To this end, systematic applications to
the fields of parameter estimation, testing hypotheses, and selection of populations are included.
Some of the problems contain additional information in order to round off the results, whereas other problems, equipped with solutions, have a more technical character. The latter play the role of auxiliary results and as such they allow readers to become familiar with the advanced techniques of mathematical statistics.
The central theme of this book is what optimal decisions are in general and in specific decision problems, and how to derive them. Optimality is understood in terms of the expected loss, i.e. the risk, or some functional of it. In this regard estimators, tests, and selection rules are initially considered in the book side by side