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- catalog abstract "This book presents the modern theory of nonparametric goodness-of-fit testing. The study is based on an asymptotic version of the minimax approach. The methods for the construction of asymptotically optimal, rate optimal, and optimal adaptive test procedures are developed. The authors present many new results that demonstrate the principal differences between nonparametric goodness-of-fit testing problems with parametric goodness-of-fit testing problems and with non-parametric estimation problems. This book fills the gap in modern nonparametric statistical theory by discussing hypothesis testing. The book is addressed to mathematical statisticians who are interesting in the theory of non-parametric statistical inference. It will be of interest to specialists who are dealing with applied non-parametric statistical problems that are relevant in signal detection and transmission and in technical and medical diagnostics among others.".
- catalog contributor b12623081.
- catalog contributor b12623082.
- catalog created "c2003.".
- catalog date "2003".
- catalog date "c2003.".
- catalog dateCopyrighted "c2003.".
- catalog description "Includes bibliographical references (p. [444]-449) and indexes.".
- catalog description "Introduction -- Non-Gaussian Asymptotics -- Gaussian Asymptotics -- Test Procedures -- Gaussian Asymptotics: Reduction to Extreme Problems -- Extreme Problems for Ellipsoids -- Extreme Problems for Besov Bodies.".
- catalog description "This book presents the modern theory of nonparametric goodness-of-fit testing. The study is based on an asymptotic version of the minimax approach. The methods for the construction of asymptotically optimal, rate optimal, and optimal adaptive test procedures are developed. The authors present many new results that demonstrate the principal differences between nonparametric goodness-of-fit testing problems with parametric goodness-of-fit testing problems and with non-parametric estimation problems. This book fills the gap in modern nonparametric statistical theory by discussing hypothesis testing. The book is addressed to mathematical statisticians who are interesting in the theory of non-parametric statistical inference. It will be of interest to specialists who are dealing with applied non-parametric statistical problems that are relevant in signal detection and transmission and in technical and medical diagnostics among others.".
- catalog extent "xiv, 452 p. ;".
- catalog identifier "0387955313 (softcover : acid-free paper)".
- catalog isPartOf "Lecture notes in statistics (Springer-Verlag) ; v. 169.".
- catalog isPartOf "Lectures notes in statistics ; 169".
- catalog issued "2003".
- catalog issued "c2003.".
- catalog language "eng".
- catalog publisher "New York : Springer,".
- catalog subject "519.5/4 21".
- catalog subject "Goodness-of-fit tests.".
- catalog subject "Mathematical statistics.".
- catalog subject "Nonparametric statistics.".
- catalog subject "QA277 .I54 2003".
- catalog subject "Statistics.".
- catalog tableOfContents "Introduction -- Non-Gaussian Asymptotics -- Gaussian Asymptotics -- Test Procedures -- Gaussian Asymptotics: Reduction to Extreme Problems -- Extreme Problems for Ellipsoids -- Extreme Problems for Besov Bodies.".
- catalog title "Nonparametric goodness-of-fit testing under Gaussian models / Yu I. Ingster, I. A. Suslina.".
- catalog type "text".