Fence Methods, The (ePub)
(Sprache: Englisch)
This book is about a recently developed class of strategies, known as the fence methods, which fits particularly well in non-conventional and complex model selection problems with practical considerations. The idea involves a procedure to isolate a subgroup...
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This book is about a recently developed class of strategies, known as the fence methods, which fits particularly well in non-conventional and complex model selection problems with practical considerations. The idea involves a procedure to isolate a subgroup of what are known as correct models, of which the optimal model is a member. This is accomplished by constructing a statistical fence, or barrier, to carefully eliminate incorrect models. Once the fence is constructed, the optimal model is selected from amongst those within the fence according to a criterion which can be made flexible. In particular, the criterion of optimality can incorporate consideration of practical interest, thus making model selection a real life practice.Furthermore, this book introduces a data-driven approach, called adaptive fence, which can be used in a wide range of problems involving determination of tuning parameters, or constants. Instead of relying on asymptotic theory, the fence focuses on finite-sample performance, and computation. Such features are particularly suitable to statistics in the new era.This book is about a recently developed class of strategies, known as the fence methods, which fits particularly well in non-conventional and complex model selection problems with practical considerations. The idea involves a procedure to isolate a subgroup of what are known as correct models, of which the optimal model is a member. This is accomplished by constructing a statistical fence, or barrier, to carefully eliminate incorrect models. Once the fence is constructed, the optimal model is selected from amongst those within the fence according to a criterion which can be made flexible. In particular, the criterion of optimality can incorporate consideration of practical interest, thus making model selection a real life practice.Furthermore, this book introduces a data-driven approach, called adaptive fence, which can be used in a wide range of problems involving determination of tuning parameters, or constants. Instead of relying on asymptotic theory, the fence focuses on finite-sample performance, and computation. Such features are particularly suitable to statistics in the new era.Readership: Graduates and researchers interested in a new class of strategies for model selection.Key Features:Introduces a general data-driven procedure, and let the data speak in choosing some critical tuning constantsTargets non-conventional and complex problems, and focuses on finite-sample performance and computationMakes model selection a real life practice
Bibliographische Angaben
- Autoren: Jiming Jiang , Thuan Nguyen
- 2015, 248 Seiten, Englisch
- Verlag: World Scientific Publishing Company
- ISBN-10: 9814596086
- ISBN-13: 9789814596084
- Erscheinungsdatum: 22.09.2015
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- Dateiformat: ePub
- Größe: 9.92 MB
- Mit Kopierschutz
Sprache:
Englisch
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