Screen LibraryThe fence methods /
"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,...
Saved in:
| Main Authors: | |
|---|---|
| Corporate Authors: | |
| Group Author: | |
| Published: |
World Scientific Publishing Co. Pte Ltd.,
|
| Publisher Address: | Singapore : |
| Publication Dates: | 2016. |
| Literature type: | eBook |
| Language: | English |
| Subjects: | |
| Online Access: |
http://www.worldscientific.com/worldscibooks/10.1142/9116#t=toc |
| Summary: |
"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."-- |
| Item Description: | Title from PDF file title page (viewed December 7, 2015). |
| Carrier Form: | 1 online resource (xiv, 233 pages) : illustrations (some color) |
| Bibliography: | Includes bibliographical references (pages 221-229) and index. |
| ISBN: |
9789814596077 (ebook) 9814596078 (ebook) |
| Index Number: | QA171 |
| CLC: | O153.1 |