Shrinkage Estimation(Springer Series in Statistics)

数学史

原   价:
1721.25
售   价:
1377.00
优惠
平台大促 低至8折优惠
发货周期:外国库房发货,通常付款后3-5周到货
出  版 社
出版时间
2018年12月06日
装      帧
ISBN
9783030021849
复制
页      码
333
语      种
英文
综合评分
暂无评分
我 要 买
- +
库存 100 本
  • 图书详情
  • 目次
  • 买家须知
  • 书评(0)
  • 权威书评(0)
图书简介
This book provides a coherent framework for understanding shrinkage estimation in statistics. The term refers to modifying a classical estimator by moving it closer to a target which could be known a priori or arise from a model. The goal is to construct estimators with improved statistical properties. The book focuses primarily on point and loss estimation of the mean vector of multivariate normal and spherically symmetric distributions.
Chapter 1 reviews the statistical and decision theoretic terminology and results that will be used throughout the book.
Chapter 2 is concerned with estimating the mean vector of a multivariate normal distribution under quadratic loss from a frequentist perspective. In Chapter 3 the authors take a Bayesian view of shrinkage estimation in the normal setting. Chapter 4 introduces the general classes of spherically and elliptically symmetric distributions. Point and loss estimation for these broad classes are studied in subsequent chapters. In particular, Chapter 5 extends many of the results from Chapters 2 and 3 to spherically and elliptically symmetric distributions.
Chapter 6 considers the general linear model with spherically symmetric error distributions when a residual vector is available. Chapter 7 then considers the problem of estimating a location vector which is constrained to lie in a convex set. Much of the chapter is devoted to one of two types of constraint sets, balls and polyhedral cones. In Chapter 8 the authors focus on loss estimation and data-dependent evidence reports.
Appendices cover a number of technical topics including weakly differentiable functions; examples where Stein?s identity doesn?t hold; Stein?s lemma and Stokes? theorem for smooth boundaries; harmonic, superharmonic and subharmonic functions; and modified Bessel functions.
本书暂无推荐
本书暂无推荐
看了又看
  • 上一个
  • 下一个