定價
：NT$ 5490 元若需訂購本書，請電洽客服 02-25006600[分機130、131]。
相關商品
商品簡介
作者簡介
商品簡介
An examination of mathematical formulations of ridge-regression-type estimators points to a curious observation: estimators can be derived by both Bayesian and Frequentist methods. In this updated and expanded edition of his 1990 treatise on the subject, Marvin H. J. Gruber presents, compares, and contrasts the development and properties of ridge-type estimators from these two philosophically different points of view.
The book is organized into five sections. Part I gives a historical survey of the literature and summarizes basic ideas in matrix theory and statistical decision theory. Part II explores the mathematical relationships between estimators from both Bayesian and Frequentist points of view. Part III considers the efficiency of estimators with and without averaging over a prior distribution. Part IV applies the methods and results discussed in the previous two sections to the Kalman Filter, analysis of variance models, and penalized splines. Part V surveys recent developments in the field. These include efficiencies of ridge-type estimators for loss functions other than squared error loss functions and applications to information geometry. Gruber also includes an updated historical survey and bibliography.
With more than 150 exercises, Regression Estimators is a valuable resource for graduate students and professional statisticians.
Praise for the first edition
"A comprehensive treatment...valuable to statisticians who would like to know more about the analytical properties of ridge-type estimators." ---Journal of the American Statistical Association
"Highly recommended to anyone working on advanced applications or research in estimation in linear models."---Technometrics
The book is organized into five sections. Part I gives a historical survey of the literature and summarizes basic ideas in matrix theory and statistical decision theory. Part II explores the mathematical relationships between estimators from both Bayesian and Frequentist points of view. Part III considers the efficiency of estimators with and without averaging over a prior distribution. Part IV applies the methods and results discussed in the previous two sections to the Kalman Filter, analysis of variance models, and penalized splines. Part V surveys recent developments in the field. These include efficiencies of ridge-type estimators for loss functions other than squared error loss functions and applications to information geometry. Gruber also includes an updated historical survey and bibliography.
With more than 150 exercises, Regression Estimators is a valuable resource for graduate students and professional statisticians.
Praise for the first edition
"A comprehensive treatment...valuable to statisticians who would like to know more about the analytical properties of ridge-type estimators." ---Journal of the American Statistical Association
"Highly recommended to anyone working on advanced applications or research in estimation in linear models."---Technometrics
作者簡介
Marvin H. J. Gruber is a professor of mathematics and statistics at the Rochester Institute of Technology.
您曾經瀏覽過的商品
購物須知
外文書商品之書封，為出版社提供之樣本。實際出貨商品，以出版社所提供之現有版本為主。部份書籍，因出版社供應狀況特殊，匯率將依實際狀況做調整。
無庫存之商品，在您完成訂單程序之後，將以空運的方式為你下單調貨。為了縮短等待的時間，建議您將外文書與其他商品分開下單，以獲得最快的取貨速度，平均調貨時間為1~2個月。
為了保護您的權益，「三民網路書店」提供會員七日商品鑑賞期(收到商品為起始日)。
若要辦理退貨，請在商品鑑賞期內寄回，且商品必須是全新狀態與完整包裝(商品、附件、發票、隨貨贈品等)否則恕不接受退貨。