# e-Book Restricted Parameter Space Estimation Problems: Admissibility and Minimaxity Properties (Lecture Notes in Statistics) download

## by Constance van Eeden

**ISBN:**0387337474

**ISBN13:**978-0387337470

**Language:**English

**Publisher:**Springer; 2006 edition (September 21, 2006)

**Pages:**168

**Category:**Mathematics

**Subategory:**Math Science

**ePub size:**1830 kb

**Fb2 size:**1817 kb

**DJVU size:**1547 kb

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Constance van Eeden (Author). Series: Lecture Notes in Statistics (Book 188). Find all the books, read about the author, and more. Constance van Eeden is Professeur émérite at the Université de Montréal, Honorary Professor at The University of British Columbia, and Professeure associée at the Université du Québec à Montréal. She previously held appointments at the Centrum voor Wiskunde en Informatica (1951–1960), Michigan State University (1960–1961), University of Minnesota (1961–1965), and Université de Montréal (1965–1989).

This monograph is addressed to anyone interested in the subject of restrict- parameter-space estimation .

This monograph is addressed to anyone interested in the subject of restrict- parameter-space estimation, and in particular to those who want to learn, or bring their knowledge up to date, about (in)admissibility and minimaxity problems for such parameter spaces. The coverage starts in the early 1950s when the subject of inference for - stricted parameter spaces began to be studied and ends around the middle of 2004. It presents known, and also some new, results on (in)admissibility and minimaxity for nonsequential point estimation problems in restricted ?ni- dimensional parameter spaces.

oceedings{S, title {Restricted parameter space estimation problems : admissibility and . A statement of the problem, the notation and some definitions. (In)admissibility and dominators.

oceedings{S, title {Restricted parameter space estimation problems : admissibility and minimaxity properties}, author {Constance van Eeden}, year {2006} }. Constance van Eeden. Introduction: Some history and some examples. Minimax estimators and their admissibility. Presence of nuisance parameters. Existence of MLEs and algorithms to compute them. View PDF. Save to Library.

Restricted Parameter Space Estimation: Admissibility and Minimaxity. Lecture Notes in Statistics. This paper discusses the problem of estimating a linear relationship between two variables observed with errors. ARTICLE IN PRESS O. Davidov, V. Griskin, Statistics & Probability Letters 78 (2008) 508–517 517. Improving Efficiency by Shrinkage. It focuses on confidence intervals for the slope parameter and confidence regions for the intercept and slope parameters in Gaussian models. A compendium of existing results as well as new results are presented.

Автор: Eeden Constance van Название: Restricted Parameter Space Estimation Problems . This book takes on these fundamental and challenging problems, introducing students and professionals to the broad range of approaches that lie in the realm of inverse theory.

This book takes on these fundamental and challenging problems, introducing students and professionals to the broad range of approaches that lie in the realm of inverse theory.

Restricted Parameter Space Estimation Problems: Admissibility and Minimaxity Properties (Lecture Notes in Statistics). Category: Техника, Аэрокосмическое оборудование.

Member Institute of Mathematics Statistics (council 1977-1980), Canada Mathematics Society (board directors 1981-1983), Statistical Society of Canada (Gold Medal award 1990), American Statistical Association.

Restricted parameter space estimation problems : admissibility and minimaxity properties, Constance van Eeden. PUBLISHER: New York : Springer, c2006. SERIES: Lecture notes in statistics ; 188. Call number: QA 27. Author: Kogan, Jacob, 1954-. TITLE: Introduction to clustering large and high-dimensional data, Jacob Kogan.

van Eeden, C. (2006). Space Estimation Problems; Admissibility and Minimaxity Properties. Lecture Notes in Statistics 188, Springer, New York. The Institute of Mathematical Statistics and the Bernoulli Society.

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