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The Minimax Estimation Of Linear Models Under Incorrect Prior Restrictions
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Book Synopsis The Minimax Estimation of Linear Models Under Incorrect Prior Restrictions by : Timo Teräsvirta
Download or read book The Minimax Estimation of Linear Models Under Incorrect Prior Restrictions written by Timo Teräsvirta and published by . This book was released on 1980 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Minimax Estimation in Linear Regression Under Restrictions by : Helge Blaker
Download or read book Minimax Estimation in Linear Regression Under Restrictions written by Helge Blaker and published by . This book was released on 1998 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis On minimax estimation in linear regression models with ellipsoidal constraints by : Norbert Christopeit
Download or read book On minimax estimation in linear regression models with ellipsoidal constraints written by Norbert Christopeit and published by . This book was released on 1991 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Minimax estimation in linear regression with convex polyhedral constraints by : Peter Stahlecker
Download or read book Minimax estimation in linear regression with convex polyhedral constraints written by Peter Stahlecker and published by . This book was released on 1990 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Linear Models and Generalizations by : C. Radhakrishna Rao
Download or read book Linear Models and Generalizations written by C. Radhakrishna Rao and published by Springer Science & Business Media. This book was released on 2007-10-15 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: Revised and updated with the latest results, this Third Edition explores the theory and applications of linear models. The authors present a unified theory of inference from linear models and its generalizations with minimal assumptions. They not only use least squares theory, but also alternative methods of estimation and testing based on convex loss functions and general estimating equations. Highlights of coverage include sensitivity analysis and model selection, an analysis of incomplete data, an analysis of categorical data based on a unified presentation of generalized linear models, and an extensive appendix on matrix theory.
Book Synopsis A Note on Minimax-estimation in Regression Models with Affine Restrictions by : Hilmar Drygas
Download or read book A Note on Minimax-estimation in Regression Models with Affine Restrictions written by Hilmar Drygas and published by . This book was released on 1988 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Prior Information in Linear Models by : Helge Toutenburg
Download or read book Prior Information in Linear Models written by Helge Toutenburg and published by John Wiley & Sons. This book was released on 1982 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Minimax Estimation in Linear Regression with Convex Polyhedral Constraints by : P. Stahlecker
Download or read book Minimax Estimation in Linear Regression with Convex Polyhedral Constraints written by P. Stahlecker and published by . This book was released on 1990 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Minimax Estimation in Linear Models by : Hilmar Drygas
Download or read book Minimax Estimation in Linear Models written by Hilmar Drygas and published by . This book was released on 1990 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Minimax Estimation with Respect to Restricted Parameter Sets by : Soebanar
Download or read book Minimax Estimation with Respect to Restricted Parameter Sets written by Soebanar and published by . This book was released on 1987 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Linear Models by : C.Radhakrishna Rao
Download or read book Linear Models written by C.Radhakrishna Rao and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is based on both authors' several years of experience in teaching linear models at various levels. It gives an up-to-date account of the theory and applications of linear models. The book can be used as a text for courses in statistics at the graduate level and as an accompanying text for courses in other areas. Some of the highlights in this book are as follows. A relatively extensive chapter on matrix theory (Appendix A) provides the necessary tools for proving theorems discussed in the text and offers a selection of classical and modern algebraic results that are useful in research work in econometrics, engineering, and optimization theory. The matrix theory of the last ten years has produced a series of fundamental results about the definiteness of matrices, especially for the differences of matrices, which enable superiority comparisons of two biased estimates to be made for the first time. We have attempted to provide a unified theory of inference from linear models with minimal assumptions. Besides the usual least-squares theory, alternative methods of estimation and testing based on convex loss func tions and general estimating equations are discussed. Special emphasis is given to sensitivity analysis and model selection. A special chapter is devoted to the analysis of categorical data based on logit, loglinear, and logistic regression models. The material covered, theoretical discussion, and its practical applica tions will be useful not only to students but also to researchers and con sultants in statistics.
Book Synopsis Robustness of Statistical Methods and Nonparametric Statistics by : Dieter Rasch
Download or read book Robustness of Statistical Methods and Nonparametric Statistics written by Dieter Rasch and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains most of the invited and contributed papers presented at the Conference on Robustness of Statistical Methods and Nonparametric Statistics held in the castle oj'Schwerin, Mai 29 - June 4 1983. This conference was organized by the Mathematical Society of the GDR in cooperation with the Society of Physical and Mathematical Biology of the GDR, the GDR-Region of the International Biometric Society and the Academy of Agricultural Sciences of the GDR. All papers included were thoroughly reviewed by scientist listed under the heading "Editorial Collabora tories·'. Some contributions, we are sorry to report, were not recommended for publi cation by the rf'vif'wers and do not appear in these proceedings. The editors thank the reviewers for their valuable comments and suggestions. The conference was organizf'd bv a Programme Committee, its chairman was Prof. Dr. Dieter Rasch (Research Centre of Animal Production, Dummerstorf-Rostock). The members of the Programme Committee were Prof. Dr., Johannes Adam (Martin-Luther-University Halle) Prof. Dr. Heinz Ahrens (Academy of Sciences of the GDR, Berlin) Doz. Dr. Jana Jureckova (Charles University Praha) Prof. Dr. Moti Lal Tiku (McMaster University, Hamilton, Ontario) The aim of the conference was to discuss several aspects of robustness but mainly to present new results regarding the robustness of classical statistical methods especially tests, confidence estimations, and selection procedures, and to compare their perfor mance with nonparametric procedures. Robustness in this sens~ is understood as intensivity against. violation of the normal assumption.
Book Synopsis Minimax estimation with additional linear restrictions by : Bernd Schipp
Download or read book Minimax estimation with additional linear restrictions written by Bernd Schipp and published by . This book was released on 1985 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Regression Estimators by : Marvin H. J. Gruber
Download or read book Regression Estimators written by Marvin H. J. Gruber and published by Academic Press. This book was released on 2014-05-10 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regression Estimators: A Comparative Study presents, compares, and contrasts the development and the properties of the ridge type estimators that result from both Bayesian and non-Bayesian (frequentist) methods. The book is divided into four parts. The first part (Chapters I and II) discusses the need for alternatives to least square estimators, gives a historical survey of the literature and summarizes basic ideas in Matrix Theory and Statistical Decision Theory used throughout the book. The second part (Chapters III and IV) covers the estimators from both the Bayesian and from the frequentist points of view and explores the mathematical relationships between them. The third part (Chapters V-VIII) considers the efficiency of the estimators with and without averaging over a prior distribution. Part IV, the final two chapters IX and X, suggests applications of the methods and results of Chapters III-VII to Kaiman Filters and Analysis of Variance, two very important areas of application. Statisticians and workers in fields that use statistical methods who would like to know more about the analytical properties of ridge type estimators will find the book invaluable.
Book Synopsis Minimax Estimation in the Linear Regression Model with Fuzzy Inequality Constraints by : Henning Knautz
Download or read book Minimax Estimation in the Linear Regression Model with Fuzzy Inequality Constraints written by Henning Knautz and published by . This book was released on 2000 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Minimax Estimation with Structured Data by : Jan-Christian Klaus Hütter
Download or read book Minimax Estimation with Structured Data written by Jan-Christian Klaus Hütter and published by . This book was released on 2019 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern statistics often deals with high-dimensional problems that suffer from poor performance guarantees and from the curse of dimensionality. In this thesis, we study how structural assumptions can be used to overcome these difficulties in several estimation problems, spanning three different areas of statistics: shape-constrained estimation, causal discovery, and optimal transport. In the area of shape-constrained estimation, we study the estimation of matrices, first under the assumption of bounded total-variation (TV) and second under the assumption that the underlying matrix is Monge, or supermodular. While the first problem has a long history in image denoising, the latter structure has so far been mainly investigated in the context of computer science and optimization. For TV denoising, we provide fast rates that are adaptive to the underlying edge sparsity of the image, as well as generalizations to other graph structures, including higher-dimensional grid-graphs. For the estimation of Monge matrices, we give near minimax rates for their estimation, including the case where latent permutations act on the rows and columns of the matrix. In the latter case, we also give two computationally efficient and consistent estimators. Moreover, we show how to obtain estimation rates in the related problem of estimating continuous totally positive distributions in 2D. In the area of causal discovery, we investigate a linear cyclic causal model and give an estimator that is near minimax optimal for causal graphs of bounded in-degree. In the area of optimal transport, we introduce the notion of the transport rank of a coupling and provide empirical and theoretical evidence that it can be used to significantly improve rates of estimation of Wasserstein distances and optimal transport plans. Finally, we give near minimax optimal rates for the estimation of smooth optimal transport maps based on a wavelet regularization of the semi-dual objective.
Book Synopsis Directionally Minimax Mean Square Error Estimation in Linear Models by : Guillermo Pedro Zarate De Lara
Download or read book Directionally Minimax Mean Square Error Estimation in Linear Models written by Guillermo Pedro Zarate De Lara and published by . This book was released on 1977 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: