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Minimax Linear Regression Estimators With Application To Ridge Regression
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Book Synopsis Minimax Linear Regression Estimators with Application to Ridge Regression by : Lawrence Charles Peele
Download or read book Minimax Linear Regression Estimators with Application to Ridge Regression written by Lawrence Charles Peele and published by . This book was released on 1980 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Minimax Ridge Regression by : Lawrence C. Peele
Download or read book Minimax Ridge Regression written by Lawrence C. Peele and published by . This book was released on 1980 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work examined minimax linear estimation in multiple linear regression. The application of minimax estimation to regression led to the development of ridge regression estimators with stochastic ridge parameters. These estimators were seen to be invariant under linear transformation; a property which has not been established for other ridge estimators. These minimax-motivated estimators were examined in several simulation studies. In particular, flaws in other simulation studies of ridge estimators were depicted. Consequently, an improved simulation procedure was used. It was observed from these studies that, contrary to published statements, a ridge estimator can be considerably superior to the ordinary least squares estimator, especially when high pairwise correlations exist among the regression variables. Robustness considerations were used to suggest a requirement that a 'good' generalized ridge regression estimator should satisfy. (Author).
Book Synopsis A Minimax Regression Estimator with Application to Ridge Regression by : Lawrence Charles Peele
Download or read book A Minimax Regression Estimator with Application to Ridge Regression written by Lawrence Charles Peele and published by . This book was released on 1978 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Minimax Ridge Regression Estimation by : George Casella
Download or read book Minimax Ridge Regression Estimation written by George Casella and published by . This book was released on 1977 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Minimax Ridge Regression Estimation by : George Casella
Download or read book Minimax Ridge Regression Estimation written by George Casella and published by . This book was released on 1977 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: The technique of ridge regression has become a popular tool for data analysts faced with a high degree of multicollinearity in their data. By using a ridge estimator, it was hoped that one could both stabilize the estimates (lower the condition number of the design matrix) and improve upon the squared error loss of the least squares estimator. Recently classes of ridge regression estimators have been developed which dominate the usual estimator in risk, and hence are minimax. This paper derives conditions that are necessary and sufficient for minimaxity of a large class of ridge regression estimators. The conditions derived here are very similar to those derived for minimaxity of some Stein-type estimators.
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 Theory of Ridge Regression Estimation with Applications by : A. K. Md. Ehsanes Saleh
Download or read book Theory of Ridge Regression Estimation with Applications written by A. K. Md. Ehsanes Saleh and published by John Wiley & Sons. This book was released on 2019-01-08 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to the systematic analytical results for ridge, LASSO, preliminary test, and Stein-type estimators with applications Theory of Ridge Regression Estimation with Applications offers a comprehensive guide to the theory and methods of estimation. Ridge regression and LASSO are at the center of all penalty estimators in a range of standard models that are used in many applied statistical analyses. Written by noted experts in the field, the book contains a thorough introduction to penalty and shrinkage estimation and explores the role that ridge, LASSO, and logistic regression play in the computer intensive area of neural network and big data analysis. Designed to be accessible, the book presents detailed coverage of the basic terminology related to various models such as the location and simple linear models, normal and rank theory-based ridge, LASSO, preliminary test and Stein-type estimators. The authors also include problem sets to enhance learning. This book is a volume in the Wiley Series in Probability and Statistics series that provides essential and invaluable reading for all statisticians. This important resource: Offers theoretical coverage and computer-intensive applications of the procedures presented Contains solutions and alternate methods for prediction accuracy and selecting model procedures Presents the first book to focus on ridge regression and unifies past research with current methodology Uses R throughout the text and includes a companion website containing convenient data sets Written for graduate students, practitioners, and researchers in various fields of science, Theory of Ridge Regression Estimation with Applications is an authoritative guide to the theory and methodology of statistical estimation.
Book Synopsis Theory of Ridge Regression Estimation with Applications by : A. K. Md. Ehsanes Saleh
Download or read book Theory of Ridge Regression Estimation with Applications written by A. K. Md. Ehsanes Saleh and published by John Wiley & Sons. This book was released on 2019-02-12 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to the systematic analytical results for ridge, LASSO, preliminary test, and Stein-type estimators with applications Theory of Ridge Regression Estimation with Applications offers a comprehensive guide to the theory and methods of estimation. Ridge regression and LASSO are at the center of all penalty estimators in a range of standard models that are used in many applied statistical analyses. Written by noted experts in the field, the book contains a thorough introduction to penalty and shrinkage estimation and explores the role that ridge, LASSO, and logistic regression play in the computer intensive area of neural network and big data analysis. Designed to be accessible, the book presents detailed coverage of the basic terminology related to various models such as the location and simple linear models, normal and rank theory-based ridge, LASSO, preliminary test and Stein-type estimators. The authors also include problem sets to enhance learning. This book is a volume in the Wiley Series in Probability and Statistics series that provides essential and invaluable reading for all statisticians. This important resource: Offers theoretical coverage and computer-intensive applications of the procedures presented Contains solutions and alternate methods for prediction accuracy and selecting model procedures Presents the first book to focus on ridge regression and unifies past research with current methodology Uses R throughout the text and includes a companion website containing convenient data sets Written for graduate students, practitioners, and researchers in various fields of science, Theory of Ridge Regression Estimation with Applications is an authoritative guide to the theory and methodology of statistical estimation.
Book Synopsis Improving Efficiency by Shrinkage by : Marvin Gruber
Download or read book Improving Efficiency by Shrinkage written by Marvin Gruber and published by Routledge. This book was released on 2017-11-01 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offers a treatment of different kinds of James-Stein and ridge regression estimators from a frequentist and Bayesian point of view. The book explains and compares estimators analytically as well as numerically and includes Mathematica and Maple programs used in numerical comparison.;College or university bookshops may order five or more copies at a special student rate, available on request.
Book Synopsis Ridge Regression, Minimax Estimation, and Empirical Bayes Methods by : Ronald Aaron Thisted
Download or read book Ridge Regression, Minimax Estimation, and Empirical Bayes Methods written by Ronald Aaron Thisted and published by . This book was released on 1989 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Scientific and Technical Aerospace Reports by :
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1981 with total page 1370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Book Synopsis V Hotine-Marussi Symposium on Mathematical Geodesy by : Fernando Sansò
Download or read book V Hotine-Marussi Symposium on Mathematical Geodesy written by Fernando Sansò and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Just as in the era of great achievements by scientists such as Newton and Gauss, the mathematical theory of geodesy is continuing the tradition of producing exciting theoretical results, but today the advances are due to the great technological push in the era of satellites for earth observations and large computers for calculations. Every four years a symposium on methodological matters documents this ongoing development in many related underlying areas such as estimation theory, stochastic modelling, inverse problems, and satellite-positioning global-reference systems. This book presents developments in geodesy and related sciences, including applied mathematics, among which are many new results of high intellectual value to help readers stay on top of the latest happenings in the field.
Book Synopsis Numerical Issues in Statistical Computing for the Social Scientist by : Micah Altman
Download or read book Numerical Issues in Statistical Computing for the Social Scientist written by Micah Altman and published by John Wiley & Sons. This book was released on 2004-02-15 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: At last—a social scientist's guide through the pitfalls of modern statistical computing Addressing the current deficiency in the literature on statistical methods as they apply to the social and behavioral sciences, Numerical Issues in Statistical Computing for the Social Scientist seeks to provide readers with a unique practical guidebook to the numerical methods underlying computerized statistical calculations specific to these fields. The authors demonstrate that knowledge of these numerical methods and how they are used in statistical packages is essential for making accurate inferences. With the aid of key contributors from both the social and behavioral sciences, the authors have assembled a rich set of interrelated chapters designed to guide empirical social scientists through the potential minefield of modern statistical computing. Uniquely accessible and abounding in modern-day tools, tricks, and advice, the text successfully bridges the gap between the current level of social science methodology and the more sophisticated technical coverage usually associated with the statistical field. Highlights include: A focus on problems occurring in maximum likelihood estimation Integrated examples of statistical computing (using software packages such as the SAS, Gauss, Splus, R, Stata, LIMDEP, SPSS, WinBUGS, and MATLAB®) A guide to choosing accurate statistical packages Discussions of a multitude of computationally intensive statistical approaches such as ecological inference, Markov chain Monte Carlo, and spatial regression analysis Emphasis on specific numerical problems, statistical procedures, and their applications in the field Replications and re-analysis of published social science research, using innovative numerical methods Key numerical estimation issues along with the means of avoiding common pitfalls A related Web site includes test data for use in demonstrating numerical problems, code for applying the original methods described in the book, and an online bibliography of Web resources for the statistical computation Designed as an independent research tool, a professional reference, or a classroom supplement, the book presents a well-thought-out treatment of a complex and multifaceted field.
Book Synopsis Bayesian Estimation and Experimental Design in Linear Regression Models by : Jürgen Pilz
Download or read book Bayesian Estimation and Experimental Design in Linear Regression Models written by Jürgen Pilz and published by . This book was released on 1991-07-09 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a clear treatment of the design and analysis of linear regression experiments in the presence of prior knowledge about the model parameters. Develops a unified approach to estimation and design; provides a Bayesian alternative to the least squares estimator; and indicates methods for the construction of optimal designs for the Bayes estimator. Material is also applicable to some well-known estimators using prior knowledge that is not available in the form of a prior distribution for the model parameters; such as mixed linear, minimax linear and ridge-type estimators.
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 Mathematical Statistics and Applications by : Marc Moore
Download or read book Mathematical Statistics and Applications written by Marc Moore and published by IMS. This book was released on 2003 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Technical Report by : University of Wisconsin--Madison. Department of Statistics
Download or read book Technical Report written by University of Wisconsin--Madison. Department of Statistics and published by . This book was released on 1972 with total page 774 pages. Available in PDF, EPUB and Kindle. Book excerpt: