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:
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.
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).
Download or read book Ridge Regression Minimax Estimation and Empirical Bayes Methods written by R. A. Thisted and published by . This book was released on 1976 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 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.
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 1976 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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:
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:
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.
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 664 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.
Download or read book acceptability and Component Risk in Multiple Regression Estimation written by Jon M. Maatta and published by . This book was released on 1983 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Ridge Regression written by Matthew K. MacGue and published by . This book was released on 1981 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Ridge Regression and Its Effect on High Leverage Points in the Data written by Carolyn Helen Lichtenstein and published by . This book was released on 1981 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Minimax Estimation in Regression and Random Censorship Models written by Eduard N. Belitser and published by . This book was released on 2000 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Some New Results on Ridge Regression Estimation written by Karl Lin and published by . This book was released on 1979 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we consider various interpretations of the ordinary ridge regression estimator with a given shrinkage factor k, and report the results of an extensive Monte Carlo of several ridge regression estimators involving sample-based rules for selecting k. A major distinguishing feature of the study is the use of a general loss structure, the p-norm, in the evaluation process. Other factors taken into consideration include different degree of ill-conditioning of data, different number of explanatory variables, and different shape and non-centrality of the regression coefficients. The main results are: (i) With minor exceptions, all the ridge regression estimators considered yield a smaller average loss regardless of the loss function used. (ii) The reduction in the average loss of the ridge regression estimators increases when the degree ill-conditioning of data increases. The reduction reaches a substantial level when the degree of ill-conditioning is only moderate. (iii) On the basis of our experiment it is possible to make a recomendation concerning the rule of k.
Download or read book Ridge Regression written by Matthew Kerry Macgue and published by . This book was released on 1981 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Minimax Estimation of Nonparametric Regression Through White Noise Problem written by Yuhai Wu and published by . This book was released on 1997 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt:
