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Empirical Bayes James Stein And Ridge Regression Type Estimators For Linear Models
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Book Synopsis Empirical Bayes, James Stein and Ridge Regression Type Estimators for Linear Models by : Marvin Haskel Jack Gruber
Download or read book Empirical Bayes, James Stein and Ridge Regression Type Estimators for Linear Models written by Marvin Haskel Jack Gruber and published by . This book was released on 1979 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 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.
Book Synopsis Theory of Preliminary Test and Stein-Type Estimation with Applications by : A. K. Md. Ehsanes Saleh
Download or read book Theory of Preliminary Test and Stein-Type Estimation with Applications written by A. K. Md. Ehsanes Saleh and published by John Wiley & Sons. This book was released on 2006-04-28 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theory of Preliminary Test and Stein-Type Estimation with Applications provides a com-prehensive account of the theory and methods of estimation in a variety of standard models used in applied statistical inference. It is an in-depth introduction to the estimation theory for graduate students, practitioners, and researchers in various fields, such as statistics, engineering, social sciences, and medical sciences. Coverage of the material is designed as a first step in improving the estimates before applying full Bayesian methodology, while problems at the end of each chapter enlarge the scope of the applications. This book contains clear and detailed coverage of basic terminology related to various topics, including: * Simple linear model; ANOVA; parallelism model; multiple regression model with non-stochastic and stochastic constraints; regression with autocorrelated errors; ridge regression; and multivariate and discrete data models * Normal, non-normal, and nonparametric theory of estimation * Bayes and empirical Bayes methods * R-estimation and U-statistics * Confidence set estimation
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 Ridge Regression, Minimax Estimation, and Empirical Bayes Methods by : R. A. Thisted
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:
Book Synopsis Empirical Bayes Estimation by : Harold Macolm Hudson
Download or read book Empirical Bayes Estimation written by Harold Macolm Hudson and published by . This book was released on 1974 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 380 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 A Connection Between Ridge Regression Estimators and the James-Stein Estimator by : H. M. Hudson
Download or read book A Connection Between Ridge Regression Estimators and the James-Stein Estimator written by H. M. Hudson and published by . This book was released on 1975 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Use of Empirical Bayes Estimators in a Linear Regression Model by : Bennie Allen Clemmer
Download or read book Use of Empirical Bayes Estimators in a Linear Regression Model written by Bennie Allen Clemmer and published by . This book was released on 1967 with total page 212 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 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 Dissertation Abstracts International by :
Download or read book Dissertation Abstracts International written by and published by . This book was released on 1986 with total page 734 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Class of James-Stein Regression Estimators: Some Relations to Ridge Regression by : P. O. Anderson
Download or read book A Class of James-Stein Regression Estimators: Some Relations to Ridge Regression written by P. O. Anderson and published by . This book was released on 1977 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :American Statistical Association. Section on Physical and Engineering Sciences Publisher : ISBN 13 : Total Pages :804 pages Book Rating :4.3/5 (91 download)
Book Synopsis Proceedings of the Section on Physical and Engineering Sciences by : American Statistical Association. Section on Physical and Engineering Sciences
Download or read book Proceedings of the Section on Physical and Engineering Sciences written by American Statistical Association. Section on Physical and Engineering Sciences and published by . This book was released on 1992 with total page 804 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Statistical Implications of Pre-test and Stein-rule Estimators in Econometrics by : George G. Judge
Download or read book The Statistical Implications of Pre-test and Stein-rule Estimators in Econometrics written by George G. Judge and published by North-Holland. This book was released on 1978 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Computer Age Statistical Inference, Student Edition by : Bradley Efron
Download or read book Computer Age Statistical Inference, Student Edition written by Bradley Efron and published by Cambridge University Press. This book was released on 2021-06-17 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and influence. 'Data science' and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? How does it all fit together? Now in paperback and fortified with exercises, this book delivers a concentrated course in modern statistical thinking. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov Chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. Each chapter ends with class-tested exercises, and the book concludes with speculation on the future direction of statistics and data science.
Book Synopsis Rank-Based Methods for Shrinkage and Selection by : A. K. Md. Ehsanes Saleh
Download or read book Rank-Based Methods for Shrinkage and Selection written by A. K. Md. Ehsanes Saleh and published by John Wiley & Sons. This book was released on 2022-04-12 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rank-Based Methods for Shrinkage and Selection A practical and hands-on guide to the theory and methodology of statistical estimation based on rank Robust statistics is an important field in contemporary mathematics and applied statistical methods. Rank-Based Methods for Shrinkage and Selection: With Application to Machine Learning describes techniques to produce higher quality data analysis in shrinkage and subset selection to obtain parsimonious models with outlier-free prediction. This book is intended for statisticians, economists, biostatisticians, data scientists and graduate students. Rank-Based Methods for Shrinkage and Selection elaborates on rank-based theory and application in machine learning to robustify the least squares methodology. It also includes: Development of rank theory and application of shrinkage and selection Methodology for robust data science using penalized rank estimators Theory and methods of penalized rank dispersion for ridge, LASSO and Enet Topics include Liu regression, high-dimension, and AR(p) Novel rank-based logistic regression and neural networks Problem sets include R code to demonstrate its use in machine learning
