[PDF] Multicollinearity And Ridge Regression eBook

Author : Hyoshin Kim
Publisher : Infinite Study
Page : 15 pages
File Size : 31,80 MB
Release :
Category : Mathematics
ISBN :

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This paper proposes an a-level estimation algorithm for ridge fuzzy regression modeling, addressing the multicollinearity phenomenon in the fuzzy linear regression setting.

Author : M. Pushpalatha
Publisher : LAP Lambert Academic Publishing
Page : 216 pages
File Size : 34,43 MB
Release : 2013
Category :
ISBN : 9783659389764

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This book proposes the various types of new Ridge regression estimators to deal with the problem of multicollinearity in multiple linear regression analysis.An Ordinary ridge regression estimators and an orthonormal( ridge regression estimators have been derived by selecting the values for ridge parameter based on studentized residuals.A partitioned linear regression model has been specified and the ridge regression estimator has been developed by using Internally studentized residual sum of squares.besides these, an Adaptive General Ridge regression estimator's and a new combined restricted ridge regression estimators have been proposed along with iterative procedures for the solutions of elements of ridge parameters matrix

Author : David G. Kleinbaum
Publisher : Duxbury
Page : 906 pages
File Size : 33,85 MB
Release : 2008
Category : Multivariate analysis
ISBN : 9780495384984

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This bestseller will help you learn regression-analysis methods that you can apply to real-life problems. It highlights the role of the computer in contemporary statistics with numerous printouts and exercises that you can solve using the computer. The authors continue to emphasize model development, the intuitive logic and assumptions that underlie the techniques covered, the purposes, advantages, and disadvantages of the techniques, and valid interpretations of those techniques.

Author : Dr.M. Chandrasekhar Reddy & Dr.P. Balasubramanyam
Publisher : KY Publications
Page : 150 pages
File Size : 45,33 MB
Release : 2021-09-01
Category : Business & Economics
ISBN : 8194807549

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There are several textbooks are available in literature in Econometrics, but we thought it is really beneficial to students and researchers to have a special textbook on multicollinearity problem in the general linear model. The topic of multicollinearity has gained high importance in recent times as the data getting generated is increased enormously. Because of this data exploration, many variables are representing the same amount of information which leads to the problem of multicollinearity. In the current textbook, the authors tried to explore the topic of multicollinearity along with the basic definitions and key tests available to detect multicollinearity. For all practical application purposes, we included a chapter on empirical analysis that will show how the model goes improved through dealing with the problem of multicollinearity. This book acts as a textbook, reference manual for all students who are studying econometrics at their graduate and post-graduate levels and also for research scholars. The design of contents is structured in such a way that users find it easy to understand and implement the same in their research works.

Author : Peter Bühlmann
Publisher : Springer Science & Business Media
Page : 568 pages
File Size : 35,29 MB
Release : 2011-06-08
Category : Mathematics
ISBN : 364220192X

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Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, including the Lasso and versions of it for various models, boosting methods, undirected graphical modeling, and procedures controlling false positive selections. A special characteristic of the book is that it contains comprehensive mathematical theory on high-dimensional statistics combined with methodology, algorithms and illustrations with real data examples. This in-depth approach highlights the methods’ great potential and practical applicability in a variety of settings. As such, it is a valuable resource for researchers, graduate students and experts in statistics, applied mathematics and computer science.

Author : A. K. Md. Ehsanes Saleh
Publisher : John Wiley & Sons
Page : 408 pages
File Size : 40,62 MB
Release : 2019-01-08
Category : Mathematics
ISBN : 1118644506

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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.

Author : Marvin Gruber
Publisher : Routledge
Page : 648 pages
File Size : 43,44 MB
Release : 2017-11-01
Category : Mathematics
ISBN : 1351439162

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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.