Download or read book Selecting Procedures for Optimal Subset of Regression Variables written by Shanti S. Gupta and published by . This book was released on 1982 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently a number of methods have been developed for selecting the best or at least a good subset of variables in regression analysis. For various reasons, we may be interested in including only a subset, say, of size r

Download or read book Selection Procedures for Optimal Subsets of Regression Variables written by Shanti S. Gupta and published by . This book was released on 1983 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper deals with selection of an optimal subset of variables in a linear regression model. Based on the criterion of expected residual mean squares, we reject inferior regression models. The derivation of the rule is different from those of the earlier papers in that here we use the simultaneous tests of a family of hypotheses. Using real data, an example is provided to illustrate the application of the proposed procedure. (Author).

Download or read book Subset Selection in Regression written by Alan Miller and published by CRC Press. This book was released on 2002-04-15 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originally published in 1990, the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade. Thoroughly revised to reflect progress in theory, methods, and computing power, the second edition promises to continue that tradition. The author ha

Download or read book Subset Selection Procedures for Regression Analysis written by Shanti S. Gupta and published by . This book was released on 1975 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past decade a number of methods have been developed for selecting the 'best' or at least a 'good' subset of variables in regression analysis. For various reasons, one may be interested in selecting a random size subset excluding all inferior independent variables. The authors are interested in deriving a selection procedure to the goal. Some results on the efficiency of the procedure are also discussed.

Download or read book Forecasting principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.

Download or read book Optimal Subset Selection written by David Boyce and published by Springer Science & Business Media. This book was released on 2013-03-08 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the course of one's research, the expediency of meeting contractual and other externally imposed deadlines too often seems to take priority over what may be more significant research findings in the longer run. Such is the case with this volume which, despite our best intentions, has been put aside time and again since 1971 in favor of what seemed to be more urgent matters. Despite this delay, to our knowledge the principal research results and documentation presented here have not been superseded by other publications. The background of this endeavor may be of some historical interest, especially to those who agree that research is not a straightforward, mechanistic process whose outcome or even direction is known in ad vance. In the process of this brief recounting, we would like to express our gratitude to those individuals and organizations who facilitated and supported our efforts. We were introduced to the Beale, Kendall and Mann algorithm, the source of all our efforts, quite by chance. Professor Britton Harris suggested to me in April 1967 that I might like to attend a CEIR half-day seminar on optimal regression being given by Professor M. G. Kendall in Washington. D. C. I agreed that the topic seemed interesting and went along. Had it not been for Harris' suggestion and financial support, this work almost certainly would have never begun.

Download or read book Mathematical Algorithms for Linear Regression written by Helmuth Späth and published by Academic Press. This book was released on 2014-05-10 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Algorithms for Linear Regression discusses numerous fitting principles related to discrete linear approximations, corresponding numerical methods, and FORTRAN 77 subroutines. The book explains linear Lp regression, method of the lease squares, the Gaussian elimination method, the modified Gram-Schmidt method, the method of least absolute deviations, and the method of least maximum absolute deviation. The investigator can determine which observations can be classified as outliers (those with large errors) and which are not by using the fitting principle. The text describes the elimination of outliers and the selection of variables if too many or all of them are given by values. The clusterwise linear regression accounts if only a few of the relevant variables have been collected or are collectible, assuming that their number is small in relation to the number of observations. The book also examines linear Lp regression with nonnegative parameters, the Kuhn-Tucker conditions, the Householder transformations, and the branch-and-bound method. The text points out the method of least squares is mainly used for models with nonlinear parameters or for orthogonal distances. The book can serve and benefit mathematicians, students, and professor of calculus, statistics, or advanced mathematics.

Download or read book Design of Experiments written by Santner and published by CRC Press. This book was released on 1984-07-30 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple comparisons; Selection and ranking; Estimation and testing.

Download or read book SAS System for Regression written by Rudolf Freund and published by John Wiley & Sons. This book was released on 2000-12-29 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: SAS® System for Regression Learn to perform a wide variety of regression analyses using SAS® software with this example-driven revised favorite from SAS Publishing. With this Third Edition you will learn the basics of performing regression analyses using a wide variety of models including nonlinear models. Other topics covered include performing linear regression analyses using PROC REG diagnosing and providing remedies for data problems, including outliers and multicollinearity. Examples feature numerous SAS procedures including REG, PLOT, GPLOT, NLIN, RSREG, AUTOREG, PRINCOMP, and others. A helpful discussion of theory is supplied where necessary. Some knowledge of both regression and the SAS System are assumed. New for this edition The Third Edition includes revisions, updated material, and new material. You’ll find new information on using SAS/INSIGHT® software regression with a binary response with emphasis on PROC LOGISTIC nonparametric regression (smoothing) using moving averages and PROC LOESS. Additionally, updated material throughout the book includes high-resolution PROC REG graphics output, using the OUTEST option to produce a data set, and using PROC SCORE to predict another data set.

Download or read book A Subset Selection Procedure for Regression Variables written by George P McCabe (Jr) and published by . This book was released on 1973 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt: Given a regression model with p independent variables, several methods are available for selecting a subset of size t

Download or read book Regression Analysis written by Rudolf J. Freund and published by Elsevier. This book was released on 2006-05-30 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regression Analysis provides complete coverage of the classical methods of statistical analysis. It is designed to give students an understanding of the purpose of statistical analyses, to allow the student to determine, at least to some degree, the correct type of statistical analyses to be performed in a given situation, and have some appreciation of what constitutes good experimental design. Examples and exercises contain real data and graphical illustration for ease of interpretation Outputs from SAS 7, SPSS 7, Excel, and Minitab are used for illustration, but any major statisticalsoftware package will work equally well

Download or read book On Selecting an Optimal Subset of Regression Variables written by Shanti S. Gupta and published by . This book was released on 1977 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past decade a number of methods have been developed for selecting the best or at least a good subset of variables in regression analysis. For various reasons, there may be interest in including only a subset say, of size r

Download or read book Statistics II for Dummies written by Deborah J. Rumsey and published by John Wiley & Sons. This book was released on 2009-08-19 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ideal supplement and study guide for students preparing for advanced statistics Packed with fresh and practical examples appropriate for a range of degree-seeking students, Statistics II For Dummies helps any reader succeed in an upper-level statistics course. It picks up with data analysis where Statistics For Dummies left off, featuring new and updated examples, real-world applications, and test-taking strategies for success. This easy-to-understand guide covers such key topics as sorting and testing models, using regression to make predictions, performing variance analysis (ANOVA), drawing test conclusions with chi-squares, and making comparisons with the Rank Sum Test.

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1984 with total page 688 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.

Download or read book Applied Logistic Regression written by David W. Hosmer, Jr. and published by John Wiley & Sons. This book was released on 2004-10-28 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the reviews of the First Edition. "An interesting, useful, and well-written book on logistic regression models . . . Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references." —Choice "Well written, clearly organized, and comprehensive . . . the authors carefully walk the reader through the estimation of interpretation of coefficients from a wide variety of logistic regression models . . . their careful explication of the quantitative re-expression of coefficients from these various models is excellent." —Contemporary Sociology "An extremely well-written book that will certainly prove an invaluable acquisition to the practicing statistician who finds other literature on analysis of discrete data hard to follow or heavily theoretical." —The Statistician In this revised and updated edition of their popular book, David Hosmer and Stanley Lemeshow continue to provide an amazingly accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. Hosmer and Lemeshow extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by a wealth of real-world examples-with extensive data sets available over the Internet.

Download or read book Introduction to Linear Regression Analysis written by Douglas C. Montgomery and published by John Wiley & Sons. This book was released on 2021-02-24 with total page 706 pages. Available in PDF, EPUB and Kindle. Book excerpt: INTRODUCTION TO LINEAR REGRESSION ANALYSIS A comprehensive and current introduction to the fundamentals of regression analysis Introduction to Linear Regression Analysis, 6th Edition is the most comprehensive, fulsome, and current examination of the foundations of linear regression analysis. Fully updated in this new sixth edition, the distinguished authors have included new material on generalized regression techniques and new examples to help the reader understand retain the concepts taught in the book. The new edition focuses on four key areas of improvement over the fifth edition: New exercises and data sets New material on generalized regression techniques The inclusion of JMP software in key areas Carefully condensing the text where possible Introduction to Linear Regression Analysis skillfully blends theory and application in both the conventional and less common uses of regression analysis in today’s cutting-edge scientific research. The text equips readers to understand the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences.

Download or read book Advances in Multivariate Statistical Analysis written by Arjun K. Gupta and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The death of Professor K.C. Sreedharan Pillai on June 5, 1985 was a heavy loss to many statisticians all around the world. This volume is dedicated to his memory in recog nition of his many contributions in multivariate statis tical analysis. It brings together eminent statisticians Working in multivariate analysis from around the world. The research and expository papers cover a cross-section of recent developments in the field. This volume is especially useful to researchers and to those who want to keep abreast of the latest directions in multivariate statistical analysis. I am grateful to the authors from so many different countries and research institutions who contributed to this volume. I wish to express my appreciation to all those who have reviewed the papers. The list of people include Professors T.C. Chang, So-Hsiang Chou, Dipak K. Dey, Peter Hall, Yu-Sheng Hsu, J.D. Knoke, W.J. Krzanowski, Edsel Pena, Bimal K. Sinha, Dennis L. Young, Drs. K. Krishnamoorthy, D.K. Nagar, and Messrs. Alphonse Amey, Chi-Chin Chao and Samuel Ofori-Nyarko. I wish to thank Professors Shanti S. Gupta and James 0. Berger for their keen interest and encouragement. Thanks are also due to Cynthia Patterson for her help and Reidel Publishing Com~any for their cooperation in bringing this volume out.