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Author : John Bibby
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (778 download)
Download or read book Prediction and Improved Estimation in Linear Models written by John Bibby and published by . This book was released on 1979 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : John Bibby
Publisher :
ISBN 13 :
Total Pages : 188 pages
Book Rating : 4.:/5 (991 download)
Download or read book Predeuction and Improved Estimation in Linear Models written by John Bibby and published by . This book was released on 1977 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : A. Chaturvedi
Publisher :
ISBN 13 : 9780864181619
Total Pages : 11 pages
Book Rating : 4.1/5 (816 download)
Download or read book Improved Estimation of the Linear Regression Model with Autocorrelated Errors written by A. Chaturvedi and published by . This book was released on 1990 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Zahirul Hoque
Publisher :
ISBN 13 :
Total Pages : 344 pages
Book Rating : 4.:/5 (889 download)
Download or read book Improved Estimation for Linear Models Under Different Loss Functions written by Zahirul Hoque and published by . This book was released on 2004 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis investigates improved estimators of the parameters of the linear regression models with normal errors, under sample and non-sample prior information about the value of the parameters. The estimators considered are the unrestricted estimator (UE), restricted estimator (RE), shrinkage preliminary test estimator (SPTE), and shrinkage estimator (SE). The performance of the estimators are investigated with respect to bias, squared error and linex loss. For the analyses of the risk functions of the estimators, analytical, graphical and numerical procedures are adopted.
Author : Alvin C. Rencher
Publisher : John Wiley & Sons
ISBN 13 : 0470192607
Total Pages : 690 pages
Book Rating : 4.4/5 (71 download)
Download or read book Linear Models in Statistics written by Alvin C. Rencher and published by John Wiley & Sons. This book was released on 2008-01-07 with total page 690 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression. Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features: New chapters on Bayesian linear models as well as random and mixed linear models Expanded discussion of two-way models with empty cells Additional sections on the geometry of least squares Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS® code for all numerical examples. Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance.
Author : V. K. Srivastava
Publisher :
ISBN 13 : 9780867461916
Total Pages : 14 pages
Book Rating : 4.4/5 (619 download)
Download or read book On Lindley-like Mean Correction in the Improved Estimation of Linear Regression Models written by V. K. Srivastava and published by . This book was released on 1980 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Truman Orville Lewis
Publisher : Prentice Hall
ISBN 13 :
Total Pages : 216 pages
Book Rating : 4.3/5 (97 download)
Download or read book Estimation in Linear Models written by Truman Orville Lewis and published by Prentice Hall. This book was released on 1971 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Karl-Rudolf Koch
Publisher : Springer Science & Business Media
ISBN 13 : 3662039761
Total Pages : 344 pages
Book Rating : 4.6/5 (62 download)
Download or read book Parameter Estimation and Hypothesis Testing in Linear Models written by Karl-Rudolf Koch and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: A treatment of estimating unknown parameters, testing hypotheses and estimating confidence intervals in linear models. Readers will find here presentations of the Gauss-Markoff model, the analysis of variance, the multivariate model, the model with unknown variance and covariance components and the regression model as well as the mixed model for estimating random parameters. A chapter on the robust estimation of parameters and several examples have been added to this second edition. The necessary theorems of vector and matrix algebra and the probability distributions of test statistics are derived so as to make this book self-contained. Geodesy students as well as those in the natural sciences and engineering will find the emphasis on the geodetic application of statistical models extremely useful.
Author : Timo Teräsvirta
Publisher :
ISBN 13 :
Total Pages : 38 pages
Book Rating : 4.:/5 (634 download)
Download or read book Some Results on Improving the Least Squares Estimation of Linear Models by Mixed Estimation written by Timo Teräsvirta and published by . This book was released on 1981 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : C.Radhakrishna Rao
Publisher : Springer Science & Business Media
ISBN 13 : 1489900241
Total Pages : 360 pages
Book Rating : 4.4/5 (899 download)
Download or read book Linear Models written by C.Radhakrishna Rao and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is based on both authors' several years of experience in teaching linear models at various levels. It gives an up-to-date account of the theory and applications of linear models. The book can be used as a text for courses in statistics at the graduate level and as an accompanying text for courses in other areas. Some of the highlights in this book are as follows. A relatively extensive chapter on matrix theory (Appendix A) provides the necessary tools for proving theorems discussed in the text and offers a selection of classical and modern algebraic results that are useful in research work in econometrics, engineering, and optimization theory. The matrix theory of the last ten years has produced a series of fundamental results about the definiteness of matrices, especially for the differences of matrices, which enable superiority comparisons of two biased estimates to be made for the first time. We have attempted to provide a unified theory of inference from linear models with minimal assumptions. Besides the usual least-squares theory, alternative methods of estimation and testing based on convex loss func tions and general estimating equations are discussed. Special emphasis is given to sensitivity analysis and model selection. A special chapter is devoted to the analysis of categorical data based on logit, loglinear, and logistic regression models. The material covered, theoretical discussion, and its practical applica tions will be useful not only to students but also to researchers and con sultants in statistics.
Author : Jeff Gill
Publisher : SAGE Publications
ISBN 13 : 1506387322
Total Pages : 140 pages
Book Rating : 4.5/5 (63 download)
Download or read book Generalized Linear Models written by Jeff Gill and published by SAGE Publications. This book was released on 2019-05-14 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generalized Linear Models: A Unified Approach provides an introduction to and overview of GLMs, with each chapter carefully laying the groundwork for the next. The Second Edition provides examples using real data from multiple fields in the social sciences such as psychology, education, economics, and political science, including data on voting intentions in the 2016 U.S. Republican presidential primaries. The Second Edition also strengthens material on the exponential family form, including a new discussion on the multinomial distribution; adds more information on how to interpret results and make inferences in the chapter on estimation procedures; and has a new section on extensions to generalized linear models. Software scripts, supporting documentation, data for the examples, and some extended mathematical derivations are available on the authors’ websites as well as through the \texttt{R} package \texttt{GLMpack}. Supporting material (data and code) to replicate the examples in the book can be found in the ′GLMpack′ package on CRAN or on the website&
Author : D. D. Joshi
Publisher : New Age International
ISBN 13 : 9780852265178
Total Pages : 308 pages
Book Rating : 4.2/5 (651 download)
Download or read book Linear Estimation and Design of Experiments written by D. D. Joshi and published by New Age International. This book was released on 1987 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Kent Alan Weigel
Publisher :
ISBN 13 :
Total Pages : 366 pages
Book Rating : 4.:/5 (89 download)
Download or read book Estimation of Heterogeneous Components of Variance in Mixed Linear Models with an Application to Dairy Cattle Breeding written by Kent Alan Weigel and published by . This book was released on 1992 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Andrew L. Rukhin
Publisher :
ISBN 13 :
Total Pages : 11 pages
Book Rating : 4.:/5 (897 download)
Download or read book Improved Estimation in Lognormal Regression Models written by Andrew L. Rukhin and published by . This book was released on 1985 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Brenton R. Clarke
Publisher : John Wiley & Sons
ISBN 13 : 9780470377970
Total Pages : 288 pages
Book Rating : 4.3/5 (779 download)
Download or read book Linear Models written by Brenton R. Clarke and published by John Wiley & Sons. This book was released on 2008-09-19 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: An insightful approach to the analysis of variance in the study of linear models Linear Models explores the theory of linear models and the dynamic relationships that these models have with Analysis of Variance (ANOVA), experimental design, and random and mixed-model effects. This one-of-a-kind book emphasizes an approach that clearly explains the distribution theory of linear models and experimental design starting from basic mathematical concepts in linear algebra. The author begins with a presentation of the classic fixed-effects linear model and goes on to illustrate eight common linear models, along with the value of their use in statistics. From this foundation, subsequent chapters introduce concepts pertaining to the linear model, starting with vector space theory and the theory of least-squares estimation. An outline of the Helmert matrix is also presented, along with a thorough explanation of how the ANOVA is created in both typical two-way and higher layout designs, ultimately revealing the distribution theory. Other important topics covered include: Vector space theory The theory of least squares estimation Gauss-Markov theorem Kronecker products Diagnostic and robust methods for linear models Likelihood approaches to estimation A discussion of Bayesian theory is also included for purposes of comparison and contrast, and numerous illustrative exercises assist the reader with uncovering the nature of the models, using both classic and new data sets. Requiring only a working knowledge of basic probability and statistical inference, Linear Models is a valuable book for courses on linear models at the upper-undergraduate and graduate levels. It is also an excellent reference for practitioners who use linear models to conduct research in the fields of econometrics, psychology, sociology, biology, and agriculture.
Author : Jana Jurečková
Publisher :
ISBN 13 :
Total Pages : 13 pages
Book Rating : 4.:/5 (165 download)
Download or read book Regression Quantiles and Improved L-estimation in Linear Models written by Jana Jurečková and published by . This book was released on 1987 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Wolfgang Härdle
Publisher : Springer Science & Business Media
ISBN 13 : 3642577008
Total Pages : 210 pages
Book Rating : 4.6/5 (425 download)
Download or read book Partially Linear Models written by Wolfgang Härdle and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last ten years, there has been increasing interest and activity in the general area of partially linear regression smoothing in statistics. Many methods and techniques have been proposed and studied. This monograph hopes to bring an up-to-date presentation of the state of the art of partially linear regression techniques. The emphasis is on methodologies rather than on the theory, with a particular focus on applications of partially linear regression techniques to various statistical problems. These problems include least squares regression, asymptotically efficient estimation, bootstrap resampling, censored data analysis, linear measurement error models, nonlinear measurement models, nonlinear and nonparametric time series models.
