Download or read book Restricted Maximum Likelihood Estimation of Variance Components written by Terrance Patrick Callanan and published by . This book was released on 1985 with total page 774 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Restricted Maximum Likelihood Estimation for Two Variance Components written by Justus Seely and published by . This book was released on 1972 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Variance Components written by Shayle R. Searle and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. ". . .Variance Components is an excellent book. It is organized and well written, and provides many references to a variety of topics. I recommend it to anyone with interest in linear models." —Journal of the American Statistical Association "This book provides a broad coverage of methods for estimating variance components which appeal to students and research workers . . . The authors make an outstanding contribution to teaching and research in the field of variance component estimation." —Mathematical Reviews "The authors have done an excellent job in collecting materials on a broad range of topics. Readers will indeed gain from using this book . . . I must say that the authors have done a commendable job in their scholarly presentation." —Technometrics This book focuses on summarizing the variability of statistical data known as the analysis of variance table. Penned in a readable style, it provides an up-to-date treatment of research in the area. The book begins with the history of analysis of variance and continues with discussions of balanced data, analysis of variance for unbalanced data, predictions of random variables, hierarchical models and Bayesian estimation, binary and discrete data, and the dispersion mean model.

Download or read book On Maximum Likelihood and Restricted Maximum Likelihood Approaches to Estimation of Variance Components written by Michael A. Burgess and published by . This book was released on 1981 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Restricted Maximum Likelihood Estimation of Variance Components for Multiple Traits with Missing Observations and an Application to Beef Cattle written by Dorian John Garrick and published by . This book was released on 1988 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computation of Restricted Maximum Likelihood Estimates of Variance Components written by Hiroshi Takahashi and published by . This book was released on 1993 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Pooling Maximum Likelihood Estimates of Variance Components Obtained from Subsets of Unbalanced Data written by James Scott Babb and published by . This book was released on 1986 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems written by David A. Harville and published by . This book was released on 1975 with total page 105 pages. Available in PDF, EPUB and Kindle. Book excerpt: Several recent developments promise to increase greatly the popularity of maximum likelihood (ML) as a technique for estimating variance components. Patterson and Thompson (Biometrika, Vol. 58, December 1971, pp. 545-554) proposed a restricted maximum likelihood (REML) approach which takes into account the loss in degrees of freedom resulting from estimating fixed effects. Miller (Technical Report No. 12, Department of Statistics, Stanford University, 1973) developed a realistic asymptotic theory for ML estimators of variance components. There are many iterative algorithms that can be considered for computing ML or REML estimates of variance components. Some were developed specifically for the variance component problem and related problems. Others are general nonlinear optimization procedures. The computations on each iteration of these algorithms are those associated with computing estimates of fixed and random effects for given values of the variance components. MINQUE's of variance components can be computed from one iteration of the REML version of Anderson's (Annals of Statistics, Vol. 1, January 1973, pp. 135-141) iterative procedures. (Author).

Download or read book Maximum Likelihood Estimation of Variance Components written by Alice Marion Richardson and published by . This book was released on 1991 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Estimating Variance Components in Hierarchical Structures Using Minque and Restricted Maximum Likelihood written by F. G. Giesbrecht and published by . This book was released on 1978 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Comparison of Restricted Maximum Likelihood and Method of Moments Variance Estimation for Small sample Split plot Experiments written by Xuan Xu and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Researchers may choose to perform an experiment using a split-plot design over more simple designs such as a completely randomized design or a randomized complete block design in order to conserve scarce resources. A split-plot becomes attractive when some treatment factors are more costly to apply to the experimental units or when it is difficult to change one factor from level to level. In such a case it may be more efficient to apply these costly treatments to a small set of larger experimental units (i.e. whole plots) and then apply the less costly treatments to more numerous smaller experimental units (i.e. subplots) nested within the larger ones. Because the subplot and whole-plot experimental units each have a corresponding variance component, the analysis of a split-plot study is more complicated. Making the split-plot analysis even more challenging, cost considerations may also lead to relatively small sample sizes for the whole-plot treatments. An unintended consequence is that some variance components in the split-plot design's model may be poorly estimated which in turn may have an unanticipated effect on the type I error rates for tests of the fixed effects. As a motivating example, alfalfa yield data from a field study with a split-plot design with four randomized complete blocks at the whole-plot level serves as the basis for a simulation study to estimate the type I error rates of three fixed effects (whole-plot main effects, subplot main effects and whole-plot by subplot interaction). Several other scenarios where the number of blocks and the relative magnitudes of the variance components are varied are also explored. For each scenario, 10,000 data sets were randomly generated assuming normally distributed errors. Two linear mixed models were fit to each data set using the MIXED procedure in SAS; one method estimates the variance components via restricted maximum likelihood (REML) and the other by the method of moments (MoM) based on the type III sums of squares. The REML models yielded inconsistent type I error rates for some tests of fixed effects compared to the MoM models but improved as the number of blocks increased. MoM models tended to hold their nominal type I error rates to within expected Monte Carlo error.

Download or read book Maximum Likelihood Estimation of a Set of Covariance Matrices Under Lowner Order Restrictions with Applications to Multivariate Variance Components written by James A. Calvin and published by . This book was released on 1988 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Variance Components written by Poduri S.R.S. Rao and published by CRC Press. This book was released on 1997-06-01 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Variance Components Estimation deals with the evaluation of the variation between observable data or classes of data. This is an up-to-date, comprehensive work that is both theoretical and applied. Topics include ML and REML methods of estimation; Steepest-Acent, Newton-Raphson, scoring, and EM algorithms; MINQUE and MIVQUE, confidence intervals for variance components and their ratios; Bayesian approaches and hierarchical models; mixed models for longitudinal data; repeated measures and multivariate observations; as well as non-linear and generalized linear models with random effects.

Download or read book Numerical Methods for Unconstrained Optimization and Nonlinear Equations written by J. E. Dennis, Jr. and published by SIAM. This book was released on 1996-12-01 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has become the standard for a complete, state-of-the-art description of the methods for unconstrained optimization and systems of nonlinear equations. Originally published in 1983, it provides information needed to understand both the theory and the practice of these methods and provides pseudocode for the problems. The algorithms covered are all based on Newton's method or "quasi-Newton" methods, and the heart of the book is the material on computational methods for multidimensional unconstrained optimization and nonlinear equation problems. The republication of this book by SIAM is driven by a continuing demand for specific and sound advice on how to solve real problems. The level of presentation is consistent throughout, with a good mix of examples and theory, making it a valuable text at both the graduate and undergraduate level. It has been praised as excellent for courses with approximately the same name as the book title and would also be useful as a supplemental text for a nonlinear programming or a numerical analysis course. Many exercises are provided to illustrate and develop the ideas in the text. A large appendix provides a mechanism for class projects and a reference for readers who want the details of the algorithms. Practitioners may use this book for self-study and reference. For complete understanding, readers should have a background in calculus and linear algebra. The book does contain background material in multivariable calculus and numerical linear algebra.

Download or read book Properties of Variance Component Estimators Obtained by Restricted Maximum Likelihood and by MINQUE written by Songsiri Sriburi and published by . This book was released on 1978 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Analysis of Variance for Random Models Volume 2 Unbalanced Data written by Hardeo Sahai and published by Springer Science & Business Media. This book was released on 2007-07-03 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systematic treatment of the commonly employed crossed and nested classification models used in analysis of variance designs with a detailed and thorough discussion of certain random effects models not commonly found in texts at the introductory or intermediate level. It also includes numerical examples to analyze data from a wide variety of disciplines as well as any worked examples containing computer outputs from standard software packages such as SAS, SPSS, and BMDP for each numerical example.

Download or read book Near Uniformly Minimum Variance Quadratic Unbiased Estimation of Variance Components in Mixed Effects Model written by Li Guo and published by . This book was released on 2013 with total page 117 pages. Available in PDF, EPUB and Kindle. Book excerpt: Several methods are available in literature for estimating the variance components in mixed effects models. In this thesis we consider the general mixed effects model without making any distributional assumptions. The quadratic unbiased estimators are considered for estimating the variance components. The uniformly minimum variance quadratic unbiased estimation (UMVQUE) of variance components is investigated for the data obtained from both balanced and unbalanced designs. In spite of its attractive properties, the UMVQUE may not always be possible. When the UMVQUE is not possible, we propose two alternative methods for estimating the variance components. We first introduce a method of near uniformly minimum variance quadratic unbiased estimation (NUMVQUE) for an unbalanced incomplete block design. When the UMVQUE of variance components is not possible for a design with replicated blocks but it is possible with a single replication of blocks, we propose another method of average uniformly minimum variance quadratic unbiased estimation (AUMVQUE). The maximum likelihood estimation (MLE) and restricted maximum likelihood estimation (REMLE) are likelihood based procedures and therefore require the distributional assumptions to estimate the variance components. We present a simulation study to evaluate the performance of our proposed estimation methods and compare them with MLE and REMLE.