A New Approach to the Estimation of Variance Components PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download A New Approach to the Estimation of Variance Components PDF full book. Access full book title A New Approach to the Estimation of Variance Components by David Worth Smith. Download full books in PDF and EPUB format.
Author: David Worth Smith
Publisher:
ISBN:
Category :
Languages : en
Pages : 206
Get Book Here
Book Description
Author: David Worth Smith
Publisher:
ISBN:
Category :
Languages : en
Pages : 206
Get Book Here
Book Description
Author: Shayle R. Searle
Publisher: John Wiley & Sons
ISBN: 0470317698
Category : Mathematics
Languages : en
Pages : 537
Get Book Here
Book Description
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.
Author: Ronald R. Hocking
Publisher:
ISBN:
Category : Analysis of covariance
Languages : en
Pages : 27
Get Book Here
Book Description
Closed form expressions are developed for the estimators of functions of the variance components in balanced, mixed, linear models. These estimators are averages of sample covariances (variances) which offer diagnostic information on the data and the model. The cause of negative estimates may be revealed. Examples illustrate the basic concepts.
Author: Poduri S.R.S. Rao
Publisher: CRC Press
ISBN: 9780412728600
Category : Mathematics
Languages : en
Pages : 232
Get Book Here
Book Description
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.
Author: James D. Malley
Publisher: Springer Science & Business Media
ISBN: 1461575540
Category : Mathematics
Languages : en
Pages : 157
Get Book Here
Book Description
Author: Robert Donald Anderson
Publisher:
ISBN:
Category : Analysis of variance
Languages : en
Pages : 308
Get Book Here
Book Description
Author: Hardeo Sahai
Publisher: Springer Science & Business Media
ISBN: 0817644253
Category : Mathematics
Languages : en
Pages : 493
Get Book Here
Book Description
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.
Author: Cheng-Hsuan Yuan
Publisher:
ISBN:
Category :
Languages : en
Pages : 122
Get Book Here
Book Description
Author: David A. Harville
Publisher:
ISBN:
Category : Analysis of variance
Languages : en
Pages : 105
Get Book Here
Book Description
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).
Author: Calyampudi Radhakrishna Rao
Publisher: North Holland
ISBN:
Category : Business & Economics
Languages : en
Pages : 392
Get Book Here
Book Description
Matrix algebra; Asymptotic distribution of quadratic statistics; Variance and covariance components models; Identifiability and estimability; minimum norm quadratic estimation; Pulling of information for estimation; Uniform optimality of minqe's; Computation of minqe's for variance-convariance components models; Integrated minqe and mile; Asymptotic properties estimators; Minimum variance quadratic estimation; Aplications to selection problems.
