Variance Components Estimation
Subtitle: Mixed Models, Methodologies and Applications (Monographs on Statistics & Applied Probability)
By: by Poduri S.R.S. Rao.
Edition: First edition
Series: Monographs on statistics and applied probability, 78.
Publisher: Chapman & Hall/CRC
Published: June 1, 1997
Place of publication: London, UK
Language: eng
Format: Hardcover
Number of pages: 230
ISBN-13: 9780412728600
Copyright date: ©1997
First sentence: Variance components are the different sources contributing to the variation in an observation.
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.
Notes: Includes bibliographical references (pages 173-193) and indexes.