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This book would serve as a suitable text for a course in linear models. The Kshirsagar book is specifically designed for a one-semester course, and one would have to move quickly to cover every- thing in that time. This book covers such standard topics as full- and non-full-rank models, the Gauss—Mar- kov theorem, distribution of estimators, distribution of quadratic forms, idempotent matrices, estimability, generalized inverses, confidence re- gions, tests Of linear hypotheses, orthogonal polynomials, one-way and two-way classifications, and analysis of covariance.
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Book Details
Table of Contents
-Linear models;
-The general linear model;
-Interval estimates and tests of hypotheses;
-Multiple regression;
-Analysis of variance;
-Comparison of individual means;
-Analysis of variance (multi-way classification);
-Analysis of variance - two-way classification, with unequal number of observations per cell;
-Analysis of covariance;
-Method of generalized least squares;
-Missing plots technique and miscellaneous topics;
-Variance components analysis.
Edition Notes
Bibliography: p. 411-416.
Includes indexes.
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February 28, 2020 | Edited by MARC Bot | remove fake subjects |
April 9, 2019 | Edited by Kaustubh Chakraborty | Added contents and description |
June 1, 2018 | Edited by Kaustubh Chakraborty | Added new cover |
December 5, 2010 | Edited by Open Library Bot | Added subjects from MARC records. |
December 10, 2009 | Created by WorkBot | add works page |