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Linear Models - A Mean Model Approach (Hardcover): William R. Moser Linear Models - A Mean Model Approach (Hardcover)
William R. Moser; Series edited by Zbynek Sidak, David Aldous, Pranab K. Sen
R2,842 Discovery Miles 28 420 Ships in 12 - 17 working days

Linear models, normally presented in a highly theoretical and mathematical style, are brought down to earth in this comprehensive textbook. Linear Models examines the subject from a mean model perspective, defining simple and easy-to-learn rules for building mean models, regression models, mean vectors, covariance matrices and sums of squares matrices for balanced and unbalanced data sets. The author includes both applied and theoretical discussions of the multivariate normal distribution, quadratic forms, maximum likelihood estimation, less than full rank models, and general mixed models. The mean model is used to bring all of these topics together in a coherent presentation of linear model theory.
Key Features
* Provides a versatile format for investigating linear model theory, using the mean model
* Uses examples that are familiar to the student:
* design of experiments, analysis of variance, regression, and normal distribution theory
* Includes a review of relevant linear algebra concepts
* Contains fully worked examples which follow the theorem/proof presentation

Theory of Rank Tests (Hardcover, 2nd edition): Zbynek Sidak, Pranab K. Sen, Jaroslav Hajek Theory of Rank Tests (Hardcover, 2nd edition)
Zbynek Sidak, Pranab K. Sen, Jaroslav Hajek
R2,388 Discovery Miles 23 880 Ships in 12 - 17 working days

The first edition of Theory of Rank Tests (1967) has been the precursor to a unified and theoretically motivated treatise of the basic theory of tests based on ranks of the sample observations. For more than 25 years, it helped raise a generation of statisticians in cultivating their theoretical research in this fertile area, as well as in using these tools in their application oriented research. The present edition not only aims to revive this classical text by updating the findings but also by incorporating several other important areas which were either not properly developed before 1965 or have gone through an evolutionary development during the past 30 years. This edition therefore aims to fulfill the needs of academic as well as professional statisticians who want to pursue nonparametrics in their academic projects, consultation, and applied research works.
Key Features
* Asymptotic Methods
* Nonparametrics
* Convergence of Probability Measures
* Statistical Inference

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