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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
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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