Advanced Linear Models: Theory and Applications

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Overview

This work details the statistical inference of linear models including parameter estimation, hypothesis testing, confidence intervals, and prediction. The authors discuss the application of statistical theories and methodologies to various linear models such as the linear regression model, the analysis of variance model, the analysis of covariance model, and the variance components model.

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Editorial Reviews

Booknews
Introducing the concept of linear models through real examples, the authors discuss the application of statistical theories and methods to various linear models, examine the relationship among linear models, and provide an overview of matrix theory and multivariate distributions. Exercises are provided at the end of each chapter. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

Table of Contents

Part 1 Preliminary results: matrix theory; multivariate normal and related distributions. Part 2 Statistical inferences; introduction to linear models; parameter estimation; statistical inferences. Part 3 Applications: linear regression models; analysis of variance models; analysis of covariance models; variance components models.

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