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.
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.