Linear Models, Statistical Information, and Statistical Inference.
Final rept. 1 Jan 68-30 Dec 70,
IOWA STATE UNIV AMES
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Research on linear models and statistical information and inference is described. Chapter I deals with parametric augmentations and error structures under which certain simple least squares and analysis of variance procedures are also best. Chapter 2 develops efficient methods for the analysis of variance of balanced complete experimental data on a digital computer. Chapter 3 considers linear spaces and unbiased estimation with application to the mixed linear model. Chapter 4 deals with questions in statistical information theory and related measures of information. Chapter 5 presents a general discussion by O. Kempthorne on implications of theories of inference to applied statistics. Author
- Statistics and Probability