Theory and computation of restricted linear models
Least squares inverses and complementary matrices are used to develop a comprehensive theory of estimation for a restricted linear model. Testable hypotheses as defined in \textit{S. R. Searle} [Linear models. (1971; Zbl 0218.62071)] are extended to involve nonestimable functions. An explicit expression for the sum of squares of deviation from the null hypothesis under the general setup with restrictions and the corresponding number of degrees of freedom are obtained for implementation on computers.
scientific article; zbMATH DE number 4084778