Puntanen S., Styan G.P.H., Isotalo J. Formulas Useful for Linear Regression Analysis and Related Matrix Theory: It's Only Formulas But We Like Them

Springer, 2013. — 137 p. — ISBN: 9783642329302, e-ISBN: 9783642329319 — (Series: SpringerBriefs in Statistics).
This is an unusual book because it contains a great deal of formulas. Hence it is a blend of monograph, textbook, and handbook.
It is intended for students and researchers who need quick access to useful formulas appearing in the linear regression model and related matrix theory. This is not a regular textbook - this is supporting material for courses given in linear statistical models. Such courses are extremely common at universities with quantitative statistical analysis programs.
Keywords » best linear unbiased estimation - linear model - linear regression - matrix theory - projector.Formulas Useful for Linear Regression Analysis and Related Matrix Theory.
The model matrix & other preliminaries.
Fitted values and residuals.
Regression coefficients.
Decompositions of sums of squares.
Distributions.
Best linear predictor.
Testing hypotheses.
Regression diagnostics.
BLUE: Some preliminaries.
Best linear unbiased estimator.
The relative efficiency of OLSE.
Linear sufficiency and admissibility.
Best linear unbiased predictor.
Mixed model.
Multivariate linear model.
Principal components, discriminant analysis, factor analysis.
Canonical correlations.
Column space properties and rank rules.
Inverse of a matrix.
Generalized inverses.
Projectors.
Eigenvalues.
Singular value decomposition & other matrix decompositions.
Lowner ordering.
nequalities.
Kronecker product, some matrix derivatives.