Linear Regression Analysis (eBook)

GEORGE A. F. SEBER, PhD, is Professor Emeritus of Statistics at the University of Auckland, New Zealand. ALAN J. LEE, PhD, is the Chairman of the Department of Statistics at the University of Auckland.

Preface.

Vectors of Random Variables.

Multivariate Normal Distribution.

Linear Regression: Estimation and Distribution Theory.

Hypothesis Testing.

Confidence Intervals and Regions.

Straight-Line Regression.

Polynomial Regression.

Analysis of Variance.

Departures from Underlying Assumptions.

Departures from Assumptions: Diagnosis and Remedies.

Computational Algorithms for Fitting a Regression.

Prediction and Model Selection.

Appendix A. Some Matrix Algebra.

Appendix B. Orthogonal Projections.

Appendix C. Tables.

Outline Solutions to Selected Exercises.

References.

Index.

"With excellent motivating and presenting style, this book is
suitable for a beginning graduate level regression course."
(Journal of Statistical Computation and Simulation, July
2005)

"...revises and expands the standard text, providing extensive
coverage of state-of-the-art theory..." (Zentralblatt Math,
Vol. 1029, 2004)

"...largely rewritten...very useful for self-study...an
excellent choice for a course in linear models and researchers who
are interested in recent literature in the fields..."
(Technometrics, Vol. 45, No. 4, November 2003)

"...rewritten to reflect current thinking, such as the
major advances in computing during the past 25 years."
(Quarterly of Applied Mathematics, Vol. LXI, No. 3,
September 2003)