Foundations of Multiple Regression and Analysis of Variance

1. Auflage 2025
ISBN: 978-1-032-98152-9
Verlag: Chapman and Hall/CRC

Buch, Englisch, 266 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 567 g

This book provides a rigorous development of the foundations of linear models for multiple regression and Analysis of Variance (ANOVA), based on orthogonal projections and relations among linear subspaces. It is appropriate for the linear models course required in most statistics Ph.D. programs.

Zielgruppe

Postgraduate and Professional Reference

Autoren/Hrsg.

Lamotte, Lynn Roy

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik

Inhaltsverzeichnis

1 Introduction 2 MLR & ANOVA Illustrations I Basics 3 Matrices and Vectors  4 Linear Subspaces  5 Orthogonal Projection  6 The Gram-Schmidt Construction  7 Further Results as Exercises  II Inference 8 LMs, LS, and the GM Theorem  9 Estimability 10 Inference on the Mean  11 Restricted Linear Models  12 Special Hypotheses  13 On Methods of Model-Building III ANOVA Models: Linear Models for Effects of Categorical Factors 14 Introduction  15 ANOVA Effects  16 Models with ANOVA Effects 17 Type III  18 ANOVA Exercises and Projects  19 Yates’s MWSM  20 Proportional Subclass Numbers  21 ANOVA Comments Appendices Appendix A Proofs and Solutions to Selected Exercises  Appendix B Sampling Distributions  Bibliography Index

Über Autor(innen)

Lynn Roy LaMotte is Professor Emeritus in the Biostatistics Program, School of Public Health, LSU Health–New Orleans. Elected Fellow of the American Statistical Association, 1985, for “important, innovative, seminal, and diverse contributions to the theory and application of linear statistical models,” he is author of about 100 articles in diverse academic journals, cited more than 2,000 times, nearly 500 since 2020.