Advanced Linear Modeling

Statistical Learning and Dependent Data

Edición de la obra Advanced Linear Modeling

This book introduces several topics related to linear model theory: multivariate linear models, discriminant analysis, principal components, factor analysis, time series in both the frequency and time domains, and spatial data analysis. The second edition adds new material on nonparametric regression, response surface maximization, and longitudinal models. The book provides a unified approach to these disparate subject and serves as a self-contained companion volume to the author's Plane Answers to Complex Questions: The Theory of Linear Models. Ronald Christensen is Professor of Statistics at the University of New Mexico. He is well known for his work on the theory and application of linear models having linear structure. He is the author of numerous technical articles and several books and he is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics. "Advanced Linear Modeling is unique in that a diverse collection of methodologies are all formulated and developed in the framework of linear models. Many topics that often seem obscure or esoteric to graduate students seem much more tangible when cast in the setting of linear models, e.g., Fourier transformations, Kalman filtering, and kriging. Professor Christensen's text effectively shows how a myriad of methodologies can be viewed and developed utilizing the same results that are used to create the foundations for regression and ANOVA modeling. The sections and chapters that have been added to Advanced Linear Modeling are all strong and will serve to enhance what is already an excellent text." (Joseph Cavanaugh, University of Missouri-Columbia) Also Available: Christensen, Ronald. Plane Answers to Complex Questions: The Theory of