This book will serve as a reference book for graduate students and researchers in statistics. Written by a leading researcher in the field, it discusses advanced topics in the area of linear models.

presents a collection of methodologies formulated and developed in the framework of linear models

Autorentext
Ronald Christensen is a Professor of Statistics at the University of New Mexico, Fellow of the American Statistical Association (ASA) and the Institute of Mathematical Statistics, former Chair of the ASA Section on Bayesian Statistical Science and former Editor of The American Statistician. His book publications include Plane Answers to Complex Questions (Springer 2011), Log-Linear Models and Logistic Regression (Springer 1997), Analysis of Variance, Design, and Regression (1996, 2016), and Bayesian Ideas and Data Analysis (2010, with Johnson, Branscum and Hanson).

Inhalt
1 Multivariate Linear Models.- 2 Discrimination and Allocation.- 3 Principal Components and Factor Analysis.- 4 Frequency Analysis of Time Series.- 5 Time Domain Analysis.- 6 Linear Models for Spatial Data: Kriging.- 7 Nonparametric Regression.- 8 Response Surface Maximization.- References.- Author Index.