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 some advanced topics in the area of linear models.

Klappentext

This is a self-contained companion volume to the authors book "Plane Answers to Complex Questions: The Theory of Linear Models". It provides introductions to 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 (geostatistics). The purpose of this volume is to use the three fundamental ideas of best linear prediction, projections, and Mahalanobis' distance to exploit their properties in examining multivariate, time series and spatial data.
Ronald Christensen is Professor of Statistics at the University of New Mexico, and is recognised internationally as an expert in the theory and application of linear models.

Inhalt

I Multivariate Linear Models.- II Discrimination and Allocation.- III Principal Components and Factor Analysis.- IV Frequency Analysis of Time Series.- V Time Domain Analysis.- VI Linear Models for Spatial Data: Kriging.- References.- Author Index.