Advanced Linear Modeling: Multivariate, Time Series, and Spatial Data; Nonparametric Regression and Response Surface Maximization

✍ Scribed by Ronald Christensen (auth.)

• Publisher: Springer-Verlag New York
• Year: 2001
• Tongue: English
• Leaves: 411
• Series: Springer Texts in Statistics
• Edition: 2
• Category: Library

✦ Synopsis

This is the second edition of Linear Models for Multivariate, Time Series and Spatial Data. It has a new title to indicate that it contains much new material. The primary changes are the addition of two new chapters: one on nonparametric regression and one on response surface maximization. As before, the presentations focus on the linear model aspects of the subject. For example, in the nonparametric regression chapter there is very little about kernal regression estimation but quite a bit about series approxi­ mations, splines, and regression trees, all of which can be viewed as linear modeling. The new edition also includes various smaller changes. Of particular note are a subsection in Chapter 1 on modeling longitudinal (repeated measures) data and a section in Chapter 6 on covariance structures for spatial lattice data. I would like to thank Dale Zimmerman for the suggestion of incor­ porating material on spatial lattices. Another change is that the subject index is now entirely alphabetical.

✦ Table of Contents

Front Matter....Pages i-xiii
Multivariate Linear Models....Pages 1-73
Discrimination and Allocation....Pages 74-111
Principal Components and Factor Analysis....Pages 112-151
Frequency Analysis of Time Series....Pages 152-199
Time Domain Analysis....Pages 200-268
Linear Models for Spatial Data: Kriging....Pages 269-311
Nonparametric Regression....Pages 312-343
Response Surface Maximization....Pages 344-376
Back Matter....Pages 377-399

✦ Subjects

Statistical Theory and Methods