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Mathematics - Probability Theory and Stochastic Processes | Advanced Linear Modeling - Multivariate, Time Series, and Spatial Data; Nonparametric Regression

Advanced Linear Modeling

Multivariate, Time Series, and Spatial Data; Nonparametric Regression and Response Surface Maximization

Christensen, Ronald

2nd ed. 2001, XIV, 398 p.

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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.

Content Level » Graduate

Keywords » ANOVA - Excel - Factor analysis - STATISTICA - Time series - data analysis - mathematical statistics

Related subjects » Computational Science & Engineering - Probability Theory and Stochastic Processes - Statistical Theory and Methods

Table of contents 

Multivariate Linear Models * Discrimination and Allocation * Principal Components and Factor Analysis * Frequency Analysis of Time Series * Time Domain Analysis * Linear Models for Spatial Data: Kriging * Nonparametric Regression * Response Surface Maximization

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