Advanced Linear Modeling
Multivariate, Time Series, and Spatial Data; Nonparametric Regression and Response Surface Maximization
Seiten
2001
|
Second Edition 2001
Springer-Verlag New York Inc.
978-0-387-95296-3 (ISBN)
Springer-Verlag New York Inc.
978-0-387-95296-3 (ISBN)
This is the second edition of Linear Models for Multivariate, Time Series and Spatial Data. 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.
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.
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.
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.
| Reihe/Serie | Springer Texts in Statistics |
|---|---|
| Zusatzinfo | XIV, 398 p. |
| Verlagsort | New York, NY |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Analysis |
| Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
| Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik | |
| Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
| ISBN-10 | 0-387-95296-9 / 0387952969 |
| ISBN-13 | 978-0-387-95296-3 / 9780387952963 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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