| Advanced Linear Modeling: Statistical Learning and Dependent Data 2019 Edition Contributor(s): Christensen, Ronald (Author) |
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ISBN: 3030291669 ISBN-13: 9783030291662 Publisher: Springer OUR PRICE: $85.49 Product Type: Paperback - Other Formats Published: January 2021 |
| Additional Information |
| BISAC Categories: - Mathematics | Probability & Statistics - General - Mathematics | Counting & Numeration - Mathematics | Numerical Analysis |
| Dewey: 518 |
| Physical Information: 1.28" H x 6.14" W x 9.21" (1.93 lbs) 608 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |
