Contemporary Statistical Models for the Plant and Soil SciencesDespite its many origins in agronomic problems, statistics today is often unrecognizable in this context. Numerous recent methodological approaches and advances originated in other subject-matter areas and agronomists frequently find it difficult to see their immediate relation to questions that their disciplines raise. On the other hand, statisticians often fail to recognize the riches of challenging data analytical problems contemporary plant and soil science provides. |
Contents
1 | |
Chapter 2 Data Structures | 35 |
Chapter 3 Linear Algebra Tools | 59 |
Least Squares and Some Alternatives | 85 |
Chapter 5 Nonlinear Models | 183 |
Chapter 6 Generalized Linear Models | 299 |
Chapter 7 Linear Mixed Models for Clustered Data | 403 |
Chapter 8 Nonlinear Models for Clustered Data | 525 |
Chapter 9 Statistical Models for Spatial Data | 561 |
703 | |
721 | |
725 | |
Back cover | 739 |
Other editions - View all
Contemporary Statistical Models for the Plant and Soil Sciences Oliver Schabenberger,Francis J. Pierce No preview available - 2001 |
Contemporary Statistical Models for the Plant and Soil Sciences Oliver Schabenberger No preview available - 2002 |