Biometry for Forestry and Environmental Data with Examples in R focuses on statistical methods that are widely applicable in forestry and environmental sciences, but it also includes material that is of wider interest.
Biometry for Forestry and Environmental Data with Examples in R focuses on statistical methods that are widely applicable in forestry and environmental sciences, but it also includes material that is of wider interest.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Lauri Mehtätalo (PhD in 2004 in Forest Sciences, University of Joensuu) is professor in applied statistics at the University of Eastern Finland and adjunct professor in forest biometrics at the University of Helsinki. Juha Lappi (PhD in 1986 in Statistics, University of Helsinki) did his research career as a senior scientist at Finnish Forest Research Institute. His thesis and other publications thereafter were one of the very first applications of mixed-effects models in forest sciences.
Inhaltsangabe
1. Introduction 2. Random Variables 3. Statistical Modeling, Estimation and Prediction 4. Linear Model 5. Linear Mixed-effects Models 6. More about Linear Mixed-eff ects Models 7. Nonlinear (Mixed-eff ects) Models 8. Generalized Linear (Mixed-E ffects) Models 9. Multivariate (Mixed-Eff ects) Models 10. Additional topics on regression 11. Modeling Tree Size 12. Taper Curves 13. Measurement Errors 14. Forest and Environmental Experiments