Advertisement

Fitting Linear Hierarchical Models

  • Andrew P. Robinson
  • Jeff D. Hamann
Part of the Use R book series (USE R)

Abstract

We now shift to the analysis of hierarchical data using mixed-effects models. These models are a natural match for many problems that occur commonly in natural resources. A number of the tools that we discuss in this chapter are extensively documented in Pinheiro and Bates (2000), and our goal is to complement that resource, not replace it. Although we focus on mixed-effects models, other solutions are possible. For example, stochastic differential equations have also seen success in forestry (García, 1983), and generalized estimating equations may also be useful.

Keywords

Habitat Type Hierarchical Model National Forest Random Slope True Relationship 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Andrew P. Robinson
    • 1
  • Jeff D. Hamann
    • 2
  1. 1.Dept. Mathematics and StatisticsUniversity of MelbourneParkvilleAustralia
  2. 2.Forest Informatics, Inc.Corvallis OregonUSA

Personalised recommendations