A conspectus on Estimating Function theory and its applicability to recurrent modeling issues in forest biometry.

摘要

Much of forestry data is characterized by a longitudinal or repeated measures structure where multiple observations taken on some units of interest are correlated. Such dependencies are often ignored in favor of an apparently simpler analysis at the cost of invalid inferences. The last decade has brought to light many new statistical techniques that enable one to successfully deal with dependent observations. Although apparently distinct at first, the theory of Estimating Functions provides a natural extension of classical estimation that encompasses many ot these new approaches. This contribution introduces Estimating Function Theory as a principle with potential for unification and presents examples covering a variety of modeling issues to demonstrate its applicability.