Skip to page content
USDA Forest Service

Research & Development Treesearch

Treesearch Home
About Treesearch
Contact Us
Research & Development
Forest Products Lab
International Institute of Tropical Forestry
Pacific Northwest
Pacific Southwest
Rocky Mountain
Southern Research Station
Help - We Participate  Government Made Easy

Global Forest Information Service

US Forest Service
P.O. Box 96090
Washington, D.C.

(202) 205-8333

You are here: Home / Search / Publication Information
Bookmark and Share

Publication Information

View PDF (681 KB bytes)

Title: Estimating parameters for tree basal area growth with a system of equations and seemingly unrelated regressions

Author: Rose, Charles E. Jr.; Lynch, Thomas B.;

Date: 2001

Source: Forest Ecology and Management 148(2001) 51-61

Publication Series: Miscellaneous Publication

Description: A method was developed for estimating parameters in an individual tree basal area growth model using a system of equations based on dbh rank classes. The estimation method developed is a compromise between an individual tree and a stand level basal area growth model that accounts for the correlation between trees within a plot by using seemingly unrelated regression (SUR) to estimate the restricted parameters. Previously, basal area growth has been modeled on either the stand or the individual tree level. Individual tree models have usually disregarded the regression assumption of independent error terms. Violation of the regression independence assumption may lead to serious underestimation of the mean square error (MSE) and standard error(s) of the parameter estimate(s). The SUR parameter estimation technique has been shown to provide a gain in efficiency for parameter estimation when the error terms for a system of equations are correlated. The data are from an ongoing natural even-aged shortleaf pine growth and yield study being conducted by the USDA Forest Service and Oklahoma State University Department of Forestry for the Ouachita and Ozark National Forests. The basal area growth model based on SUR estimation using a system of four equations (Model 2) corresponding to four dbh rank classes within a plot was compared with a basal area growth model (Model 1) using ordinary least squares (OLS) parameter estimation. The calibration, validation, and complete data set results reveal that Model 2 has a better fit index (FI) and MSE, but that Model 1 has a smaller absolute average error. Model 2 accounts for partial tree interdependency within a plot and consequently should more accurately estimate the parameter standard errors.

Keywords: Shortleaf pine, interdependency, seemingly unrelated regression

Publication Notes:

  • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
  • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
  • You may send email to to request a hard copy of this publication. (Please specify exactly which publication you are requesting and your mailing address.)



Rose, Charles E., Jr.; Lynch, Thomas B. 2001. Estimating parameters for tree basal area growth with a system of equations and seemingly unrelated regressions. Forest Ecology and Management 148(2001) 51-61


 [ Get Acrobat ]  Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility

USDA logo which links to the department's national site. Forest Service logo which links to the agency's national site.