0.091751098632811117646SRSOTHERPublished to Web1Publication2Informally Refereed (Peer-Reviewed)53Miscellaneous Publication<![CDATA[Modeling Multiplicative Error Variance: An Example Predicting Tree Diameter from Stump Dimensions in Baldcypress]]> 1993-1In the context of forest modeling, it is often reasonable to assume a multiplicative heteroscedastic error structure to the data. Under such circumstances ordinary least squares no longer provides minimum variance estimates of the model parameters. Through study of the error structure, a suitable error variance model can be specified and its parameters estimated. This error model is used to construct a covariance matrix which in turn is used to form an estimated generalized least squares estimator of the forest model parameters. The theory is illustrated with data on baldcypress (Taxodium distichum [L.] Rich.). A multiple linear regression equation is developed for predicting diameter at 3 m from solid-wood stump diameter (i.e., diameter inside the fluting) and stump height. By modeling the error structure, standard errors on three of the four coefficients from the tree diameter-stump dimensions regression were reduced by 13 to 50%. The effect on prediction confidence intervals is graphically illustrated.https://www.srs.fs.usda.gov/pubs/ja/ja_parresol002.pdf224 KBhttps://www.fs.usda.gov/treesearch/pubs/124812480Forest Science, Vol. 39, No. 4, pp. 670-6790T0Parresol, Bernard R.; 22-AUG-2006 10:59:48AY27Ecology, Ecosystems, & Environment36Wildlife (or Fauna)76Forest ProductsParresol, Bernard R.SRSHQbparresol2530001Parresol, Bernard R.PNW2600bparresol2530001This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.

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