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Multivariate regression model for partitioning tree volume of white oak into round-product classesAuthor(s): Daniel A. Yaussy; David L. Sonderman
Source: Research Note NE-317. Broomall, PA: U.S. Department of Agriculture, Forest Service, Northeastern Forest Experiment Station. 4p.
Publication Series: Research Note (RN)
Station: Northeastern Research Station
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DescriptionDescribes the development of multivariate equations that predict the expected cubic volume of four round-product classes from independent variables composed of individual tree-quality characteristics. Although the model has limited application at this time, it does demonstrate the feasibility of partitioning total tree cubic volume into round-product classes based on tree-quality characteristics.
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CitationYaussy, Daniel A.; Sonderman, David L. 1984. Multivariate regression model for partitioning tree volume of white oak into round-product classes. Research Note NE-317. Broomall, PA: U.S. Department of Agriculture, Forest Service, Northeastern Forest Experiment Station. 4p.
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