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Uncertainty estimation of the self-thinning process by Maximum-Entropy PrincipleAuthor(s): Shoufan Fang; George Z. Gertner
Source: In: Hansen, Mark; Burk, Tom, eds. Integrated tools for natural resources inventories in the 21st century. Gen. Tech. Rep. NC-212. St. Paul, MN: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station. 199-206.
Publication Series: General Technical Report (GTR)
Station: North Central Research Station
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DescriptionWhen available information is scarce, the Maximum-Entropy Principle can estimate the distributions of parameters. In our case study, we estimated the distributions of the parameters of the forest self-thinning process based on literature information, and we derived the conditional distribution functions and estimated the 95 percent confidence interval (CI) of the self-thinning process for several tree species. The 95 percent CI indicated that the slope parameter of the so-called self-thinning law can be considered a random variable with a mean value of -3/2.
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CitationFang, Shoufan; Gertner, George Z. 2000. Uncertainty estimation of the self-thinning process by Maximum-Entropy Principle. In: Hansen, Mark; Burk, Tom, eds. Integrated tools for natural resources inventories in the 21st century. Gen. Tech. Rep. NC-212. St. Paul, MN: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station. 199-206.
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