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Evaluating the Performance of Weight Functions with No Constraints on Function Types

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In weighted linear regression, the variance of the error terms is estimated by a weight function. Methods for testing two competing weight functions exist provided one of the functions is a special case of another weight function. A method based on an index of fit and bootstrap sampling, which allows two unrelated weight functions to be compared, is given. This method is tested on six artificial data sets of different sizes. For data sets of size 100 and larger, the proposed method could detect the difference between the weight functions ²f1(xi) = ²e1xi and ²f2(xi) = ²xi2 at the 95% level. For. Sci. 40(4):787-793.

Keywords: Weighted linear regression; bootstrap sample; index of fit

Document Type: Journal Article

Affiliations: Multiresource Inventory Techniques, Rocky Mountain Forest and Range Experiment Station, 240 W. Prospect, USDA Forest Service, Fort Collins, Colorado 80526-2098

Publication date: November 1, 1994

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