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- W2065703612 abstract "Poisson (3P) sampling is a commonly used method for generating estimates of timber volume. The usual estimator employed is the adjusted estimator, Y hat a . The efficiency of this estimator can be greatly influenced by the presence of outliers. We formalize such a realistic situation for high-value timber estimation for which Y hat a is inefficient. Here, y i approx beta x i for all but a few units in a population for which y i is large and x i very small. This situation can occur when estimating the net volume of high-value standing timber, such as that found in the Pacific Northwest region of the United States. A generalized regression estimator and an approximate Srivastava estimator are not affected by such data points. Simulations on a small population illustrate these ideas." @default.
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- W2065703612 date "1998-05-01" @default.
- W2065703612 modified "2023-10-18" @default.
- W2065703612 title "Outlier-resistant estimators for Poisson sampling: a note" @default.
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- W2065703612 doi "https://doi.org/10.1139/x98-050" @default.
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