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Bias-corrected Pearson estimating functions for Taylor’s power law applied to benthic macrofauna data. (English) Zbl 1217.62204
Summary: Estimation of L. R. Taylor’s [Nature 189, 732–735 (1961)] power law for species abundance data may be performed by linear regression of the log empirical variances on the log means, but this method suffers from a problem of bias for sparse data. We show that the bias may be reduced by using a bias-corrected Pearson estimating function. Furthermore, we investigate a more general regression model allowing for site-specific covariates. This method may be efficiently implemented using a Newton scoring algorithm, with standard errors calculated from the inverse Godambe information matrix. The method is applied to a set of biomass data for benthic macrofauna from two Danish estuaries.

62P12 Applications of statistics to environmental and related topics
62H12 Estimation in multivariate analysis
65C60 Computational problems in statistics (MSC2010)
Full Text: DOI
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