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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.

MSC:
62P12 Applications of statistics to environmental and related topics
62H12 Estimation in multivariate analysis
65C60 Computational problems in statistics (MSC2010)
Software:
Tweedie
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