Bias-corrected Pearson estimating functions for Taylor's power law applied to benthic macrofauna data

Bent Jørgensen (1) , Clarice G.B. Demétrio (2) , Erik Kristensen (3) , Gary T. Banta (4) , Hans Christian Petersen (1) , Matthieu Delefosse (3)

1 Department of Mathematics and Computer Science
2 Department of Exact Sciences
3 SDU - University of Southern Denmark
4 Department of Environmental

Estimation of Taylor's 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.

Mots clés: Physical Sciences

Domaines: Bio-informatique [q-bio.QM]; Bio-Informatique, Biologie Systémique [q-bio.QM]

Bent Jørgensen, Clarice G.B. Demétrio, Erik Kristensen, Gary T. Banta, Hans Christian Petersen, et al.. Bias-corrected Pearson estimating functions for Taylor's power law applied to benthic macrofauna data. Statistics and Probability Letters, 2011, ⟨10.1016/j.spl.2011.01.005⟩. ⟨hal-00746104⟩