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.
- bentisk fauna
Jørgensen, B., Demétrio, C. G. B., Kristensen, E., Banta, G. T., Petersen, H. C., & Delfosse, M. (2011). Bias-corrected Pearson estimating functions for Taylor’s power law applied to benthic macrofauna data. Statistics & Probability Letters, 81(7), 749-758. https://doi.org/10.1016/j.spl.2011.01.005