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

Author

Listed:
  • Jørgensen, Bent
  • Demétrio, Clarice G.B.
  • Kristensen, Erik
  • Banta, Gary T.
  • Petersen, Hans Christian
  • Delefosse, Matthieu

Abstract

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.

Suggested Citation

  • Jørgensen, Bent & Demétrio, Clarice G.B. & Kristensen, Erik & Banta, Gary T. & Petersen, Hans Christian & Delefosse, Matthieu, 2011. "Bias-corrected Pearson estimating functions for Taylor's power law applied to benthic macrofauna data," Statistics & Probability Letters, Elsevier, vol. 81(7), pages 749-758, July.
    • Handle: RePEc:eee:stapro:v:81:y:2011:i:7:p:749-758
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    References listed on IDEAS

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    1. Haihong Li & Bruce G. Lindsay & Richard P. Waterman, 2003. "Efficiency of projected score methods in rectangular array asymptotics," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 191-208, February.
    2. Bent Jørgensen & Sven Jesper Knudsen, 2004. "Parameter Orthogonality and Bias Adjustment for Estimating Functions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 31(1), pages 93-114, March.
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