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

Bent Jørgensen, Clarice G.B. Demétrio, Erik Kristensen, Gary Thomas Banta, Hans Christian Petersen, Matthieu Delfosse

Research output: Contribution to journalJournal articleResearchpeer-review

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.
Original languageEnglish
JournalStatistics & Probability Letters
Volume81
Issue number7
Pages (from-to)749-758
Number of pages10
ISSN0167-7152
DOIs
Publication statusPublished - 2011

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