Estimating the Number of Species in a Stochastic Abundance Model
Article first published online: 21 MAY 2004
Volume 58, Issue 3, pages 531–539, September 2002
How to Cite
Chao, A. and Bunge, J. (2002), Estimating the Number of Species in a Stochastic Abundance Model. Biometrics, 58: 531–539. doi: 10.1111/j.0006-341X.2002.00531.x
- Issue published online: 21 MAY 2004
- Article first published online: 21 MAY 2004
- Received February 2001. Revised February 2002. Accepted March 2002.
- Animal abundance;
- Empirical Bayes;
- Maximum likelihood;
- Sample coverage;
- Species richness
Summary. Consider a stochastic abundance model in which the species arrive in the sample according to independent Poisson processes, where the abundance parameters of the processes follow a gamma distribution. We propose a new estimator of the number of species for this model. The estimator takes the form of the number of duplicated species (i.e., species represented by two or more individuals) divided by an estimated duplication fraction. The duplication fraction is estimated from all frequencies including singleton information. The new estimator is closely related to the sample coverage estimator presented by Chao and Lee (1992, Journal of the American Statistical Association87, 210–217). We illustrate the procedure using the Malayan butterfly data discussed by Fisher, Corbet, and Williams (1943, Journal of Animal Ecology12, 42–58) and a 1989 Christmas Bird Count dataset collected in Florida, U.S.A. Simulation studies show that this estimator compares well with maximum likelihood estimators (i.e., empirical Bayes estimators from the Bayesian viewpoint) for which an iterative numerical procedure is needed and may be infeasible.