Bunge John, Barger Kathryn
Departgment of Statistical Science, Cornell University, Ithaca, NY 14853, USA.
Biom J. 2008 Dec;50(6):971-82. doi: 10.1002/bimj.200810452.
We consider parametric distributions intended to model heterogeneity in population size estimation, especially parametric stochastic abundance models for species richness estimation. We briefly review (conditional) maximum likelihood estimation of the number of species, and summarize the results of fitting 7 candidate models to frequency-count data, from a database of >40000 such instances, mostly arising from microbial ecology. We consider error estimation, goodness-of-fit assessment, data subsetting, and other practical matters. We find that, although the array of candidate models can be improved, finite mixtures of a small number of components (point masses or simple diffuse distributions) represent a promising direction. Finally we consider the connections between parametric models for abundance and incidence data, again noting the usefulness of finite mixture models.
我们考虑用于对种群大小估计中的异质性进行建模的参数分布,特别是用于物种丰富度估计的参数随机丰度模型。我们简要回顾物种数量的(条件)最大似然估计,并总结将7个候选模型拟合到频率计数数据的结果,这些数据来自一个包含超过40000个此类实例的数据库,大多来自微生物生态学。我们考虑误差估计、拟合优度评估、数据子集划分及其他实际问题。我们发现,尽管候选模型的阵列可以改进,但少量成分(点质量或简单扩散分布)的有限混合代表了一个有前景的方向。最后,我们考虑丰度和发生率数据的参数模型之间的联系,再次指出有限混合模型的有用性。