Wang Ji-Ping
Department of Statistics , Northwestern University , 2006 Sheridan Road, Evanston, Illinois 60208 , U.S.A.
Biometrika. 2010 Sep;97(3):727-740. doi: 10.1093/biomet/asq026. Epub 2010 Jun 22.
We propose a Poisson-compound gamma approach for species richness estimation. Based on the denseness and nesting properties of the gamma mixture, we fix the shape parameter of each gamma component at a unified value, and estimate the mixture using nonparametric maximum likelihood. A least-squares crossvalidation procedure is proposed for the choice of the common shape parameter. The performance of the resulting estimator of N is assessed using numerical studies and genomic data.
我们提出一种用于物种丰富度估计的泊松复合伽马方法。基于伽马混合的密集性和嵌套特性,我们将每个伽马分量的形状参数固定为一个统一值,并使用非参数最大似然法估计该混合。为选择共同形状参数提出了一种最小二乘交叉验证程序。使用数值研究和基因组数据评估所得N估计量的性能。