生态位因子分析方法是一种基于生态位概念的多变量分析方法,然而该方法在计算相关性时所使用的协方差只考虑了变量间的线性关系,而大部分变量间的关系是非线性相关的.互信息可用于衡量两个变量间相互依赖的强弱程度,且不局限于线性相关.本文提出基于互信息的生态位因子分析方法,采用互信息计算变量间的相关性,分析斑头雁在青海湖地区的栖息地选择情况以及栖息地适宜性,与传统生态位因子分析方法相比,所提出的方法改变了特化向量,提高了栖息地适宜性预测的准确率.
Ecological-Niche Factor Analysis(ENFA) is a multivariable approach based on the concept of the ecological niche. But when computing the relevance between variables by covariance, it only handles linear dependencies, while most is nonlinear interaction. Mutual information measures the interdependence between variables and it's not limited to linear relations. ENFA based on mutual information(MIENFA) is presented which uses mutual information as the relevance. Through studies of Bar-headed Goose in Qinghai Lake, compared with the traditional ENFA, the proposed approach changes the specialization vector and improves the accurate rate of habitat suitability prediction.