多重共线性
毒性
主成分分析
化学
线性回归
回归分析
金属
数学
生物系统
统计
生物
有机化学
作者
Yu Liu,Xiaoli Li,Xuewei Du,Meng Wang,Xin Jing,Hui‐Juan Yan,Yao Wang
标识
DOI:10.1080/10807039.2012.722820
摘要
ABSTRACT The quantitative ion character–activity relationship (QICAR) was used to correlate nine ion characteristics with ion toxicity order numbers (TON) in 19 metals. A multi-parameter regression model was used to simulate the metals toxicity order numbers after minimization of the multicollinearity among the ion characteristics using principal component analysis (PCA). The toxicity order numbers of the metals increased with the positively correlated variables AN, Xm 2r, AN/ΔIP, AW, and Xm , and decreased with the negatively correlated variables ΔE 0, |logK OH|, AR/AW, and σ P . The regression model provided high prediction ability, with Nash-Suttcliffe simulation efficiency coefficients (NSC) of 0.93 for the modeling phase and 0.87 for the testing phases. The model may be successfully employed to predict the stability constants and metal toxicity and used as a first step in the further risk assessment modeling.
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