Michaelis-Menten模型近似回归方法的改进  

Improvement About Method of Approximate Regression in Modle of Michaclis-Menten

作　　者：姚莉[1] 王勤[2] 张世强[1] 

机构地区：[1]重庆医科大学数理教研室,重庆400016 [2]西南师范大学计算机与信息科学学院,重庆400715

出　　处：《西南师范大学学报（自然科学版）》2002年第1期26-29,共4页Journal of Southwest China Normal University(Natural Science Edition)

摘　　要：对在生命科学中广泛应用的Michaelis Menten模型 ,人们通常采用Y =1/y代换 ,然后用最小二乘法求出近似回归模型 .该近似回归模型对原始数据的测量误差较敏感 ,严重时会使模型无实用价值 .通过对该现象的分析 ,找出了导致模型失败的原因 。Model of Michaelis Menten was widely applied in life science. We usually make the subtitution Y=1/y , then, use Least Square Method for solving the model of approximate reagression. The model is very sensitive to the error of measurement of initial data. When the state is serious, it should not have any practical values. By analyzing the phenomenon, the authors found out the reasons of failure, and provided a simple, useful method to solve the former problem.

关 键 词：Michaelis-Menten模型 非线性函数 近似回归模型 残差 最小二乘法 近拟回归方程 

分 类 号：O212.1[理学—概率论与数理统计]