最小一乘估计的最优化方法与灵敏度分析

最小一乘估计是人们最常用的回归方法之一,因为其回归结果受奇异点的影响较小,从而受到人们越来越多的关注,鉴于此方法所构造模型的非光滑性,进而增加了其计算的难度.针对不同观测结果及需求,将最小一乘模型转化成不同的线性规划模型,利用相应的求解软件进行求解.并针对不同情况对结果进行了灵敏度分析,从而找出了影响结果的因素.

Least Absolue Estimation Optimiaztion and it's Sensitivity Analysis

Least squares estimation is a kind of commonly regression method.In this method,the regression results are less affected by the singualarity,so it is concerned more and more by many scholars.Given the smoothness of the constructed model in the way. Thus there are some difficulties in he calculation.According the different observations and demand.Articles least absolute deviation model transforms to different linear model and Solutes it,then conductes a sensitivity analysis,thus finds the factors of fluencing the results.