针对现有总体最小二乘抗差算法存在的缺陷,应用中位数法确定模型参数的初值,提出了对模型的观测向量与系数矩阵中的观测元素进行分类定权的思想,避免了中误差估计偏差与随机模型误差对等价权函数抗差性的影响。基于中位数法建立总体最小二乘抗差迭代算法,并结合算例对算法进行验证。结果表明,在相同观测样本条件下,本文提出的算法拟合的精度高于传统算法拟合的精度。
Because the present algorithms of total least squares for robust estimation have disadvantages, solution for computation primary model parameters based on median method is proposed. And to get over the influence that estimation error of random model and error of mean square has, computation weight matrix of observation vector and coefficient matrix separately are proposed. Iterative algorithm of robust total least squares is established based on median method, and to prove the proposed solution to be feasible, an instance is cited. The numerical results of the instance clearly demonstrate that the presented solution is more accurate than the traditional method for line fitting.
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