computing error on least square fitting

1 次查看（过去 30 天）
Sumera Yamin
Sumera Yamin 2020-8-13
编辑： Sumera Yamin 2020-8-16
Hi, i slove a system of equations (Ax-b) using least square method. i get an output with x like [2.5; -11.1; 0.8; 0.5]. the status flag is zero with system converging at iteration 2 and relative residual of 0.019. I want to calculate the error on my fit i--e with which certainity my solution is accurate. Can i claim that the residual which is norm of (Ax-b)/b means that my fit has an error of 1.9%?if not how can i calculate error on my fit?

请先登录，再回答此问题。

回答（1 个）

Bruno Luong
Bruno Luong 2020-8-15
Can i claim that the residual which is norm of (Ax-b)/b
No make it
norm(A*x-b) / norm(b)
  3 个评论
显示 1更早的评论
Bruno Luong
Bruno Luong 2020-8-15
If you want an unnambiguous mathematical statement, just state exactly what mean:
norm(A*x-b) / norm(b) is approximatively 0.019
At your place I would say in the speaking language
The fit has a relative l2-norm residual of 1.9%.
The fit error usually designates the difference between the true and the estimated fit (parameters). So to me you shouldn't use the word "error."
Sumera Yamin
Sumera Yamin 2020-8-15
Sorry i am not getting hang of it. " The fit has a relative l2-norm residual of 1.9%." how would i interpret this statement in terms of accuracy of my solution.
"The fit error usually designates the difference between the true and the estimated fit (parameters)" how can i calculate fit error?

请先登录，再进行评论。

类别

在 Help Center 和 File Exchange 中查找有关 Probability Distributions 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by