computing error on least square fitting
6 visualizzazioni (ultimi 30 giorni)
Mostra commenti meno recenti
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?
2 Commenti
Risposte (1)
Bruno Luong
il 15 Ago 2020
Can i claim that the residual which is norm of (Ax-b)/b
No make it
norm(A*x-b) / norm(b)
3 Commenti
Bruno Luong
il 15 Ago 2020
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."
Vedere anche
Categorie
Scopri di più su Interpolation in Help Center e File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!