Improve least squares solution
2 vues (au cours des 30 derniers jours)
Afficher commentaires plus anciens
I have to solve a least squares problem in which y=Ax, where y is a vector whose entries are experimental data, A is my model and x is the solution I need to find so as to weight properly my model to fit the experiments. The following figure shows in blue the experimental data (y) and in red Ax.
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/192031/image.jpeg)
How could I obtain a better fit for my data in MATLAB? Is there any specific function for this? (I am not sure how to use the nonlinear least squares method, I simply solved the normal equations with the backslash \ )
3 commentaires
dpb
le 17 Juil 2018
You're apparently trying to use an extremely high-order polynomial to fit a very difficult problem.
The solution is undoubtedly to find a more suitable model.
The backslash operator is quite sophisticated despite its deceptively simple syntax; internally it does quite sophisticated stuff and generally outperforms any other technique for badly condition systems.
Réponses (0)
Voir également
Catégories
En savoir plus sur Least Squares dans Help Center et File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!