Solving least squares problems

  title={Solving least squares problems},
  author={C. Lawson and R. Hanson},
  booktitle={Classics in applied mathematics},
Since the lm function provides a lot of features it is rather complicated. So we are going to instead use the function lsfit as a model. It computes only the coefficient estimates and the residuals. Now would be a good time to read the help file for lsfit. Note that lsfit supports the fitting of multiple least squares models and weighted least squares. Our function will not, hence we can omit the arguments wt, weights and yname. Also, changing tolerances is a little advanced so we will trust… Expand
3,790 Citations

Topics from this paper

Least Squares Auto-Tuning
  • 7
  • PDF
On direct elimination methods for solving the equality constrained least squares problem
The method of (not so) ordinary least squares: what can go wrong and how to fix them
A Projection Method for Least Squares Problems with a Quadratic Equality Constraint
  • 22
Better Subset Regression Using the
Exactly initialized recursive least squares
  • Jie Zhou, Y. Zhu, X. Li, Zhisheng You
  • Mathematics, Medicine
  • Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228)
  • 2001
  • 5
Sign-constrained least squares estimation for high-dimensional regression
  • 63
  • PDF