- #1

fog37

- 1,382

- 95

- TL;DR Summary
- Understanding if linear regression can be done with other variants of least squares

Hello,

Simple linear regression aims at finding the slope and intercept of the best-fit line to for a pair of ##X## and ##Y## variables.

In general, the optimal intercept and slope are found using OLS. However, I learned that "O" means ordinary and there are other types of least square computations...

Question: is it possible to apply those variants of LS to the linear regression model, i.e., can we find the best-fit line parameters using something other than OLS (for example, I think there is "robust" LS, etc.)?

thank you!

Simple linear regression aims at finding the slope and intercept of the best-fit line to for a pair of ##X## and ##Y## variables.

In general, the optimal intercept and slope are found using OLS. However, I learned that "O" means ordinary and there are other types of least square computations...

Question: is it possible to apply those variants of LS to the linear regression model, i.e., can we find the best-fit line parameters using something other than OLS (for example, I think there is "robust" LS, etc.)?

thank you!