100BHWV - STAT 100B HWV Due Friday Problem 1: Suppose we...

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: STAT 100B HWV Due Friday Problem 1: Suppose we want to fit the linear regression model yi = xi1 β1 + xi2 β2 + ... + xip βp + i for i = 1, 2, ..., n by the least squares principle, i.e., we estimate β = (β1 , β2 , ..., βp )T by minimizing n n i=1 R(β ) = i=1 [yi − (xi1 β1 + xi2 β2 + ... + xip βp )]2 = (yi − xT β )2 , i where xi = (xi1 , xi2 , ..., xip )T . ˆ (1) Calculate the least squares estimate β . (2) Compare the result in (1) with the result we obtained before for p = 1. (3) Compare the result in (1) with the result we obtained before for simple linear regression with the intercept. 1 ...
View Full Document

Ask a homework question - tutors are online