MS&E
Take Home Midterm (2015)

# Take Home Midterm (2015) - MS&E 226 Small Data Take-Home...

• Test Prep
• 5
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PROBLEM 1. In this problem we will investigate some of the properties of weighted least squares . If you haven’t already done so, you should review the notes for Discussion Section 3. Suppose we are given n observations ( Y i , X i ) , together with positive weights w i , i = 1 , . . . , n . In weighted least squares, we find the coefficients ˆ γ that minimize the following objective function: n X i =1 w i ( Y i - ˆ γ 0 - ˆ γ 1 X i 1 - · · · - ˆ γ p X ip ) 2 . (1) We refer to the resulting coefficients ˆ γ as the weighted least squares (WLS) solution; we refer to w = ( w 1 , . . . , w n ) as the vector of weights .
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• Fall '15
• JOHARI
• Regression Analysis, Yi, Ordinary least squares, error variance, weighted least squares

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