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Unformatted text preview: Answer Sketch for The Elements of Statistical Learning (second edition) Yao-Liang Yu University of Alberta [email protected] March 11, 2009 Abstract This partial solution collection to the book The Elements of Statistical Learning (second edition) is a by-product of my own reading. However, one should NEVER expect the solutions in this collection to be (completely) correct or appropriate or exhaustive (tailored by my own taste). I tried my best when solving these exercises but I cannot give any guarantee (and I am not responsible for any consequence). Mind your own risk if you would like to refer to this collection. Whenever you are sure that there is a mistake in this collection or you have a better solution, please feel free to send me an email and I will be more than happy to revise as much as I can. Chapter 3 Linear Regression Ex. 3.3b (Gauss-Markov Theorem) A linear unbiased estimator can be written as: ˜ β = Ay , and the least square estimator is ˆ β = ( X T X )- 1 X T y = X † y . For unbiasedness, we have E ˜ β = A E y...
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This note was uploaded on 02/29/2012 for the course STATS 315A taught by Professor Tibshirani,r during the Winter '10 term at Stanford.

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