STAT444 Lecture Notes - Lecture 12: Local Regression, Smoothing Spline, Linear Combination

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K be a smooth and symmetric nnivaviate density function . Kh ) at exp c- e) need a scale bandwidth parameter h . Zina kh ( x - xi ) yi. The bandwidth parameter h determines the width of the local neighbourhood larger h leads to lower variance but larger bias. The local construct ( nw ) estimator has. Kh ( x - xi ) ( yi latex and the fitted value fix) 21mt p( dx ( o ) has an explict solution. Then ( o ) can be written as f^ ( x ) ( 1. ) ( btw ( ) b) It ( x ) y where the lxn vector. I " ( x ) ( 1. ( btwh ) b) t btw ( x ) Local linear regression is a linear smoother i. e. fh) is a linear combination of.

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