Lecture3 Slide - The Department of Statistics and Applied Probability ...

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34 Digression to density estimation • { } AMISE ˆf (x) ; h = 1 nh c K + ∫ f ′′ (x) 2 dx h 4 d 2 K 4 • To find the optimal h, solve the following equation d { } dh AMISE ˆf (x) ; h = − 1 ∫ nh 2 c K + f ′′ (x) 2 dxh 3 d 2 K = 0 ST5207 Nonparametric Regression, 27th January 2005
35 Digression to density estimation • { } AMISE ˆf (x) ; h = 1 nh c K + ∫ f ′′ (x) 2 dx h 4 d 2 K 4 • To find the optimal h, solve the following equation d { } dh AMISE ˆf (x) ; h = − 1 ∫ nh 2 c K + f ′′ (x) 2 dxh 3 d 2 K = 0 • <strong>The</strong> optimal b<strong>and</strong>width is h opt = { c K d 2 K } 1/5 1 ∫ f ′′ (x) 2 n −1/5 dx ST5207 Nonparametric Regression, 27th January 2005
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Page 3 and 4: 3 Step one, continued • E |ξ in
Page 15 and 16: 15 Step one, continued • E |K h (
Page 21 and 22: 21 Step one, continued • ≤ [ f
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Page 25 and 26: 25 Digression to density estimation
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Lecture3 Slide - The Department of Statistics and Applied Probability ...

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