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

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23<br />

Step one, continued<br />

•<br />

≤<br />

[ f (x)<br />

nh<br />

∫<br />

n −(2+δ) 2 1+δ 1<br />

h 1+δ<br />

K 2 (v) dv {1 + u (1)}] −(2+δ)/2<br />

× n×<br />

∫<br />

max f (t)<br />

t∈[a,b]<br />

K 2+δ (v) dv {1 + u (1)}<br />

≤ Cn (2+δ)/2+1−(2+δ) h (2+δ)/2−(1+δ) = Cn −δ/2 h −δ/2 = C (nh) −δ/2<br />

• Lyapunov CLT shows<br />

V −1<br />

n<br />

n∑<br />

i=1<br />

ξ in<br />

D<br />

→ N (0, 1) ,<br />

{ f (x)<br />

nh<br />

∫<br />

} −1/2 ∑ n<br />

K 2 (v) dv<br />

i=1<br />

ξ in<br />

D<br />

→ N (0, 1)<br />

ST5207 Nonparametric Regression, 27th January 2005

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