Prove Theorem XXXXXXXXXXHint: Put m                              ¯ R(x) = ‑ Sx,R m(z)µ(dz) µ(Sx,R) , then, by Lemma 24.6,                                    im...


Prove Theorem 25.17. Hint: Put m


                             ¯ R(x) = ‑ Sx,R m(z)µ(dz) µ(Sx,R) ,


then, by Lemma 24.6,


                                   im R→0 m¯ R(x) = m(x) mod µ.


Given x − X(kn,n)(x)= R, the distribution of


                                 (X(1,n)(x), Y(1,n)(x)),..., (X(kn,n)(x), Y(kn,n)(x))


is the same as the distribution of the nearest neighbor permutation of the i.i.d.


                                 (X∗ 1 (x), Y ∗ 1 (x)),..., (X∗ kn (x), Y ∗ kn (x)),


  where


                              P{X∗ i (x) ∈ A, Y ∗ i (x) ∈ B} = P{Xi ∈ A, Yi ∈ B|Xi ∈ Sx,R},


therefore,


                   E{Y ∗ i (x)} = E{Yi|Xi ∈ Sx,R} = ¯mR(x).


Thus, by Hoeffding’s inequality,


                                         P  1 kn kn i=1 Y(i,n)(x) − m¯ R(x) > x − X(kn,n)(x)


                                           = R  = P  1 kn kn i=1 (Y ∗ i (x) − EY ∗ i (x)) >


                                            ≤ 2e − kn2 2L2 ,


which is summable because of kn/ log n → ∞.

May 03, 2022
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