Ergodicity and central limit theorem for random interval homeomorphisms



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i

n

i

Σn



[0,1]


Pn(di)μ(dy) for t R

it

exp

Φn(t) =
ϕ(f 1(y)) + ·· · + ϕ(fn(y))




and

Φn(t) =
x
ϕ(f 1(x)) + ·· · + ϕ(fn(x))





i

n

i

exp

it

Pn(di) for t R.
From the first part of the proof we know that there exists σ ≥ 0 such that for
every t R

Φn(t) exp
t2σ2
as n .


2
Therefore, to finish the proof it is sufficient to show for every t ∈ R the conver- gence

x
|Φn(t) Φn(t)|→ 0 as n → ∞.
Since |eitx1 eitx2 |≤ |t||x1 x2| for every t R, for sufficiently large n N
and x [εn, 1 εn] using μ PM,α we have


| |x
t
|Φ (t) Φn(t)| ≤√ ·



(ϕ(fj(x)) ϕ(fj(y))) Pn(di)μ(dy)

n n
|t|
[0,1]
i i
Σn j=1

Σ

i

i

n



n

[ε ,1−ε ]
≤√
(ϕ(fj(x)) ϕ(fj(y))) Pn(di)μ(dy)

n
|t|
n n j=1


α

+ n · 2nϕn

n
|t|


n

[ε ,1−ε ]

A \D

i

i
≤√
(ϕ(fj (x))−ϕ(f j(y))) Pn(di)μ(dy)

n
|t|
n n n


α
j=1
|t|

+ n · 2n∗ϕ∗Mεn + n · 2n∗ϕ∗(Pnn \ An)+ Pn(Dn)).
Since εn 0 as n , for every x (0, 1) and t R, by (5.2) and using the
estimates Pn(Bn) (1 β) n and P (D ) 2 , we finally obtain
8

n
n n



lim
n→∞
|Φn(t) Φn




  1. |≤
    lim

n→∞
2|t|

n



x
n

3
(C1Ln 8 + n


ϕ∗(1 β) √8 n)

This completes the proof.
+ lim
n→∞

2|t|∗ϕ∗n((1 δ) √4 n + α) = 0.





Corollary 2: If the assumptions of Theorem 4 are satisfied, then the sta-

n

k=0
tionary sequence ( 1 [nt] ϕ(Xk)) converges in distribution to σW (t), where
W (t), 0 t 1 is a Brownian motion. Moreover, for μ-a.e. x (0, 1) the

n

k=0

k
sequence ( 1 [nt] ϕ(Xx)) also converges in distribution to σW (t), 0 ≤ t ≤ 1.




n


Proof. From the proof of Theorem 4 it follows that the Maxwell–Woodroofe condition

n =1
n
3

j=1
Ujϕ <


L2(μ)

is satisfied. Applying Theorem 1.1 in [28] we obtain the first assertion. On the other hand, the second assertion follows from Theorem 2.7 in [9].


Acknowledgments. The authors wish to express their gratitude to an anony- mous referee for thorough reading of the manuscript and valuable remarks.

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