Random central limit theorem for associated random variables and the order of approximation

2016 ◽  
Vol 111 ◽  
pp. 1-7
Author(s):  
B.L.S. Prakasa Rao ◽  
M. Sreehari
2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Yuanying Jiang ◽  
Qunying Wu

In this paper, the almost sure central limit theorem is established for sequences of negatively associated random variables:limn→∞(1/logn)∑k=1n(I(ak≤Sk<bk)/k)P(ak≤Sk<bk)=1, almost surely. This is the local almost sure central limit theorem for negatively associated sequences similar to results by Csáki et al. (1993). The results extend those on almost sure local central limit theorems from the i.i.d. case to the stationary negatively associated sequences.


2002 ◽  
Vol 29 (3) ◽  
pp. 125-131 ◽  
Author(s):  
Khurelbaatar Gonchigdanzan

We prove an almost sure central limit theorem (ASCLT) for strongly mixing sequence of random variables with a slightly slow mixing rateα(n)=O((loglogn)−1−δ). We also show that ASCLT holds for an associated sequence of random variables without a stationarity assumption.


Filomat ◽  
2017 ◽  
Vol 31 (5) ◽  
pp. 1413-1422 ◽  
Author(s):  
Qunying Wu ◽  
Yuanying Jiang

Let X,X1,X2,... be a stationary sequence of negatively associated random variables. A universal result in almost sure central limit theorem for the self-normalized partial sums Sn/Vn is established, where: Sn = ?ni=1 Xi,V2n = ?ni=1 X2i .


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