scholarly journals Complete moment convergence for moving average process generated by ρ − $\rho^{-}$ -mixing random variables

2015 ◽  
Vol 2015 (1) ◽  
Author(s):  
Yong Zhang
Keyword(s):  
Moving Average ◽  
Random Variables ◽  
Complete Moment Convergence ◽  
Average Process ◽  
Moving Average Process ◽  
Moment Convergence ◽  
Mixing Random Variables

scholarly journals Complete Convergence for Moving Average Process of Martingale Differences

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Wenzhi Yang ◽  
Shuhe Hu ◽  
Xuejun Wang
Keyword(s):  
Complete Convergence ◽  
Moving Average ◽  
Random Variables ◽  
Complete Moment Convergence ◽  
Average Process ◽  
Moving Average Process ◽  
Martingale Differences ◽  
Moment Convergence ◽  
Moving Process

Under some simple conditions, by using some techniques such as truncated method for random variables (see e.g., Gut (2005)) and properties of martingale differences, we studied the moving process based on martingale differences and obtained complete convergence and complete moment convergence for this moving process. Our results extend some related ones.

scholarly journals On Complete Convergence of Moving Average Process for AANA Sequence

2012 ◽  
Vol 2012 ◽  
pp. 1-24 ◽  
Author(s):  
Wenzhi Yang ◽  
Xuejun Wang ◽  
Nengxiang Ling ◽  
Shuhe Hu
Keyword(s):  
Complete Convergence ◽  
Moving Average ◽  
Random Variables ◽  
Partial Sums ◽  
Complete Moment Convergence ◽  
Average Process ◽  
Moving Average Process ◽  
Moment Convergence ◽  
The Moment ◽  
Asymptotically Almost Negatively Associated

We investigate the moving average process such thatXn=∑i=1∞aiYi+n,n≥1, where∑i=1∞|ai|<∞and{Yi,1≤i<∞}is a sequence of asymptotically almost negatively associated (AANA) random variables. The complete convergence, complete moment convergence, and the existence of the moment of supermum of normed partial sums are presented for this moving average process.

Complete moment convergence of moving average processes under ρ-mixing assumption

2011 ◽  
Vol 61 (6) ◽  
Author(s):  
Xing-Cai Zhou ◽  
Jin-Guan Lin
Keyword(s):  
Infinite Sequence ◽  
Moving Average ◽  
Random Variables ◽  
Partial Sums ◽  
Complete Moment Convergence ◽  
Real Numbers ◽  
Moment Convergence ◽  
Summable Sequence ◽  
Moving Average Processes ◽  
Mixing Random Variables

AbstractLet {Y i: −∞ < i < ∞} be a doubly infinite sequence of identically distributed ρ-mixing random variables, and {a i: −∞ < i < ∞} an absolutely summable sequence of real numbers. In this paper we prove the complete moment convergence for the partial sums of moving average processes $\{ X_n = \sum\limits_{i = - \infty }^\infty {a_i Y_{i + n,} n \geqslant 1} \} $ based on the sequence {Y i: −∞ < i < ∞} of ρ-mixing random variables under some suitable conditions.

scholarly journals Complete Moment Convergence of Weighted Sums for Arrays of Rowwiseφ-Mixing Random Variables

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Ming Le Guo
Keyword(s):  
Moving Average ◽  
Random Sequence ◽  
Sufficient Conditions ◽  
Random Variables ◽  
Weighted Sums ◽  
Complete Moment Convergence ◽  
Moment Inequality ◽  
Moment Convergence ◽  
Moving Average Processes ◽  
Mixing Random Variables

The complete moment convergence of weighted sums for arrays of rowwiseφ-mixing random variables is investigated. By using moment inequality and truncation method, the sufficient conditions for complete moment convergence of weighted sums for arrays of rowwiseφ-mixing random variables are obtained. The results of Ahmed et al. (2002) are complemented. As an application, the complete moment convergence of moving average processes based on aφ-mixing random sequence is obtained, which improves the result of Kim et al. (2008).

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