Distance in the metric of L1 of the distribution of a sum of weakly dependent random variables from the normal distribution function

1983 ◽  
Vol 22 (2) ◽  
pp. 177-189 ◽  
Author(s):  
J. Sunklodas
Keyword(s):  
Distribution Function ◽  
Normal Distribution ◽  
Random Variables ◽  
Normal Distribution Function ◽  
Dependent Random Variables ◽  
Weakly Dependent Random Variables ◽  
Weakly Dependent

Moment bounds for non-stationary dependent sequences

1994 ◽  
Vol 31 (3) ◽  
pp. 731-742 ◽  
Author(s):  
Tae Yoon Kim
Keyword(s):  
Random Variables ◽  
Partial Sums ◽  
Unified Approach ◽  
Dependent Random Variables ◽  
Combinatorial Argument ◽  
Stationarity Condition ◽  
Weakly Dependent Random Variables ◽  
Mixing Sequences ◽  
Moment Bounds ◽  
Weakly Dependent

We provide a unified approach for establishing even-moment bounds for partial sums for a class of weakly dependent random variables satisfying a stationarity condition. As applications, we discuss moment bounds for various types of mixing sequences. To obtain even-moment bounds, we use a ‘combinatorial argument' developed by Cox and Kim (1990).

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