scholarly journals A uniform central limit theorem for dependent variables

2009 ◽  
Vol 36 (2) ◽  
pp. 129-138
Author(s):  
Konrad Furmańczyk
2012 ◽  
Vol 82 (5) ◽  
pp. 1021-1027 ◽  
Author(s):  
Jongsig Bae ◽  
Changha Hwang ◽  
Doobae Jun

Author(s):  
P. H. Diananda

In a previous paper (4) central limit theorems were obtained for sequences of m-dependent random variables (r.v.'s) asymptotically stationary to second order, the sufficient conditions being akin to the Lindeberg condition (3). In this paper similar theorems are obtained for sequences of m-dependent r.v.'s with bounded variances and with the property that for large n, where s′n is the standard deviation of the nth partial sum of the sequence. The same basic ideas as in (4) are used, but the proofs have been simplified. The results of this paper are examined in relation to earlier ones of Hoeffding and Robbins(5) and of the author (4). The cases of identically distributed r.v.'s and of vector r.v.'s are mentioned.


2021 ◽  
pp. 699-723
Author(s):  
James Davidson

After some technical preliminaries, this chapter gives two contrasting proofs of the functional central limit theorem for near‐epoch dependent functions of mixing processes. It goes on to consider variants of the result for nonstationary increments in which the limits are transformed Brownian motions, subject to distortions of the time domain. The multivariate case of the result is also given.


2003 ◽  
Vol 67 (3) ◽  
pp. 467-480 ◽  
Author(s):  
Jongsig Bae ◽  
Sungyeun Kim

Let be the Kaplan-Meier integral process constructed from the random censorship model. We prove a uniform central limit theorem for {Un} under the bracketing entropy condition and mild conditions due to the censoring effects. We also prove a sequential version of the uniform central limit theorem that will give a functional law of the iterated logarithm of Strassen type.


Sign in / Sign up

Export Citation Format

Share Document