scholarly journals Stein’s method via induction

2020 ◽  
Vol 25 (0) ◽  
Author(s):  
Louis H.Y. Chen ◽  
Larry Goldstein ◽  
Adrian Röllin
1997 ◽  
Vol 34 (4) ◽  
pp. 898-907 ◽  
Author(s):  
Aihua Xia

This note gives the rate for a Wasserstein distance between the distribution of a Bernoulli process on discrete time and that of a Poisson process, using Stein's method and Palm theory. The result here highlights the possibility that the logarithmic factor involved in the upper bounds established by Barbour and Brown (1992) and Barbour et al. (1995) may be superfluous in the true Wasserstein distance between the distributions of a point process and a Poisson process.


1984 ◽  
Vol 26 (1) ◽  
pp. 8-15 ◽  
Author(s):  
A. D. Barbour ◽  
Peter Hall

2007 ◽  
Vol 39 (3) ◽  
pp. 731-752 ◽  
Author(s):  
Martin Raič

Large deviation estimates are derived for sums of random variables with certain dependence structures, including finite population statistics and random graphs. The argument is based on Stein's method, but with a novel modification of Stein's equation inspired by the Cramér transform.


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