Barbour introduced a probabilistic view of Stein's method for
estimating the error in probability approximations. However, in the case of
approximations by general distributions on the integers, there have been no
purely probabilistic proofs of Stein's bounds till this paper. Furthermore, the
methods introduced here apply to a very large class of approximating
distributions on the non-negative integers, among which there is a natural
class for higher-order approximations by probability distributions rather than
signed measures (as previously). The methods also produce Stein magic factors
for process approximations which do not increase with the window of observation
and which are simpler to apply than those in Brown, Weinberg and Xia.
@article{1015345606,
author = {Brown, Timothy C. and Xia, Aihua},
title = {Stein's Method and Birth-Death Processes},
journal = {Ann. Probab.},
volume = {29},
number = {1},
year = {2001},
pages = { 1373-1403},
language = {en},
url = {http://dml.mathdoc.fr/item/1015345606}
}
Brown, Timothy C.; Xia, Aihua. Stein's Method and Birth-Death Processes. Ann. Probab., Tome 29 (2001) no. 1, pp. 1373-1403. http://gdmltest.u-ga.fr/item/1015345606/