It is shown here how to extend the spectral characterization of the
strong law of large numbers for weakly stationary processes to certain singular
averages. For instance, letting ${X_t, t \in R^3}$ be a weakly stationary
field, ${X_t}$ satisfies the usual SLLN (by averaging over balls) if and only if
the averages of ${X_t}$ over spheres of increasing radii converge pointwise.
The same result in two dimensions is false. This spectral approach also
provides a necessary and sufficient condition for the a.s. convergence of some
series of stationary variables.
@article{1039639364,
author = {Houdr\'e, C. and Lacey, M. T.},
title = {Spectral criteria, SLLN's and A.S. convergence of series of
stationary variables},
journal = {Ann. Probab.},
volume = {24},
number = {2},
year = {1996},
pages = { 838-856},
language = {en},
url = {http://dml.mathdoc.fr/item/1039639364}
}
Houdré, C.; Lacey, M. T. Spectral criteria, SLLN's and A.S. convergence of series of
stationary variables. Ann. Probab., Tome 24 (1996) no. 2, pp. 838-856. http://gdmltest.u-ga.fr/item/1039639364/