How Sampling Reveals a Process
Ornstein, Donald S. ; Weiss, Benjamin
Ann. Probab., Tome 18 (1990) no. 4, p. 905-930 / Harvested from Project Euclid
A series of observations $\{\xi_1, \xi_2, \xi_3,\ldots\}$ is presented to us and at each time $n$, when we have observed the first $n$ of them, we are called upon to give our guess for what stochastic process produced the data. A universal scheme is given which, for any Bernoulli process (not necessarily independent), gives a sequence of processes that converges in a strong sense (the $\bar{d}$-metric) to the real process. In addition to this main result, many others are given which put it into proper perspective. In particular it is shown that in a certain sense the class of Bernoulli processes is the largest one for which such a universal scheme is possible.
Publié le : 1990-07-14
Classification:  Stationary process,  ergodic theory,  entropy,  Shannon-McMillan theorem,  prediction,  Bernoulli shifts,  60G10,  60F15,  28D05,  28D10
@article{1176990729,
     author = {Ornstein, Donald S. and Weiss, Benjamin},
     title = {How Sampling Reveals a Process},
     journal = {Ann. Probab.},
     volume = {18},
     number = {4},
     year = {1990},
     pages = { 905-930},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176990729}
}
Ornstein, Donald S.; Weiss, Benjamin. How Sampling Reveals a Process. Ann. Probab., Tome 18 (1990) no. 4, pp.  905-930. http://gdmltest.u-ga.fr/item/1176990729/