We address the problem of sequence prediction for nonstationary sto-chastic processes. In particular, given two measures on the set of one-way infinite sequences over a finite alphabet, consider the question whether one of the measures predicts the other. We find some conditions on local absolute continuity under which prediction is possible.
The one-step prediction problem is studied in the context of Pn-weakly stationary stochastic process...
We construct prediction intervals for the observations of first-order autoregressive processes when ...
We present an example of stationary process with long-time memory for which we can calculate explici...
Suppose we are given two probability measures on the set of one-way infinite finite-alphabet sequenc...
International audienceSuppose we are given two probability measures on the set of one-way infinite f...
International audienceSuppose we are given two probability measures on the set of one-way infinite f...
We address the problem of sequence prediction for nonstationary stochastic processes. In particular,...
We address the problem of sequence prediction for nonstationary stochastic processes. In particular,...
Suppose we are given two probability measures on the set of one-way infinite finite-alphabet sequenc...
AbstractSuppose we are given two probability measures on the set of one-way infinite finite-alphabet...
Suppose we are given two probability measures on the set of one-way infinite finite-alphabet sequenc...
International audienceA sequence x1,...,xn,... of discrete-valued observations is generated accordin...
We present data-dependent learning bounds for the general scenario of non-stationary non-mixing stoc...
International audienceWe consider the problem of sequence prediction in a probabilistic setting. Let...
International audienceWe consider the problem of sequence prediction in a probabilistic setting. Let...
The one-step prediction problem is studied in the context of Pn-weakly stationary stochastic process...
We construct prediction intervals for the observations of first-order autoregressive processes when ...
We present an example of stationary process with long-time memory for which we can calculate explici...
Suppose we are given two probability measures on the set of one-way infinite finite-alphabet sequenc...
International audienceSuppose we are given two probability measures on the set of one-way infinite f...
International audienceSuppose we are given two probability measures on the set of one-way infinite f...
We address the problem of sequence prediction for nonstationary stochastic processes. In particular,...
We address the problem of sequence prediction for nonstationary stochastic processes. In particular,...
Suppose we are given two probability measures on the set of one-way infinite finite-alphabet sequenc...
AbstractSuppose we are given two probability measures on the set of one-way infinite finite-alphabet...
Suppose we are given two probability measures on the set of one-way infinite finite-alphabet sequenc...
International audienceA sequence x1,...,xn,... of discrete-valued observations is generated accordin...
We present data-dependent learning bounds for the general scenario of non-stationary non-mixing stoc...
International audienceWe consider the problem of sequence prediction in a probabilistic setting. Let...
International audienceWe consider the problem of sequence prediction in a probabilistic setting. Let...
The one-step prediction problem is studied in the context of Pn-weakly stationary stochastic process...
We construct prediction intervals for the observations of first-order autoregressive processes when ...
We present an example of stationary process with long-time memory for which we can calculate explici...