Forecasting for stationary binary time series

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dc.creatorMorvai, Gusztav
dc.creatorWeiss, Benjamin
dc.date2007-10-26
dc.date.accessioned2026-07-07T09:45:12Z
dc.date.available2026-07-07T09:45:12Z
dc.descriptionThe forecasting problem for a stationary and ergodic binary time series $\{X_n\}_{n=0}^{\infty}$ is to estimate the probability that $X_{n+1}=1$ based on the observations $X_i$, $0\le i\le n$ without prior knowledge of the distribution of the process $\{X_n\}$. It is known that this is not possible if one estimates at all values of $n$. We present a simple procedure which will attempt to make such a prediction infinitely often at carefully selected stopping times chosen by the algorithm. We show that the proposed procedure is consistent under certain conditions, and we estimate the growth rate of the stopping times.
dc.identifierhttps://arxiv.org/abs/0710.5144
dc.identifierhttp://arxiv.org/abs/0710.5144
dc.identifierActa Appl. Math. 79 (2003), no. 1-2, 25--34
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/163120
dc.subjectProbability
dc.subjectInformation Theory
dc.titleForecasting for stationary binary time series
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