The Annals of Probability

On 1-Dependent Processes and $k$-Block Factors

Robert M. Burton, Marc Goulet, and Ronald Meester
Source: Ann. Probab. Volume 21, Number 4 (1993), 2157-2168.

Abstract

A stationary process $\{X_n\}_{n \in \mathbb{Z}}$ is said to be $k$-dependent if $\{X_n\}_{n < 0}$ is independent of $\{X_n\}_{n > k-1}$. It is said to be a $k$-block factor of a process $\{Y_n\}$ if it can be represented as $X_n = f(Y_n,\ldots, Y_{n+k-1}),$ where $f$ is a measurable function of $k$ variables. Any $(k + 1)$-block factor of an i.i.d. process is $k$-dependent. We answer an old question by showing that there exists a one-dependent process which is not a $k$-block factor of any i.i.d. process for any $k$. Our method also leads to generalizations of this result and to a simple construction of an eight-state one-dependent Markov chain which is not a two-block factor of an i.i.d. process.

First Page: Show Hide
Primary Subjects: 60G10
Secondary Subjects: 54H20, 28D05
Full-text: Open access
Links and Identifiers

Permanent link to this document: http://projecteuclid.org/euclid.aop/1176989014
JSTOR: links.jstor.org
Digital Object Identifier: doi:10.1214/aop/1176989014
Mathematical Reviews number (MathSciNet): MR1245304
Zentralblatt MATH identifier: 0788.60049


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The Annals of Probability

The Annals of Probability

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