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On weak dependence conditions: The case of discrete valued processes

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On weak dependence conditions: The case of discrete valued processes. / Doukhan, P.; Fokianos, K.; Li, X.
In: Statistics and Probability Letters, Vol. 82, No. 11, 11.2012, p. 1941-1948.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Doukhan, P, Fokianos, K & Li, X 2012, 'On weak dependence conditions: The case of discrete valued processes', Statistics and Probability Letters, vol. 82, no. 11, pp. 1941-1948. https://doi.org/10.1016/j.spl.2012.06.020

APA

Doukhan, P., Fokianos, K., & Li, X. (2012). On weak dependence conditions: The case of discrete valued processes. Statistics and Probability Letters, 82(11), 1941-1948. https://doi.org/10.1016/j.spl.2012.06.020

Vancouver

Doukhan P, Fokianos K, Li X. On weak dependence conditions: The case of discrete valued processes. Statistics and Probability Letters. 2012 Nov;82(11):1941-1948. Epub 2012 Jun 26. doi: 10.1016/j.spl.2012.06.020

Author

Doukhan, P. ; Fokianos, K. ; Li, X. / On weak dependence conditions : The case of discrete valued processes. In: Statistics and Probability Letters. 2012 ; Vol. 82, No. 11. pp. 1941-1948.

Bibtex

@article{b47341ec426b4e5e88411f066293e214,
title = "On weak dependence conditions: The case of discrete valued processes",
abstract = "We investigate the relationship between weak dependence and mixing for discrete valued processes. We show that weak dependence implies mixing conditions under natural assumptions. The results specialize to the case of Markov processes. Several examples of integer valued processes are discussed and their weak dependence properties are investigated by means of a contraction principle. In fact, we show the stronger result that the mixing coefficients for infinite memory weakly dependent models decay geometrically fast. Hence, all integer values models that we consider have weak dependence coefficients which decay geometrically fast.",
keywords = "Contraction, Dependence, Integer autoregressive processes, Mixing, Thinning operator",
author = "P. Doukhan and K. Fokianos and X. Li",
year = "2012",
month = nov,
doi = "10.1016/j.spl.2012.06.020",
language = "English",
volume = "82",
pages = "1941--1948",
journal = "Statistics and Probability Letters",
issn = "0167-7152",
publisher = "Elsevier",
number = "11",

}

RIS

TY - JOUR

T1 - On weak dependence conditions

T2 - The case of discrete valued processes

AU - Doukhan, P.

AU - Fokianos, K.

AU - Li, X.

PY - 2012/11

Y1 - 2012/11

N2 - We investigate the relationship between weak dependence and mixing for discrete valued processes. We show that weak dependence implies mixing conditions under natural assumptions. The results specialize to the case of Markov processes. Several examples of integer valued processes are discussed and their weak dependence properties are investigated by means of a contraction principle. In fact, we show the stronger result that the mixing coefficients for infinite memory weakly dependent models decay geometrically fast. Hence, all integer values models that we consider have weak dependence coefficients which decay geometrically fast.

AB - We investigate the relationship between weak dependence and mixing for discrete valued processes. We show that weak dependence implies mixing conditions under natural assumptions. The results specialize to the case of Markov processes. Several examples of integer valued processes are discussed and their weak dependence properties are investigated by means of a contraction principle. In fact, we show the stronger result that the mixing coefficients for infinite memory weakly dependent models decay geometrically fast. Hence, all integer values models that we consider have weak dependence coefficients which decay geometrically fast.

KW - Contraction

KW - Dependence

KW - Integer autoregressive processes

KW - Mixing

KW - Thinning operator

U2 - 10.1016/j.spl.2012.06.020

DO - 10.1016/j.spl.2012.06.020

M3 - Journal article

VL - 82

SP - 1941

EP - 1948

JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

SN - 0167-7152

IS - 11

ER -