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Proceedings Paper

Semiparametric, parametric, and possibly sparse models for multivariate long-range dependence
Author(s): Changryong Baek; Stefanos Kechagias; Vladas Pipiras
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Paper Abstract

Several available formulations, parametric models and sparsity settings for multivariate long-range dependence (MLRD) are discussed. Furthermore, a new parametric identifiable model for a general formulation of MLRD is introduced in any dimension, and another sparsity setting is identified of potential interest in MLRD modeling. Estimation approaches for MLRD are also reviewed, including some recent progress and open questions about estimation in higher dimensions and sparse settings.

Paper Details

Date Published: 24 August 2017
PDF: 14 pages
Proc. SPIE 10394, Wavelets and Sparsity XVII, 103941S (24 August 2017); doi: 10.1117/12.2275101
Show Author Affiliations
Changryong Baek, Sungkyunkwan Univ. (Korea, Republic of)
Stefanos Kechagias, SAS Institute Inc. (United States)
Vladas Pipiras, The Univ. of North Carolina at Chapel Hill (United States)

Published in SPIE Proceedings Vol. 10394:
Wavelets and Sparsity XVII
Yue M. Lu; Dimitri Van De Ville; Manos Papadakis, Editor(s)

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