Semiparametric, parametric, and possibly sparse models for multivariate long-range dependence

Changryong Baek; Stefanos Kechagias; Vladas Pipiras

doi:10.1117/12.2275101

24 August 2017 Semiparametric, parametric, and possibly sparse models for multivariate long-range dependence

Changryong Baek, Stefanos Kechagias, Vladas Pipiras

Proceedings Volume 10394, Wavelets and Sparsity XVII; 103941S (2017) https://doi.org/10.1117/12.2275101
Event: SPIE Optical Engineering + Applications, 2017, San Diego, California, United States

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.

Citation Download Citation

Changryong Baek, Stefanos Kechagias, and Vladas Pipiras "Semiparametric, parametric, and possibly sparse models for multivariate long-range dependence", Proc. SPIE 10394, Wavelets and Sparsity XVII, 103941S (24 August 2017); https://doi.org/10.1117/12.2275101

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