Sparse vector heterogeneous autoregressive model with nonconvex penalties-Reference-Cited by-同舟云学术

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Sparse vector heterogeneous autoregressive model with nonconvex penalties

Published:2022-01-31 Issue:1 Volume:29 Page:53-64
ISSN:2287-7843
Container-title:Communications for Statistical Applications and Methods
language:en
Short-container-title:Communications for Statistical Applications and Methods

Author:

Shin Andrew Jaeho¹,Park Minsu¹,Baek Changryong¹

Affiliation:

1. Department of Statistics, Sungkyunkwan University, Korea

Funder

National Research Foundation of Korea

Publisher

Communications for Statistical Applications and Methods

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,Finance,Modeling and Simulation,Statistics and Probability

Link

http://pdf.medrang.co.kr/CSAM/2022/029/CSAM029-01-53.pdf

Reference13 articles.

1. Modeling and Forecasting Realized Volatility

2. Periodic dynamic factor models: estimation approaches and applications

3. Baek CR and Park MS (2020). Sparse vector heterogeneous autoregressive modeling for realized volatility. <italic>Journal of the Korean Statistical Society</italic>, <bold>50</bold>, 1-16.

4. Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection

5. Extended Bayesian information criteria for model selection with large model spaces

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Robust estimation of sparse vector autoregressive models;Korean Journal of Applied Statistics;2022-10-31

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