Dynamic semi-parametric factor model for functional expectiles-Reference-Cited by-同舟云学术

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Dynamic semi-parametric factor model for functional expectiles

Published:2019-04-03 Issue:2 Volume:34 Page:489-502
ISSN:0943-4062
Container-title:Computational Statistics
language:en
Short-container-title:Comput Stat

Author:

Burdejová Petra^ORCID,Härdle Wolfgang K.

Funder

German Research Foundation (DFG) via Collaborative Research Center 649 ”Economic Risk”

German Research Foundation (DFG) via International Research Training Group 1792 ”High Dimensional Nonstationary Time Series’

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability

Link

http://link.springer.com/content/pdf/10.1007/s00180-019-00883-1.pdf

Reference29 articles.

1. Benko M, Härdle W, Kneip A (2009) Common functional principal components. Ann Stat 37(1):1–34, 02. https://doi.org/10.1214/07-AOS516

2. Borke L, Härdle WK (2017a) Q3-D3-LSA. In: Härdle WK, Lu HH, Shen X (eds) Handbook of big data analytics. Springer, New York. https://doi.org/10.2139/ssrn.2871111

3. Borke L, Härdle WK (2017b) GitHub API based QuantNet mining infrastructure in R. Discussion Paper SFB2017-08, Humboldt-Universität zu Berlin. https://doi.org/10.2139/ssrn.2927901

4. Breckling J, Chambers R (1988) M-quantiles. Biometrika 75:761–771. https://doi.org/10.2307/2336317

5. Burdejova P, Härdle W, Kokoszka P, Xiong Q (2017) Change point and trend analyses of annual expectile curves of tropical storms. Econom Stat 1:101–117. https://doi.org/10.1016/j.ecosta.2016.09.002

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