The smoots Package in R for Semiparametric Modeling of Trend Stationary Time Series
Y. Feng, T. Gries, S. Letmathe, D. Schulz, The R Journal 14 (2022) 182–195.
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Journal Article
| Published
| English
Author
Feng, Yuanhua;
Gries, Thomas;
Letmathe, Sebastian;
Schulz, Dominik
Publishing Year
Journal Title
The R Journal
Volume
14
Issue
1
Page
182-195
ISSN
LibreCat-ID
Cite this
Feng Y, Gries T, Letmathe S, Schulz D. The smoots Package in R for Semiparametric Modeling of Trend Stationary Time Series. The R Journal. 2022;14(1):182-195. doi:10.32614/rj-2022-017
Feng, Y., Gries, T., Letmathe, S., & Schulz, D. (2022). The smoots Package in R for Semiparametric Modeling of Trend Stationary Time Series. The R Journal, 14(1), 182–195. https://doi.org/10.32614/rj-2022-017
@article{Feng_Gries_Letmathe_Schulz_2022, title={The smoots Package in R for Semiparametric Modeling of Trend Stationary Time Series}, volume={14}, DOI={10.32614/rj-2022-017}, number={1}, journal={The R Journal}, publisher={The R Foundation}, author={Feng, Yuanhua and Gries, Thomas and Letmathe, Sebastian and Schulz, Dominik}, year={2022}, pages={182–195} }
Feng, Yuanhua, Thomas Gries, Sebastian Letmathe, and Dominik Schulz. “The Smoots Package in R for Semiparametric Modeling of Trend Stationary Time Series.” The R Journal 14, no. 1 (2022): 182–95. https://doi.org/10.32614/rj-2022-017.
Y. Feng, T. Gries, S. Letmathe, and D. Schulz, “The smoots Package in R for Semiparametric Modeling of Trend Stationary Time Series,” The R Journal, vol. 14, no. 1, pp. 182–195, 2022, doi: 10.32614/rj-2022-017.
Feng, Yuanhua, et al. “The Smoots Package in R for Semiparametric Modeling of Trend Stationary Time Series.” The R Journal, vol. 14, no. 1, The R Foundation, 2022, pp. 182–95, doi:10.32614/rj-2022-017.
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