To cite the methodology or journal article, please use: Feng, Y., Gries, T., Letmathe, S., and Schulz, D. (2022). The smoots Package in R for Semiparametric Modeling of Trend Stationary Time Series. The R Journal, 14(1), 182-195.<doi:10.32614/RJ-2022-017>.

To cite the specific software version/manual, please use: Feng, Y., Letmathe, S., and Schulz, D. (2026). smoots: Nonparametric Estimation of the Trend and Its Derivatives in TS. R package version 1.1.5.<doi:10.32614/CRAN.package.smoots>.

Corresponding BibTeX entries:

  @Article{,
    title = {The smoots Package in R for Semiparametric Modeling of
      Trend Stationary Time Series},
    author = {Yuanhua Feng and Thomas Gries and Sebastian Letmathe and
      Dominik Schulz},
    journal = {The R Journal},
    year = {2022},
    volume = {14},
    number = {1},
    pages = {182-195},
    doi = {10.32614/RJ-2022-017},
  }

  @Manual{,
    title = {smoots: Nonparametric Estimation of the Trend and Its
      Derivatives in TS},
    author = {Yuanhua Feng and Sebastian Letmathe and Dominik Schulz
      and Thomas Gries and Marlon Fritz},
    year = {2026},
    note = {R package version 1.1.5},
    doi = {10.32614/CRAN.package.smoots},
  }