• Thomas Yee. Author, maintainer.

  • Cleve Moler. Contributor.
    LINPACK routines in src

Citation

Thomas W. Yee (2015). Vector Generalized Linear and Additive Models: With an Implementation in R. New York, USA: Springer.

@Book{,
  title = {Vector Generalized Linear and Additive Models: With an Implementation in R},
  author = {T. W. Yee},
  year = {2015},
  publisher = {Springer},
  address = {New York, USA},
}

Thomas W. Yee and C. J. Wild (1996). Vector Generalized Additive Models. Journal of Royal Statistical Society, Series B, 58(3), 481--493.

@Article{,
  title = {Vector Generalized Additive Models},
  author = {T. W. Yee and C. J. Wild},
  journal = {Journal of Royal Statistical Society, Series B},
  year = {1996},
  volume = {58},
  number = {3},
  pages = {481--493},
}

Thomas W. Yee (2010). The VGAM Package for Categorical Data Analysis. Journal of Statistical Software, 32(10), 1-34. DOI: 10.18637/jss.v032.i10. URL https://www.jstatsoft.org/article/view/v032i10/.

@Article{,
  title = {The {VGAM} Package for Categorical Data Analysis},
  author = {T. W. Yee},
  journal = {Journal of Statistical Software},
  year = {2010},
  volume = {32},
  number = {10},
  pages = {1--34},
  doi = {10.18637/jss.v032.i10},
}

Thomas W. Yee, Alfian F. Hadi (2014). Row-column interaction models, with an R implementation. Computational Statistics, 29(6), 1427--1445.

@Article{,
  title = {Row-column interaction models, with an {R} implementation},
  author = {T. W. Yee and A. F. Hadi},
  journal = {Computational Statistics},
  year = {2014},
  volume = {29},
  number = {6},
  pages = {1427--1445},
}

Thomas W. Yee (2025). VGAM: Vector Generalized Linear and Additive Models. R package version 1.1-13. URL https://CRAN.R-project.org/package=VGAM

@Manual{,
  title = {{VGAM}: Vector Generalized Linear and Additive Models},
  author = {T. W. Yee},
  year = {2025},
  note = {R package version 1.1-13},
  url = {https://CRAN.R-project.org/package=VGAM},
}

Thomas W. Yee (2013). Two-parameter reduced-rank vector generalized linear models. Computational Statistics and Data Analysis, 71, 889--902.

@Article{,
  title = {Two-parameter reduced-rank vector generalized linear models},
  author = {T. W. Yee},
  journal = {Computational Statistics and Data Analysis},
  year = {2013},
  volume = {71},
  pages = {889--902},
}

Thomas W. Yee, Jakub Stoklosa, Richard M. Huggins (2015). The VGAM Package for Capture-Recapture Data Using the Conditional Likelihood. Journal of Statistical Software, 65(5), 1--33. DOI: 10.18637/jss.v065.i05. URL https://www.jstatsoft.org/article/view/v065i05/.

@Article{,
  title = {The {VGAM} Package for Capture-Recapture Data Using the Conditional Likelihood},
  author = {T. W. Yee and J. Stoklosa and R. M. Huggins},
  journal = {Journal of Statistical Software},
  year = {2015},
  volume = {65},
  number = {5},
  pages = {1--33},
  doi = {10.18637/jss.v065.i05},
}

Thomas W. Yee (2020). The VGAM package for negative binomial regression. Australian and New Zealand Journal of Statistics, 62(1), 116--131.

@Article{,
  title = {The {VGAM} package for negative binomial regression},
  author = {T. W. Yee},
  journal = {Australian and New Zealand Journal of Statistics},
  year = {2020},
  volume = {62},
  number = {1},
  pages = {116--131},
}

Thomas W. Yee (2022). On the Hauck-Donner effect in Wald tests: Detection, tipping points and parameter space characterization. Journal of the American Statistical Association, 117(540), 1763--1774.

@Article{,
  title = {On the {H}auck-{D}onner effect in {W}ald tests: {D}etection, tipping points and parameter space characterization},
  author = {T. W. Yee},
  journal = {Journal of the American Statistical Association},
  year = {2022},
  volume = {117},
  number = {540},
  pages = {1763--1774},
}

Thomas W. Yee and Chenchen Ma (2024). Generally altered, inflated, truncated and deflated regression. Statistical Science, 39(4), 568--588.

@Article{,
  title = {Generally altered, inflated, truncated and deflated regression},
  author = {T. W. Yee and C. Ma},
  journal = {Statistical Science},
  year = {2024},
  volume = {39},
  number = {4},
  pages = {568--588},
}