Smooth Terms using s() and pb()

Examples on how to set up models using smooth terms with s() and pb().

References

Eilers, P. H. C., and B. D. Marx. 2021. Practical Smoothing: The Joys of p-Splines. Cambridge University Press.

Fahrmeir, Ludwig, Thomas Kneib, Stefan Lang, and Brian Marx. 2021. Regression – Models, Methods and Applications. 2nd ed. Berlin: Springer-Verlag. https://doi.org/10.1007/978-3-662-63882-8.

Hofner, B., A. Mayr, N. Robinzonov, and M. Schmid. 2014. “Model-Based Boosting in r: A Hands-on Tutorial Using the r Package Mboost.” Computational Statistics 29: 3–35.

Hofner, B., A. Mayr, and M. Schmid. 2016. “gamboostLSS: An R Package for Model Building and Variable Selection in the GAMLSS Framework.” Journal of Statistical Software 74 (1): 1–31.

Kleiber, C., and A. Zeileis. 2016. “Visualizing Count Data Regressions Using Rootograms.” The American Statistician 70 (3): 296–303.

Lang, Stefan, Nikolaus Umlauf, Peter Wechselberger, Kenneth Harttgen, and Thomas Kneib. 2012. “Multilevel Structured Additive Regression.” Statistics and Computing 24 (2): 223–38. https://doi.org/10.1007/s11222-012-9366-0.

Mayr, A., N. Fenske, B. Hofner, T. Kneib, and M. Schmid. 2012. “Generalized Additive Models for Location, Scale and Shape for High Dimensional Data, a Flexible Approach Based on Boosting.” J. R. Statist. Soc. Series C 61: 403–27.

Rigby, R. A., and D. M. Stasinopoulos. 2005. “Generalized Additive Models for Location, Scale and Shape.” Journal of the Royal Statistical Society Series C (Applied Statistics) 54 (3): 507–54. https://doi.org/10.1111/j.1467-9876.2005.00510.x.

Rigby, R. A., D. M. Stasinopoulos, G. Z. Heller, and F. De Bastiani. 2019. Distributions for Modeling Location, Scale, and Shape: Using GAMLSS in r. Boca Raton: Chapman & Hall/CRC.

Stadlmann, S. 2019. Distreg.vis: Framework for the Visualization of Distributional Regression Models. https://CRAN.R-project.org/package=distreg.vis.

Stasinopoulos, D. M., R. A. Rigby, and F. De Bastiani. 2018. “GAMLSS: A Distributional Regression Approach.” Statistical Modelling 18 (3-4): 248–73.

Stasinopoulos, D. M., R. A. Rigby, N. Giorgikopoulos, and F. De Bastiani. 2022. “Principal component regression in GAMLSS applied to Greek–German government bond yield spreads.” Statistical Modelling 22 (1-2): 127–45. https://doi.org/10.1177/1471082X211022980.

Stasinopoulos, D. M., R. A. Rigby, G. Z. Heller, V. Voudouris, and F. De Bastiani. 2017. Flexible Regression and Smoothing: Using GAMLSS in r. Boca Raton: Chapman & Hall/CRC.

Stasinopoulos, Dimitrios M, Robert A Rigby, Gillian Z Heller, and Fernanda De Bastiani. 2023. “P-Splines and GAMLSS: A Powerful Combination, with an Application to Zero-Adjusted Distributions.” Statistical Modelling 23 (5-6): 510–24.

Stasinopoulos, M. D., T. Kneib, N. Klein, A. Mayr, and G. Z Heller. 2024. Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, with Applications. Vol. 56. Cambridge University Press.

Umlauf, N., N. Klein, and Α. Zeileis. 2018. “BAMLSS: Bayesian Additive Models for Location, Scale and Shape (and Beyond).” Journal of Computational and Graphical Statistics 27: 612–27.