The R Journal: article published in 2018, volume 10:1

PanJen: An R package for Ranking Transformations in a Linear Regression
Cathrine Ulla Jensen and Toke Emil Panduro , The R Journal (2018) 10:1, pages 109-121.

Abstract PanJen is an R-package for ranking transformations in linear regressions. It provides users with the ability to explore the relationship between a dependent variable and its independent variables. The package offers an easy and data-driven way to choose a functional form in multiple linear regression models by comparing a range of parametric transformations. The parametric functional forms are benchmarked against each other and a non-parametric transformation. The package allows users to generate plots that show the relation between a covariate and the dependent variable. Furthermore, PanJen will enable users to specify specific functional transformations, driven by a priori and theory-based hypotheses. The package supplies both model fits and plots that allow users to make informed choices on the functional forms in their regression. We show that the ranking in PanJen outperforms the Box-Tidwell transformation, especially in the presence of inefficiency, heteroscedasticity or endogeneity.

Received: 2017-05-12; online 2018-05-21, supplementary material, (1 KiB)
CRAN packages: PanJen, mgcv
CRAN Task Views implied by cited CRAN packages: Bayesian, Econometrics, Environmetrics, SocialSciences

This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2018-018,
  author = {Cathrine Ulla Jensen and Toke Emil Panduro},
  title = {{PanJen: An R package for Ranking Transformations in a Linear
          Regression}},
  year = {2018},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2018-018},
  url = {https://doi.org/10.32614/RJ-2018-018},
  pages = {109--121},
  volume = {10},
  number = {1}
}