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.
Supplementary materials are available in addition to this article. It can be downloaded at RJ-2018-018.zip
Bayesian, Econometrics, Environmetrics, SocialSciences
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For attribution, please cite this work as
Jensen & Panduro, "The R Journal: PanJen: An R package for Ranking Transformations in a Linear Regression", The R Journal, 2018
BibTeX citation
@article{RJ-2018-018,
author = {Jensen, Cathrine Ulla and Panduro, Toke Emil},
title = {The R Journal: PanJen: An R package for Ranking Transformations in a Linear Regression},
journal = {The R Journal},
year = {2018},
note = {https://doi.org/10.32614/RJ-2018-018},
doi = {10.32614/RJ-2018-018},
volume = {10},
issue = {1},
issn = {2073-4859},
pages = {109-121}
}