A collection of parametric modal regression models for bounded data

ABSTRACT

Modal regression is an alternative approach for investigating the relationship between the most likely response and covariates and can hence reveal important structure missed by usual regression methods. This paper provides a collection of parametric mode regression models for bounded response variable by considering some recently introduced probability distributions with bounded support along with the well-established Beta and Kumaraswamy distribution. The main properties of the distributions are highlighted and compared. An empirical comparison between the considered modal regression is demonstrated through the analysis of three data sets from health and social science. For reproducible research, the proposed models are freely available to users as an R package unitModalReg.

KEYWORDS:

• Parametric modal regression
• Beta distribution
• Kumaraswamy distribution

Acknowledgments

The authors are thankful to the referees for many valuable suggestions. Josmar Mazucheli gratefully acknowledge the partial financial support from Fundação Araucária (Grant 064/2019 - UEM/Fundação Araucária).