An introduction to nonparametric multimodal regression

Authors: María Alonso-Pena

Abstract: The mean, the median and the mode are the classical location measures introduced in any elementary course in statistics. Although mean and median based statistical methods are the usual approaches in different contexts, the mode seems to be somehow neglected. This paper gives a review on nonparametric multimodal regression, an approach for regression where, instead of seeking the mean of the conditional density, as in classical regression models, the conditional local modes are targeted. In addition to revising the existing literature on multimodal regression, the finite sample performance of the multimodal regression  estimator is explored with both simulated and real data examples.

Citation: Alonso-Pena, M. (2020). An introduction to nonparametric multimodal regression. Boletín de Estadística e Investigación Operativa, 36(1), 5-23.

Highlights:

Literature review of multimodal regression estimation

Simulation study comparing alternatives for selecting the smoothing parameters

New considerations about multimodal regression