Moda condicional: un enfoque vía regresión cuantílica suavizada

Recently, it has been proposed to estimate the conditional mode of a response, given a vector of covariates, using a computationally scalable estimator derived from the linear quantile regression model. Alternatively, we propose to estimate the conditional mode by maximizing a smoothed conditional density estimator. This approach offers at least two benefits: computational efficiency and good asymptotic behavior which, in particular, bypasses the curse of dimensionality.