A regression model on distributional data in a context of functional data analysis through an appropriate LDQ transformation
The results of the model in terms of the original distributional variable, can be obtained, minus a constant, by applying the inverse transformation of the LDQ. To this end, a minimum value estimation model of the original quantile functions is proposed to estimate the constant lost in the reconstruction.
Finally, we show the performance of the regression model on real and simulated data.
Keywords: Distributional data analysis regression model LDQ transformation